Healthy States, Progressive India - NITI Aayog

Healthy States, Progressive IndiaR e p o r t o n t h e R a n k s o f S t a t e s a n d U n i o n T e r r i t o r i e s

Ministry of Health & Family Welfare

Visit http://social.niti.gov.in/ to download this report, state-wise data and other content

ForewordNITI Aayog has been mandated with transforming India by exercising thought leadership and by invoking the instruments of co-operative and competitive federalism, focussing the attention of the State Governments and Union Ministries on achieving outcomes. As the nodal agency responsible for charting India’s quest for attaining the commitments under the Sustainable Development Goals (SDGs), it was necessary to devise a mechanism for measuring outcomes particularly in the critical social sectors – such as Health and Education, where India’s record has been less than stellar. This was intended to provide feedback to all stakeholders as to whether we are on course to what we have set out to achieve, and deviations, if any, to be pointed out in time to ensure necessary mid-course correction.

It is important to realize that implementation of social sector programs is squarely in the domain of the State Governments and India’s achievement of SDGs is therefore critically dependent on the action in the States. Nudging States towards improving their social outcomes therefore requires developing indices that would capture annual increments in performance through an independent third party process and publish these. It is true that summarizing the complexities of a given sector and condensing it in an Index has its own limitations. However, in an environment where the focus is on budget spends and outputs with limited attention on outcomes, there is a need to increase competition among States to encourage them to strive evermore for increasing the pace of change.

The Health of its population is central to a nation’s well-being and productivity. While India has made some significant gains in improving life expectancy and reducing infant and maternal mortality, our rates of improvement have been inadequate as a nation.

Further, there are large variations in health system performance and outcomes achieved across States. The “Performance in Health Outcomes” Index seeks to capture the annual progress of States and Union Territories (UTs) on a variety of indicators – Outcomes, Governance and Processes. While we have also reported the overall levels of performance of States, the focus of the NITI Index is to propel change, highlighting those States that have shown most improvement. The exercise has been spearheaded by NITI Aayog in collaboration with the Ministry of Health and Family Welfare, with technical assistance from the World Bank, the authors of this report on the ranks and their interpretation.

The exercise, which is the first of its kind attempted by the Union Government was conducted over a period of eighteen months. In addition to the technical expertise of the World Bank, experts in public health, economics, statistics and health systems were consulted in the development of the Index. It involved extensive engagement with the States for finalization of the indicators, sensitization workshops for sharing the methodology, process of data submission and addressing concerns; mentoring of States for the data submission process on an online portal and independent data validation.

The process of Index development and implementation highlighted the large gaps in data availability on health outcomes.The need for making outcome data available for smaller states, more frequent and updated outcomes for non-communicable diseases and financial protection, and the need for robust programmatic data that can be used for continuous monitoring, were important issues that despite our efforts, could not be addressed optimally in this first round. Despite these challenges and limitations, it was decided to launch the Index in the first year as a model to measuring performance and ranking States on change. We thereby hope to spur action on several fronts in bringing about national level transformation. We will strive to address the lessons learned in this first round and refine the Index in the successive years of its implementation. The linking of the Health Index with incentives under the National Health Mission by the Ministry of Health and Family Welfare underlines the importance of such an exercise. It re-emphasizes the move towards performance based financing for better outcomes.

I would like to acknowledge here the large number of individuals who contributed to the initiative being brought to completion of its first round. The Ministry of Health and Family Welfare under the guidance of Mr. C.K. Mishra, former Secretary, Department of Health & Family Welfare; Ms. Preeti Sudan, Secretary,

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Department of Health & Family Welfare; Mr. Manoj Jhalani, Additional Secretary and Mission Director, National Health Mission, as well as the Joint Secretaries and their teams from the programme divisions provided their complete support to the initiative and worked in close co-ordination with NITI Aayog during its entire course.

Technical Assistance to NITI Aayog was provided through the entire duration by The World Bank, along with authorship of this report. We are grateful to Mr. Junaid Kamal Ahmad, Country Director and the technical team led by Ms. Sheena Chhabra, Senior Health Specialist along with Dr. Rattan Chand, Senior Consultant; Dr. Nikhil Utture, Consultant; and Dr. Iryna Postolovska, Young Professional with support from Ms. Manveen Kohli, Consultant. Peer review of the final report by Dr. Rekha Menon, Practice Manager; Dr. Ajay Tandon, Lead Economist; Dr. Mickey Chopra, Global Lead on Service Delivery; and Dr. Owen K. Smith, Senior Economist is gratefully acknowledged.

Inputs from statistical, economics and sector experts including Prof. Pulak Ghosh, IIM-Bangalore; Prof. Karthik Muralidharan, University of California, San Diego; Prof. Ladu Singh, International Institute of Population Sciences; Prof. Arvind Pandey, ICMR; Prof. Mudit Kapoor, Indian Statistical Institute; Dr. Shamika Ravi, Brookings India (and currently a Member of the Economic Advisory Council to the Prime Minister), were obtained at various stages of the project. Support provided by the Registrar General and Census Commissioner of India and the officials from the Office of Registrar General and Census Commissioner, India is gratefully acknowledged. Inputs received from Technical Organizations including UNICEF and DFID are also acknowledged.

NITI Aayog is most grateful to senior officials of the Health departments, nodal officers and their teams in all the States and UTs for their extensive co-operation throughout the project, including providing inputs and feedback during the development of the index, participation in regional sensitization workshops, submission of data on the online portal and provision of required supporting documentation/evidence for validation of data.

The mentor organizations, USAID (led by Mr. Xerxes Sidhwa and Mr. Gautam Chakraborty, and the team led by Ms. Alia Kauser and Dr. Rashmi Kukreja), Regional Resource Centre for the North Eastern States, branch of National Health Systems Resource Centre, MoHFW (led by Dr. Bamin Tada and Mr. Bhaswat Das), Centre for Innovations in Public Systems (led by Dr. Nivedita Haran) and TERI (led by Ms. Meena Sehgal) provided their valuable support to the States during the data submission phase of the project. Extended mentor support provided by Mr. Pankaj Gupta, USAID is also gratefully acknowledged. The data validation was conducted by the team at IPE Global led by Mr. Soumitro Ghosh and Ms. Daljeet Kaur. The online portal was developed by Silvertouch Technologies, led by Ms. Surbhi Singhal and Mr. Rushiraj Yadav.

The project was designed and executed under the guidance of the senior leadership of NITI Aayog,Dr. Arvind Panagariya, former Vice Chairman, NITI Aayog; Dr. Rajiv Kumar, Vice Chairman, NITI Aayog; Dr. Bibek Debroy, Member and Dr. Vinod Paul, Member, NITI Aayog. The Health Division team led by Mr. Alok Kumar, Adviser; Mr. Sumant Narain, former Director; Dr. Dinesh Arora, Director, and Dr. Kheya Furtado, Research Assistant, with support from Ms. Jyoti Khattar, Senior Research Officer planned, implemented and co-ordinated the entire project.

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Amitabh KantChief Executive Of�cer, NITI Aayog

AbbreviationsAHPI Association of Healthcare Providers (India)ANC Antenatal CareANM Auxiliary Nurse MidwifeART Antiretroviral TherapyBCG Bacillus Calmette–Guérin BY Base YearCCU Cardiac Care UnitCHC Community Health CentreCIPS Centre for Innovation in Public SystemsCMO Chief Medical OfficerCRS Civil Registration SystemC-Section Caesarean SectionDH District HospitalDPT Diphtheria, Pertussis, and Tetanus EAG Empowered Action Group ENT Ear-Nose-ThroatGBD Global Burden of DiseaseFLV First Level VerificationFRU First Referral UnitHb HemoglobinHIV Human Immunodeficiency VirusHMIS Health Management Information SystemHRMIS Human Resources Management Information SystemIDSP Integrated Disease Surveillance ProgrammeIMR Infant Mortality RateINR Indian RupeesIVA Independent Validation AgencyISO International Organization for StandardizationIT Information TechnologyJSSK Janani Shishu Suraksha KaryakramJSY Janani Suraksha YojanaLBW Low Birth WeightL Form IDSP Reporting Format for Laboratory SurveillanceMCTS Mother and Child Tracking SystemMCTFC Mother and Child Tracking Facilitation CentreMIS Management Information SystemMMR Maternal Mortality RatioMO Medical OfficerMoHFW Ministry of Health and Family WelfareNA Not ApplicableNABH National Accreditation Board for Hospitals and Healthcare ProvidersNACO National AIDS Control OrganizationNCDs Non-communicable DiseasesNE North-EasternNFHS National Family Health SurveyNHM National Health MissionNHP National Health PolicyNITI National Institution for Transforming India

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NMR Neonatal Mortality RateNQAS National Quality Assurance StandardsOPV Oral Polio VaccineORGI Office of the Registrar General and Census Commissioner, IndiaOOP Out-of-Pocket PCPNDT Pre-Conception and Pre-Natal Diagnostic TechniquesP Form IDSP Reporting Format for Presumptive SurveillancePHC Primary Health CentrePLHIV People Living with HIVRRC-NE Regional Resource Centre for North Eastern StatesRNTCP Revised National Tuberculosis Control ProgrammeRU Reporting UnitRY Reference YearSBR Still Birth RateSC Sub-CentreSDGs Sustainable Development GoalsSDH Sub-District HospitalSLV Second Level VerificationSRB Sex Ratio at BirthSRS Sample Registration SystemSN Staff NurseSNO State Nodal OfficerTA Technical AssistanceTB TuberculosisTERI The Energy Research InstituteTFR Total Fertility RateU5MR Under-Five Mortality RateUSAID United States Agency for International DevelopmentUTs Union Territories

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ContentsFOREWORD i

ABBREVIATIONS iii

LIST OF TABLES vii

LIST OF FIGURES viii

EXECUTIVE SUMMARY 1

BACKGROUND 8

1. OVERVIEW – EVOLUTION AND RATIONALE 9

2. ABOUT THE INDEX – DEFINING AND MEASURING 10

2.1 Aim 10

2.2 Objectives 10

2.3 Salient Features 10

2.4 Methodology 10

2.4.1 Computation of Index scores and ranks 10

2.4.2 Categorization of States for ranking 11

2.4.3 The Health Index - List of indicators and weightage 12

2.5 Limitations of the Index 15

3. PROCESSES – FROM IDEA TO PRACTICE 17

3.1 Key stakeholders - Roles and responsibilities 17

3.2 Process �ow 17

3.2.1 Development of Index 18

3.2.2 Regional workshops with States 18

3.2.3 Submission of data on the portal 18

3.2.4 Independent validation of data 19

3.2.5 Index and rank generation 19

RESULTS AND FINDINGS 20

4. UNVEILING PERFORMANCE – ENCOURAGING ACTIONS 21

4.1 Performance of Larger States 21

4.1.1 Overall performance 21

4.1.2 Incremental performance 23

4.1.3 Domain-speci�c performance 25

4.1.4 Incremental performance on indicators 27

4.2 Performance of Smaller States 29





4.3. Performance of Union Territories 35



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4.4 States and Union Territories: Performance on indicators 40

WAY FORWARD 69

5. INSTITUTIONALIZATION – TAKING THE INDEX AHEAD 70

ANNEXURES 71

Annexure 1: Discrepancies in data and resolution 72

Annexure 2: Original Health Index 73

Annexure 3: Reference Year Index (with and without the indicator on out-of-pocket expenditure) 77

Annexure 4: Snapshot: State-wise performance on indicators 79

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List of TablesTable E.1 - Categorization of Larger States on incremental performance

and overall performance 5

Table E.2 - Categorization of Smaller States on incremental performance


Table E.3 - Categorization of Union Territories on incremental performance


Table 2.1 - Categorization of States and UTs 12

Table 2.2 - Health Index: Summary 12

Table 2.3 - Health Index: Indicators, de�nitions, data sources, base and reference years 13

Table 3.1 - Key stakeholders: Roles and responsibilities 17

Table 3.2 - Timeline for development of Health Index 17

Table 3.3 - Health Index regional workshops 18

Table 3.4 - List of mentor agencies 19

Table 4.1 - Larger States: Overall performance in reference year - Categorization 22

Table 4.2 - Larger States: Incremental performance from

base to reference year - Categorization 24

Table 4.3 - Smaller States: Overall performance in reference year - Categorization 30

Table 4.4 - Smaller States: Incremental performance from


Table 4.5 - Union Territories: Overall performance in reference year - Categorization 36

Table 4.6 - Union Territories: Incremental performance from


Table A.2.1 - Original Health Index indicators: A snapshot 73

Table A.2.2 - Original Health Index: Indicators, de�nitions and data sources 73

Table A.4.1 - Larger States: Health Outcomes domain indicators, base and reference years 80

Table A.4.2 - Larger States: Governance and information domain

indicators, base and reference years 82

Table A.4.3 - Larger States: Key Inputs/Processes domain indicators, base and reference years 83

Table A.4.4 - Smaller States: Health outcomes domain indicators, base and reference years 86

Table A.4.5 - Smaller States: Governance and information domain indicators,

base and reference years 86

Table A.4.6 - Smaller States: Key Inputs/Processes domain indicators, base and reference years 87

Table A.4.7 - Union Territories: Health outcomes domain indicators, base and reference years 88

Table A.4.8 - Union Territories: Governance and information domain indicators,


Table A.4.9 - Union Territories: Key Inputs/Processes domain indicators,


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List of FiguresFigure E.1 - Larger States: Incremental scores and ranks, with overall performance

from base year to reference year and ranks 3

Figure E.2 - Smaller States: Incremental scores and ranks, with overall performance from base year to reference year and ranks 4

Figure E.3 - Union Territories: Incremental scores and ranks, with overall performance from base year to reference year and ranks 5

Figure 3.1 - Steps for validating data 19

Figure 4.1 - Larger States: Overall performance - Composite Index score and rank, base and reference years 22

Figure 4.2 - Larger States: Overall and incremental performance, base and reference years and incremental rank 23

Figure 4.3 - Larger States: Overall and domain-speci�c performance, reference year 25

Figure 4.4 - Larger States: Performance in the Health Outcomes domain, base and reference years 26

Figure 4.5 - Larger States: Performance in the Key Inputs/Processes domain, base and reference years 27

Figure 4.6 - Larger States: Number of indicators/sub-indicators, by category of incremental performance 28

Figure 4.7 - Smaller States: Overall performance - Composite Index score and rank, base and reference years 29

Figure 4.8 - Smaller States: Overall and incremental performance, base and reference years and incremental rank 30

Figure 4.9 - Smaller States: Overall and domain-speci�c performance, reference year 32

Figure 4.10 - Smaller States: Performance in the Health Outcomes domain, base and reference years 32

Figure 4.11 - Smaller States: Performance in the Key Inputs/Processes domain, base and reference years 33

Figure 4.12 - Smaller States: Number of indicators/sub-indicators, by category of incremental performance 34

Figure 4.13 - Union Territories: Overall performance - Composite Index score and rank, base and reference years 35

Figure 4.14 - Union Territories: Overall and incremental performance, base and reference years and incremental rank 36

Figure 4.15 - Union Territories: Overall and domain-speci�c performance, reference year 38

Figure 4.16 - Union Territories: Performance in the Health Outcomes domain, base and reference years 38

Figure 4.17 - Union Territories: Performance in the Key Inputs/Processes domain, base and reference years 39

Figure 4.18 - Union Territories: Number of indicators/sub-indicators, by category of incremental performance 39

Figure 4.19 - Indicator 1.1.1: Neonatal Mortality Rate - Larger States 40

Figure 4.20 - Indicator 1.1.2: Under-�ve Mortality Rate - Larger States 41

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Figure 4.21 - Indicator 1.1.4: Proportion of Low Birth Weight among newborns - Larger States 42

Figure 4.22 - Indicator 1.1.4: Proportion of Low Birth Weight among newborns - Smaller States and UTs 42

Figure 4.23 - Indicator 1.1.5: Sex Ratio at Birth - Larger States 43

Figure 4.24 - Indicator 1.2.1: Full immunization coverage - Larger States 44

Figure 4.25 - Indicator 1.2.1: Full immunization coverage - Smaller States and UTs 44

Figure 4.26 - Indicator 1.2.2: Proportion of institutional deliveries - Larger States 45

Figure 4.27 - Indicator 1.2.2: Proportion of institutional deliveries - Smaller States and UTs 46

Figure 4.28 - Indicator 1.2.3: Total case noti�cation rate of TB - Larger States 46

Figure 4.29 - Indicator 1.2.3: Total case noti�cation rate of TB - Smaller States and UTs 47

Figure 4.30 - Indicator 1.2.4: Treatment success rate of new microbiologically con�rmed TB cases - Larger States 47

Figure 4.31 - Indicator 1.2.4: Treatment success rate of new microbiologically con�rmed TB cases - Smaller States and UTs 48

Figure 4.32 - Indicator 1.2.5: Proportion of people living with HIV on antiretroviral therapy - Larger States 48

Figure 4.33 - Indicator 1.2.5: Proportion of people living with HIV on antiretroviral therapy - Smaller States 49

Figure 4.34 - Indicator 1.2.6: Average out-of-pocket expenditure per delivery in public health facility (in INR) - Larger States 49

Figure 4.35 - Indicator 1.2.6: Average out-of-pocket expenditure per delivery in public health facility (in INR) - Smaller States and UTs 50

Figure 4.36 - Indicator 2.1.1: Data Integrity Measure - Institutional deliveries - Larger States 50

Figure 4.37 - Indicator 2.1.1: Data Integrity Measure - ANC registered within �rst trimester - Larger States 51

Figure 4.38 - Indicator 2.1.1: Data Integrity Measure - Institutional deliveries - Smaller States and UTs 51

Figure 4.39 - Indicator 2.1.1: Data Integrity Measure - ANC registered within �rst trimester - Smaller States and UTs 51

Figure 4.40 - Indicator 2.2.1: Average occupancy of an of�cer (in months) combined for three key posts at State-level for last three years - Larger States 52

Figure 4.41 - Indicator 2.2.1: Average occupancy of an of�cer (in months) combined for three key posts at State-level for last three years - Smaller States and UTs 53

Figure 4.42 - Indicator 2.2.2: Average occupancy of a full-time of�cer (in months) for all the districts in last three years - CMOs or equivalent post - Larger States 54

Figure 4.43 - Indicator 2.2.2: Average occupancy of a full-time of�cer (in months) for all the districts in last three years - CMOs or equivalent post - Smaller States and UTs 54

Figure 4.44 - Indicator 3.1.1a: Proportion of vacant healthcare provider positions - ANMs at sub-centres - Larger States 55

Figure 4.45 - Indicator 3.1.1a: Proportion of vacant healthcare provider positions - ANMs at sub-centres - Smaller States 56

Figure 4.46 - Indicator 3.1.1b: Proportion of vacant healthcare provider positions - Staff nurses at PHCs and CHCs - Larger States 56

x

Figure 4.47 - Indicator 3.1.1c: Proportion of vacant healthcare provider positions - Medical of�cers at PHCs - Larger States 57

Figure 4.48 - Indicator 3.1.1c: Proportion of vacant healthcare provider positions - Medical of�cers at PHCs - Smaller States 57

Figure 4.49 - Indicator 3.1.1.d: Proportion of vacant healthcare provider positions - Specialists at district hospitals - Larger States 58

Figure 4.50 - Indicator 3.1.1d: Proportion of vacant healthcare provider positions - Specialists at district hospitals - Smaller States and UTs 58

Figure 4.51 - Indicator 3.1.3.a: Proportion of speci�ed type of facilities functioning as First Referral Units - Larger States 59

Figure 4.52 - Indicator 3.1.3.a: Proportion of speci�ed type of facilities functioning as First Referral Units - Smaller States 60

Figure 4.53 - Indicator 3.1.3.b: Proportion of functional 24x7 PHCs - Larger States 61

Figure 4.54 - Indicator 3.1.3.b: Proportion of functional 24x7 PHCs - Smaller States 61

Figure 4.55 - Indicator 3.1.4: Proportion of districts with functional Cardiac Care Units - Larger States 62

Figure 4.56 - Indicator 3.1.5: Proportion of ANC registered within �rst trimester against total registrations - Larger States 63

Figure 4.57 - Indicator 3.1.5: Proportion of ANC registered within �rst trimester against total registrations - Smaller States and UTs 63

Figure 4.58 - Indicator 3.1.6: Level of registration of births - Larger States 64

Figure 4.59 - Indicator 3.1.6: Level of registration of births - Smaller States and UTs 65

Figure 4.60 - Indicator 3.1.7: Completeness of IDSP reporting of P form - Larger States 66

Figure 4.61 - Indicator 3.1.7: Completeness of IDSP reporting of P and L forms - Smaller States 66

Figure 4.62 - Indicator 3.1.8: Proportion of CHCs with grading above 3 points - Larger States 67

Figure 4.63 - Indicator 3.1.10: Average number of days for transfer of Central National Health Mission fund from State Treasury to implementation agency (Department/Society) based on all tranches of the last �nancial year - Larger States 68

Figure 4.64 - Indicator 3.1.10: Average number of days for transfer of Central NHMfund from State Treasury to implementation agency (Department/Society) based on all tranches of the last �nancial year - Smaller States and UTs 68

Figure A.3.1 - Larger States: Ranking for reference year (2015-16) with and without the OOP expenditure indicator 77

Figure A.3.2 - Smaller States: Ranking for reference year (2015-16) with and without OOP expenditure indicator 78

Figure A.3.3 - Union Territories: Ranking for reference year (2015-16) with and without OOPexpenditure indicator 78

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ExecutiveSummary

Background and MethodologyKey Results

Conclusions and Way Forward

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Background and Methodology1. The National Institution for Transforming India (NITI) Aayog is spearheading the Health Index

initiative to bring about transformational change in achieving desirable health outcomes: India has achieved significant economic growth over the past decades, but the progress in health has not been commensurate. Despite notable gains in improving life expectancy, reducing fertility, maternal and child mortality, and addressing other health priorities, the rates of improvement have been insufficient, falling short on several national and global targets. Furthermore, there are wide variations across States in their health outcomes and systems performance. In order to bring about transformational change in population health through a spirit of co-operative and competitive federalism, NITI Aayog has spearheaded the Health Index initiative, to measure the annual performance of States and Union Territories (UTs), and rank States on the basis of incremental change, while also providing an overall status of States’ performance and helping identify specific areas of improvement. It is envisaged that this tool will propel States towards undertaking multi-pronged interventions that will bring about the much-desired optimal population health outcomes.

2. Multiple stakeholders contributed to the Index development: The Index was developed by NITI Aayog with technical assistance from the World Bank through an iterative process in consultation with the Ministry of Health and Family Welfare (MoHFW), States and UTs, domestic and international sector experts and other development partners (Table 2.3 provides Health Index-indicator details and data sources).

3. States and UTs have been ranked on a composite Health Index in three categories (Larger States, Smaller States and UTs) to ensure comparison among similar entities: With a focus on outcomes, outputs and critical inputs, the main criteria for inclusion of indicators was the availability of reliable data for States and UTs, with at least an annual frequency. The Index is a weighted composite Index based on indicators in three domains: (a) Health Outcomes; (b) Governance and Information; and (c) Key Inputs/Processes, with each domain assigned a weight based on its importance. The indicator values are standardized (scaled 0 to 100) and used in generating composite Index scores and overall performance rankings for base year (2014-15) and reference year (2015-16). The annual incremental progress made by the States and UTs from base year to reference year is used to generate incremental ranks (Section 2 provides methodological details of constructing the Index). States and UTs have been ranked in three categories (Larger States, Smaller States and UTs) to ensure comparison among similar entities (Table 2.1 deals with categorization of States and UTs).

4. For generation of Index values and ranks, data was submitted online and validated by an Independent Validation Agency (IVA): The States were sensitized about the Health Index including indicator definitions, data sources and process for data submission through a series of regional workshops and mentor support was provided to most States (Table 3.4). Data was submitted by States on the online portal hosted by NITI Aayog and data from sources in the public domain was pre-entered. This data was then validated by an IVA and was used as an input into automated generation of Index values and ranks on the portal (Sections 3.2.4 and 3.2.5).

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Key Results5. There is a large gap in overall performance between the best and the least performing States and

UTs; besides, all States and UTs have substantial scope for improvement: In the reference year (2015-16) among Larger States, the Index score for overall performance ranged widely between 33.69 in Uttar Pradesh to 76.55 in Kerala. Similarly, among Smaller States, the Index score for overall performance varied between 37.38 in Nagaland to 73.70 in Mizoram, and among UTs this varied between 34.64 in Dadra & Nagar Haveli to 65.79 in Lakshadweep. Among Larger States, the variation between the best and least performing States and UTs was the widest around 43 points as compared with 36 points in Smaller States and 31 points in UTs. However, based on the highest observed overall Index scores in each category of States and UTs, clearly there is room for improvement in all States and UTs.

6. The States and UTs rank differently on overall performance and annual incremental performance: States and UTs that start at lower levels of the Health Index (lower levels of development of their health systems) are generally at an advantage in notching up incremental progress over States with high Health Index score due to diminishing marginal returns in outcomes for similar effort levels. It is a challenge for States at high levels of the Index score even to maintain their performance levels. For example, Kerala ranks on top in terms of overall performance and at the bottom in terms of incremental progress mainly as it had already achieved a low level of Neonatal Mortality Rate (NMR) and Under-five Mortality Rate (U5MR) and replacement level fertility, leaving limited space for any further improvements.

Figure E.1 - Larger States: Incremental scores and ranks, with overall performance from base year to reference year and ranks

-3.45Kerala

Punjab

Tamil Nadu

Gujarat

Himachal Pradesh

Maharashtra

Jammu & Kashmir

Andhra Pradesh

Karnataka

West Bengal

Telangana

Chhattisgarh

Haryana

Jharkhand

Uttarakhand

Assam

Madhya Pradesh

Odisha

Bihar

Rajasthan

Uttar Pradesh

21

6

15

19

17

10

2

7

18

13

12

5

20

1

16

11

9

14

4

8

3

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

76.55

3.19

0.10

-1.29

-0.92

0.98

6.83

2.41

-1.03

0.38

0.45

3.39

-2.90

6.87

-0.10

1.10

0.20

3.76

2.24

5.55

0.60

63.28

61.99

61.20 62.12

60.09

63.28

61.07

53.52

57.75

60.35

60.16

58.70 59.73

57.87 58.25

54.94 55.39

48.63 52.02

46.97 49.87

38.46 45.33

45.22 45.32

43.53 44.13

38.99 40.09

39.23 39.43

34.70

20 30 40 50 60 70 80

Overall Performance Index ScoreOverall Reference

Year RankIncremental

RankIncremental Change

-4 0 4 8

38.46

36.7934.55

33.6928.14

63.38

62.02

80.00

65.21

Reference Year (2015-16)Base Year (2014-15)

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7. Among the Larger States, Jharkhand, Jammu & Kashmir, and Uttar Pradesh are the top three ranking States in terms of annual incremental performance, while Kerala, Punjab, and Tamil Nadu ranked on top in terms of overall performance: In terms of annual incremental performance in Index scores from the base to the reference year, the top three ranked States in the group of Larger States are Jharkhand (up 6.87 points), Jammu & Kashmir (up 6.83 points) and Uttar Pradesh (up 5.55 points). However, in terms of overall levels of performance, these States are in the bottom two-third of the range of Index scores, with Kerala (76.55), Punjab (65.21) and Tamil Nadu (63.38) showing the highest scores. Jharkhand, Jammu & Kashmir, and Uttar Pradesh showed the maximum gains in improvement of health outcomes from base to reference year in indicators such as NMR, U5MR, full immunization coverage, institutional deliveries, and people living with HIV (PLHIV) on antiretroviral therapy (ART).

8. Among Smaller States, Manipur ranked �rst in terms of annual incremental performance and second in terms of overall performance, while Goa ranked second in terms of annual incremental performance: Among Smaller States, Mizoram (73.70) followed by Manipur (57.78) are the best overall performers. In annual incremental performance, Manipur (up 7.18 points) and Goa (up 6.67 points) ranked the highest. For Smaller States, among the top performers, the indicators that contributed to higher incremental performance varied. Manipur, ranked at the top and registered maximum incremental progress on indicators such as PLHIV on ART, first trimester antenatal care (ANC) registration, grading of Community Health Centres (CHCs) on quality parameters, average occupancy of three key State-level officers, and good reporting on the Integrated Disease Surveillance Programme (IDSP).

9. Among UTs, Lakshadweep showed both the highest annual incremental performance as well as the best overall performance: In annual incremental performance, Lakshadweep ranked at the top (up 9.56 points) followed by Andaman & Nicobar Islands (up 3.82 points). In terms of overall performance, Lakshadweep (65.79) ranked at the top, followed by Chandigarh (52.27). Lakshadweep showed the highest improvement in indicators such as institutional deliveries, tuberculosis (TB) treatment success rate and transfer of Central National Health Mission (NHM) funds from State Treasury to implementation agency.

Mizoram

Manipur

Meghalaya

Sikkim

Goa

Arunachal Pradesh

Tripura

Nagaland

71.27 73.70

53.20 53.39

50.60 57.78

51.40 56.83

49.51 50.60

46.46 53.13

43.51 48.35

37.38 45.26

30 40 50 60 70 80 -10 0 10

1

2

3

4

5

6

7

8

4

1

3

5

2

6

7

8

Overall Performance Index Score Incremental ChangeIncremental

Rank

OverallReferenceYear Rank


7.18

5.43

-0.19

-1.09

-4.84

-7.88

6.67

2.43

Figure E.2 - Smaller States: Incremental scores and ranks, with overall performance from base year to reference year and ranks

10. The incremental measurement shows that about one-third of the States have registered a decline in their Health Indices in the reference year as compared to the base year: This is a matter of concern and should nudge the States into reviewing and revitalizing their programmatic efforts. Among the Larger States, six States, namely Uttarakhand, Himachal Pradesh, Karnataka, Gujarat, Haryana and Kerala have shown a decline in performance from base year to reference year, despite some of them being among the top ten in overall performance. Among the Smaller States, Sikkim, Arunachal Pradesh, Tripura and Nagaland have shown a decline; and among the UTs, Chandigarh and Daman & Diu have shown a decline. Tables E.1, E.2 and E.3 provide a categorization of States and UTs based on the level of annual incremental performance and the overall performance.

56.23 65.79

52.27

48.05 50.02

46.18 50.00

46.54 47.48

36.10 44.77

34.6431.34

30 40 50 60 70 -10 -5 0 5 10

57.49

1

2

3

4

5

6

7

1

6

4

2

5

7

3

Overall Performance Index Score Incremental Change

Overall ReferenceYear Rank

IncrementalRank


1.97

3.82

0.94

3.30

9.56

-5.22

-8.67

Lakshadweep

Chandigarh

Delhi

Andaman & NicobarIslands

Puducherry

Daman & Diu

Dadra & Nagar Haveli

Figure E.3 - Union Territories: Incremental scores and ranks, with overall performance from base year to reference year and ranks

Table E.1 - Categorization of Larger States on incremental performance and overall performance

Note: Overall Performance: The States are categorized on the basis of reference year Index score range: Front-runners: top one-third (Index score>62); Achievers: middle one-third (Index score between 48 and 62), Aspirants: lowest one-third (Index score<48). Incremental Performance: The States are categorized on the basis of incremental Index score range: ‘Not Improved’ (incremental Index score<=0), ‘Least Improved’ (incremental Index score between 0.01 and 2), ‘Moderately Improved’ (incremental Index score between 2.01 and 4), ‘Most Improved’ (incremental Index score>4.0).

Incremental Performance Overall Performance

Aspirants Achievers Front-runnersNot Improved Uttarakhand Himachal Pradesh Kerala Haryana Karnataka Gujarat

Least Improved Madhya Pradesh Maharashtra Tamil Nadu Assam Telangana Odisha West Bengal

Moderately Improved Bihar Chhattisgarh Punjab Rajasthan Andhra Pradesh

Most Improved Jharkhand Jammu & Kashmir Uttar Pradesh

5

6

In terms of numbers of indicators, Chhattisgarh, Goa and Delhi showed improvement in the highest number of parameters, within the three categories of States respectively (Figures 4.6, 4.12, 4.18). The specific indicators for which the States’ performance has dipped or improved and actual values for these are provided in Annexure 4. The indicators where most States and UTs need to focus include addressing vacancies in key staff, establishment of functional district Cardiac Care Units (CCUs), quality accreditation of public health facilities, and institutionalization of Human Resources Management Information System (HRMIS). Additionally, almost all Larger States need to focus on improving the Sex Ratio at Birth (SRB).

11. The overall performance of States is not always consistent with the domain-speci�c performance: Some States fare significantly better in one domain than others, suggesting that there is scope to improve their performance in lagging domains with specific targeted interventions. For example, while most States showed a better performance in Health Outcomes, Tamil Nadu, West Bengal, Assam, Madhya Pradesh, Odisha, Rajasthan, Daman & Diu, and Dadra & Nagar Haveli performed better in terms of Key Inputs/Processes. Domain-wise incremental performance among the three categories of States showed the highest improvement in outcomes, respectively for Jammu & Kashmir, Uttar Pradesh and Jharkhand; Goa and Manipur; Andaman & Nicobar Islands and Lakshadweep.

Note: Overall Performance: The States are categorized on the basis of reference year Index score range: Front-runners: top one-third (Index score>61.60), Achievers: middle one-third (Index score between 49.49 and 61.60), Aspirants: lowest one-third (Index score <49.49).Incremental Performance: The States are categorized on the basis of incremental Index score range: ‘Not Improved’ (incremental Index score<=0), ‘Least Improved’ (incremental Index score between 0.01 and 2), ‘Moderately Improved’ (incremental Index score between 2.01 and 4), ‘Most Improved’ (incremental Index score>4.0).

Table E.2 - Categorization of Smaller States on incremental performance and overall performance

Table E.3 - Categorization of Union Territories based on incremental performance and overall performance

Note: Overall Performance: The UTs are categorized on the basis of reference year Index score range: Front-runners: top one-third (Index score>55), Achievers: middle one-third (Index score between 45 and 55), Aspirants: lowest one-third (Index score<45).For Incremental Performance: The UTs are categorized on the basis of incremental Index score range: ‘Not Improved’ (incremental Index score<=0), ‘Least Improved’ (incremental Index score between 0.01 and 2), ‘Moderately Improved’ (incremental Index score between 2.01 and 4), ‘Most Improved’ (incremental Index score>4.0).


Aspirants Achievers Front-runners

Not Improved Tripura Sikkim -

Nagaland Arunachal Pradesh

Least Improved - - -

Moderately Improved - - Mizoram

Most Improved - Manipur - Meghalaya Goa



Not Improved Daman & Diu Chandigarh -

Least Improved - Delhi

Puducherry -

Moderately Improved Dadra & Nagar Haveli Andaman & Nicobar Islands -

Most Improved - Lakshadweep

7

Conclusions and Way Forward12. The Health Index is a useful tool for systematic measurement of annual performance across

States and UTs: Rich learnings have emerged that will guide improvement of both the methods and the data to make the Index better. The Health Index is an important aid in understanding the heterogeneity and complexity of the nation’s performance in health. It is the first attempt at establishing an annual systematic tool for measurement of performance across States and UTs on a variety of health parameters within a composite measure. In its first year, it may not have achieved perfection; however, it does set the foundation for a systematic output and outcome based performance measurement. In linking this Index to incentives under the NHM, the MoHFW has underlined the importance of such an exercise. The results and analysis in this report provide an important insight into the areas in which States have improved, stagnated or declined and this will help in better targeting of interventions. Owing to the multiplicity of determinants that impact health outcomes, some of these actions may lie outside the ambit of health departments and, in fact, depend on the actions of the private sector and sectors other than health. The learnings that have emerged during the process of development of the Health Index, will guide in refining the Index for the coming year and also address some of the limitations. The exercise also calls for urgently improving the data systems in health, in terms of representativeness of the priority areas, periodic availability for all States and UTs, and completeness for private sector service delivery.

8

Background

Overview – evolution and rationaleAbout the Index – defining and measuring

Processes – from idea to practice

9

1. Overview – evolution and rationale India has achieved significant economic growth over the past decades, but the progress in health has not

been commensurate. The inability to rapidly improve the human capital also places a binding constraint on economic growth. Between 1991 and 2015, India made major improvements, for instance, life expectancy at birth increased by approximately 10 years; Infant Mortality Rate (IMR) more than halved; Total Fertility Rate (TFR) dropped to near replacement level; and Maternal Mortality Ratio (MMR) declined by more than 60 percent1. At the same time, non-communicable diseases (NCDs) have emerged as the leading cause of morbidity and death for adults, contributing to 55 percent of all disease burden and more than 62 percent of deaths in the country2. When compared with India’s economic progress and achievements, the rates of improvement in health outcomes have remained slower than that of developing countries with comparable levels of spending on health3. Furthermore, there is large variation in terms of health outcomes and health systems across States.

The National Development Agenda unanimously agreed to by all State Chief Ministers and Lieutenant Governors of Union Territories in 2015 had inter alia identified education, health, nutrition, women and children as priority sectors. To fulfil the National Development Agenda, it is imperative to make rapid improvement in these sectors. While the responsibility in this regard is shared between the Center and the States, given that health is a State subject, implementation is largely done by the States. The Center’s role is limited primarily to financing, setting policy principles and program guidelines.

India, along with other countries, has committed itself to adopting the Sustainable Development Goals (SDGs) to end poverty, protect the planet, and ensure prosperity for all as part of a new global sustainable development agenda to be fulfilled by 2030. There is renewed commitment in India to accelerate the pace of achievement of the SDGs, including Goal 3 related to ensuring healthy lives and promoting the well-being for all.

In order to bring about rapid transformative action in achieving the desired outcomes, a priority for NITI Aayog is to nudge the States towards improvement in outcomes in the coming years. The broader goal is to develop a spirit of co-operative and competitive federalism whereby the Center and States can jointly determine the route to progress and prosperity. It is in this context that NITI Aayog has spearheaded the Health Index initiative with the MoHFW, and has an explicit focus on the outcomes of health systems. Technical assistance for the Health Index initiative was provided by the World Bank. Various stakeholders, including the States, domestic and international sector experts and development partners, were consulted throughout the process and given the opportunity to provide feedback. An interactive web portal hosted by NITI Aayog, provided a pre-designed format for the States to submit data concerning identified indicators for the Health Index. The data was verified by IPE Global, an independent validation agency prior to computing the Index and ranks for all States and UTs.

The Health Index consists of 24 indicators grouped in the domains of Health Outcomes, Governance and Information, and Key Inputs/Processes. The States and UTs have been ranked in three categories to ensure comparison among similar entities - Larger States, Smaller States, and UTs. The Health Index will be calculated and disseminated annually, with a focus on measuring and highlighting annual incremental improvement in the States and UTs. The composite Health Index and ranking of States and UTs will assist in monitoring the States’ performance, also serving as an input for performance-based incentives, leading ultimately to improvements in the state of health in each State.

1 World Bank. 2017. World Development Indicators 2017. Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/26447 License: CC BY 3.0 IGO.2 Indian Council of Medical Research, Public Health Foundation of India, and Institute for Health Metrics and Evaluation. India: Health of the Nation's States — The India State-Level Disease Burden

Initiative. New Delhi, India: ICMR, PHFI, and IHME; 2017.3 Paper no I/2015, Working Paper Series I, Health Division, NITI Aayog.

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2. About the Index – defining and measuring2.1 AIM

To promote a co-operative and competitive spirit amongst the States and UTs to rapidly bring about transformative action in achieving the desired health outcomes.

2.2 OBJECTIVES

1. To develop a composite Health Index based on key health outcomes and other health systems and service delivery indicators.

2. To ensure States’ participation and ownership through Health Index data submission on a web-based portal with requested mentor support.

3. To build transparency through independent validation of data by an independent agency.

4. To generate Health Index scores and rankings for different categories of the States and UTs based on year-to-year progress (annual incremental performance) and overall performance.

2.3 SALIENT FEATURES

• The Health Index consists of a limited set of relevant indicators categorized in the domains of Health Outcomes, Governance and Information, and Key Inputs/Processes.

• Health Outcomes are assigned the highest weight, as these remain the focus of performance.

• Indicators have been selected on the basis of their importance and availability of reliable data at least annually from existing data sources such as the Sample Registration System (SRS), Civil Registration System (CRS) and Health Management Information Systems (HMIS).

• Data on indicators is included for Index calculations after validation by the IVA.

• A composite Index is calculated as a weighted average of various indicators, focused on measuring the state of health in each State and UT for a base year (BY) and a reference year (RY).

• The change in the Index score of each State from the base year to a reference year measures the annual incremental progress of each State.

• States and UTs have been grouped in three categories to ensure comparison among similar entities, namely 21 Larger States, 8 Smaller States, and 7 UTs.

2.4 METHODOLOGY

2.4.1 Computation of Index scores and ranks

After validation of data by the IVA, data submitted by the States and pre-entered from established sources was used for the Health Index score calculations. Each indicator value was scaled, based on the nature of the indicator. For positive indicators, where higher the value, better the performance (e.g. service coverage indicators), the scaled value (Si) for the ith indicator, with data value as Xi. was calculated as follows:

11

Similarly, for negative indicators where lower the value, better the performance (e.g. NMR, U5MR, human resource vacancies), the scaled value was calculated as follows:

The minimum and maximum values of each indicator were ascertained based on the values for that indicator across States within the grouping of States (Larger States, Smaller States, and UTs) for that year.

The scaled value for each indicator lies between the range of 0 to 100. Thus, for a positive indicator such as institutional deliveries, the State with the lowest institutional deliveries will get a scaled value of 0, while the State with the highest institutional deliveries will get a scaled value of 100. Similarly, for a negative indicator such as NMR, the State with the highest NMR will get a scaled value of 0, while the one with the lowest NMR will get a scaled value of 100. Accordingly, the scaled value of other States will lie between 0 and 100 in both cases.

Based on the above scaled values (Si), a composite Index score was then calculated for the base year and reference year after application of the weights using the following formula:

where Wi is the weight for ith indicator.

The composite Index score provides the overall performance and domain-wise performance for each State and UT, and has been used for generating overall performance ranks.

The difference between the composite Index score of reference and base years was used to compute the annual incremental performance. Ranks were also generated to ascertain the relative position of the States in terms of annual incremental performance.

The ranking is primarily based on the incremental progress made by the States and UTs from the base year to the reference year. However, rankings based on Index scores for the base year and the reference year performance have also been presented to provide the overall performance of the States and UTs. A comparison of the change in ranks between the base and reference years has also been undertaken.

2.4.2 Categorization of States for ranking

Based on the availability of data and the fact that similar States should be compared, it was decided to rank the States in three categories, namely Larger States, Smaller States and UTs (Table 2.1).

Scaled value (Si) for positive indicator = (Xi – Minimum value) x 100

(Maximum value – Minimum value)

Scaled value (Si) for negative indicator = (Maximum value – Xi) x 100

(Maximum value – Minimum value)

Composite Index = (∑ Wi*Si )

(∑ Wi)

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4 Experts included Pulak Ghosh, Professor, Indian Institute of Management, Bangalore; Arvind Pandey, Advisor, Indian Council for Medical Research/ National Institute of Medical Statistics (ICMR-NIMS); Laishram Ladusingh, Director, International Institute of Population Studies; Mudit Kapoor, Associate Professor of Economics, the Indian Statistical Institute (ISI).

This categorization was adopted due to the following reasons:

• The SRS data on health outcomes (NMR, U5MR, TFR and SRB) are not available for 8 Smaller States and 7 UTs, and though options were explored by the Office of the Registrar General and Census Commissioner of India (ORGI) to generate these estimates, no reliable option was available.

• Experts consulted4 by NITI Aayog also reported that reliable estimates for these outcome indicators based on raw data obtained from SRS for the Smaller States and UTs could not be derived due to small sample size and insufficient number of events.

2.4.3 The Health Index - List of indicators and weightage

As the Index is a weighted composite Index based on indicators in three domains, each domain has been assigned weights based on its importance. Within a domain or sub–domain, the weight has been equally distributed among the indicators in that domain or sub-domain. Table 2.2 provides a snapshot of the number of indicators in each domain and sub-domain along with weights, while Table 2.3 provides the detailed Health Index with indicators, their definitions, data sources, and specifics of base and reference years.

Category Number of States and UTs States and UTs

Larger States 21 Andhra Pradesh, Assam, Bihar, Chhattisgarh, Gujarat, Haryana, Himachal Pradesh, Jammu & Kashmir, Jharkhand, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Odisha, Punjab, Rajasthan, Tamil Nadu,Telangana, Uttar Pradesh, Uttarakhand, West Bengal

Smaller States 8 Arunachal Pradesh, Goa, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, Tripura

Union Territories 7 Andaman & Nicobar, Chandigarh, Dadra & Nagar Haveli, Daman & Diu, Delhi, Lakshadweep, Puducherry

Table 2.1 - Categorization of States and UTs

Larger States Smaller States Union Territories

Domain Sub-domain Number Number Number of Weight of Weight of Weight Indicators Indicators Indicators

Health Key Outcomes 5 500 1 100 1 100

Outcomes Intermediate Outcomes 6* 300* 6* 300* 5* 250*

Governance Healthand Monitoring and 1 70 1 70 1 70Information Data Integrity

Governance 2 60 2 60 2 60

Key Inputs/ Health Processes Systems/Service 10 200 10 200 10 200

Delivery

TOTAL 24 1130 20 730 19 680

Table 2.2 - Health Index: Summary

* The data for indicator no. 1.2.6 related to out of pocket expenditure was available only for 2015-16 and hence was used to calculate independently the reference year Index and rank (as provided in Annexure 3). This was not included for analyzing improvements between the base and reference years/annual incremental performance as data between the two years needed to be comparable for that purpose.

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S. No. Indicator Definition Data Source Base Year (BY) Remarks & Reference Year (RY)

DOMAIN 1 – HEALTH OUTCOMESSub-domain 1.1 - Key Outcomes (Weight: Larger States – 500, Smaller States & UTs – 100)

1.1.1 Neonatal Mortality Number of infant deaths SRS BY: 2014 Indicators 1.1.1, Rate (NMR) of less than 29 days per thousand live [pre-entered] RY: 2015 1.1.2, 1.1.3, births during a specific year. and 1.1.5 are not applicable for category of Smaller States and UTs

1.1.2 Under-five Mortality Number of child deaths of less than 5 years SRS BY: 2014 Rate (U5MR) per thousand live births during a specific year. [pre-entered] RY: 2015

1.1.3 Total Fertility Average number of children that would be born SRS BY: 2014 Rate (TFR) to a woman if she experiences the current [pre-entered] RY: 2015 fertility pattern throughout her reproductive span (15-49 years), during a specific year.

1.1.4 Proportion of Low Proportion of low birth weight (<=2.5 kg) HMIS BY: 2014-15 Birth Weight (LBW) newborns out of the total number of RY:2015-16 among newborns newborns weighed during a specific year born in a public health facility.

1.1.5 Sex Ratio at Birth The number of girls born for every 1,000 SRS BY: 2012-14 (SRB) boys born during a specific year. [pre-entered] RY: 2013-15

Sub-domain 1.2 - Intermediate Outcomes (Weight: Larger & Smaller States – 300, UTs – 250)

1.2.1 Full immunization Proportion of infants 9-11 months old who HMIS BY: 2014-15 coverage have received BCG, 3 doses of DPT, 3 doses RY: 2015-16 of OPV and one dose of measles against estimated number of infants during a specific year.

1.2.2 Proportion of Proportion of deliveries conducted in public HMIS BY: 2014-15 institutional and private health facilities against the RY: 2015-16 deliveries number of estimated deliveries during a specific year.

1.2.3 Total case Number of new and relapsed TB cases Revised National BY: 2015 notification rate notified (public + private) per 100,000 Tuberculosis Control RY: 2016 of tuberculosis population during a specific year. Programme (RNTCP) (TB) MIS, MoHFW [pre-entered]

1.2.4 Treatment success Proportion of new cured and their treatment RNTCP MIS, MoHFW BY: 2014 rate of new completed against the total number of new [pre-entered] RY: 2015 microbiologically microbiologically confirmed TB cases confirmed TB cases registered during a specific year.

1.2.5 Proportion of people Proportion of PLHIVs receiving ART Central MoHFW Data BY: 2014-15 Indicator not living with HIV treatment against the number of [pre-entered] RY:2015-16 applicable for (PLHIV) on antiretroviral estimated PLHIVs who needed ART category of UTs. therapy (ART) treatment for the specific year.

1.2.6 Average out-of-pocket Average out-of-pocket expenditure per National Family Health RY: 2015-16 Indicator applicable expenditure per delivery delivery in public health facility (in INR). Survey (NFHS)-4 only for reference in public health facility [pre-entered] year ranking. Not (in INR) considered for generating incremental performance scores/ranks or drawing comparison between base and reference years scores/ranks.

Table 2.3 - Health Index: Indicators, definitions, data sources, base and reference years

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DOMAIN 2 – GOVERNANCE AND INFORMATIONSub-domain 2.1 – Health Monitoring and Data Integrity (Weight: 70)

2.1.1 Data Integrity Measure: Percentage deviation of reported data from HMIS and NFHS-4 BY & RY: The NFHS data was standard survey data to assess the quality/ 2015-16 (NFHS) available only for a. Institutional deliveries integrity of reported data for a specific period. reference year and BY & RY: the data for this was b. ANC registered within 2011-12 to repeated for the first trimester 2015-16 base year and (HMIS) reference year.

Sub-domain 2.2 – Governance (Weight – 60)

2.2.1 Average occupancy of Average occupancy of an officer (in months), State Report BY: April 1, an officer (in months), combined for following posts in last three years: 2012-March combined for following 1. Principal Secretary 31, 2015 three posts at State level 2. Mission Director (NHM) for last three years 3. Director (Health Services) RY: April 1, 1. Principal Secretary 2013-March 2. Mission Director (NHM) 31, 2016 3. Director (Health Services)

2.2.2 Average occupancy of Average occupancy of a CMO (in months) for all State Report BY: April 1, a full-time officer (in the districts in last three years. 2012- March months) for all the 31, 2015 districts in last three years - District Chief RY: April 1, Medical Officers (CMOs) 2013-March or equivalent post 31, 2016 (heading District Health Services)

DOMAIN 3 – KEY INPUTS/PROCESSES

Sub-domain 3.1 – Health Systems/Service Delivery (Weight – 200)

3.1.1 Proportion of vacant Vacant healthcare provider positions in public State Report BY: As on healthcare provider health facilities against total sanctioned healthcare March 31, 2015 positions (regular + provider positions for following cadres contractual) in public (separately for each cadre) during a specific year: RY: As on health facilities a. Auxiliary Nurse Mid-wife (ANM) at sub-centers March 31, 2016 (SCs) b. Staff nurse (SN) at Primary Health Centers (PHCs) and Community Health Centers (CHCs) c. Medical officers (MOs) at PHCs d. Specialists at District Hospitals (Medicine, Surgery, Obstetrics and Gynaecology, Pediatrics, Anesthesia, Ophthalmology, Radiology, Pathology, Ear-Nose-Throat (ENT), Dental, Psychiatry)

3.1.2 Proportion of total staff Availability of a functional IT-enabled HRMIS State Report BY: As on (regular + contractual) measured by the proportion of staff (regular + March 31, 2015 for whom an e-payslip contractual) for whom an e-payslip can be can be generated in the generated in the IT-enabled HRMIS against total RY: As on IT-enabled Human number of staff (regular + contractual) during a March 31, 2016 Resources Management specific year. Information System (HRMIS).

3.1.3 a. Proportion of specified Proportion of public sector facilities conducting State Report on BY: 2014-15 Indicator definition type of facilities specified number of C-sections* per year (FRUs) number of functional modified functioning as First against the norm of one FRU per 500,000 FRUs, MoHFW data on RY: 2015-16 Referral Units (FRUs) population during a specific year. required number of (FRUs

b. Proportion of Proportion of PHCs providing all stipulated State Report on number BY: 2014-15 functional 24x7 PHCs healthcare services** round the clock against of functional 24x7 the norm of one 24x7 PHC per 100,000 PHCs, MoHFW data on RY: 2015-16 population during a specific year. required number of PHCs

15

*Criteria for fully operational FRUs: SDHs/CHCs - conducting minimum 60 C-sections per year (36 C-sections per year for Hilly and North-Eastern States except for Assam); DHs - conducting minimum 120 C-sections per year (72 C-sections per year for Hilly and North-Eastern States except Assam). **Criteria for functional 24x7 PHCs: 10 deliveries per month (5 deliveries per month for Hilly and North-Eastern States except Assam)#Centre NHM Finance data includes the RCH �exi-pool and NHM-Health System Strengthening �exi-pool data (representing a substantial portion of the NHM funds) for calculating delay in transfer of funds.

2.5 LIMITATIONS OF THE INDEX

• Some critical areas such as infectious diseases, NCDs, mental health, governance, and financial risk protection could not be fully captured in the Index due to non-availability of acceptable quality of data on an annual basis.

• For several indicators, the data was limited to service delivery in public facilities due to the paucity and uneven availability of private sector data on health services in the HMIS.

• As data was not available for various indicators at the time of Index development, analytical tools could not be used to derive indicator or domain-specific weights and expert opinion was thus used to assign weights. The data generated for this Index will be helpful in refining the Index and assigning weights in the future. This will also be helpful in fixing the minimum and maximum values of the scale for the next several years, instead of a year-to-year basis.

• For SRS related key outcome indicators, data was available only for Larger States. Hence, the Health Index scores and ranks for Smaller States and UTs were calculated excluding these indicators.


3.1.4 Proportion of districts Proportion of districts with functional CCUs [with State Report BY: As on with functional Cardiac desired equipment (ventilator, monitor, March 31, 2015 Care Units (CCUs) defibrillator, CCU beds, portable ECG machine, pulse oxymeter etc.), drugs, diagnostics and RY: As on desired staff as per programme guidelines] March 31, 2016 against total number of districts.

3.1.5 Proportion of ANC Proportion of pregnant women registered for ANC HMIS BY:2014-15 registered within first within 12 weeks of pregnancy during a trimester against total specific year. RY: 2015-16 registrations

3.1.6 Level of registration Proportion of births registered under Civil Civil Registration BY: 2013 of births Registration System (CRS) against the estimated System (CRS) number of births during a specific year. [pre-entered] RY: 2014

3.1.7 Completeness of IDSP Proportion of Reporting Units (RUs) reporting in Central IDSP, BY: 2014 reporting of P and stipulated time period against total RUs, for P MoHFW Data L forms and L forms during a specific year. [pre-entered] RY: 2015

3.1.8 Proportion of CHCs with Proportion of CHCs that are graded above 3 points HMIS BY: 2014-15 grading above 3 points against total number of CHCs during a specific year. RY: 2015-16

3.1.9 Proportion of public Proportion of specified type of public health State Report BY: As on health facilities with facilities with accreditation certificates by a March 31, 2015 accreditation certificates standard quality assurance program against the by a standard quality total number of following specified type of RY: As on assurance program facilities during a specific year. March 31, 2016 (NQAS/NABH/ISO/AHPI) 1. District hospital (DH)/Sub-district hospital (SDH) 2. CHC/Block PHC

3.1.10 Average number of days Average time taken (in number of days) by the Centre NHM Finance BY: 2014-15 for transfer of Central State Treasury to transfer funds to Data#

NHM fund from State implementation agencies during a specific year. [pre-entered] RY: 2015-16 Treasury to implementation agency (Department/Society) based on all tranches of the last financial year

16

• Data for some indicators was available for formerly undivided States. In such instances, the decision was based on data triangulation. For example, data on the SRB was available only for the undivided State of Andhra Pradesh, and the same value was used for the States of Andhra Pradesh and Telangana as this was comparable with other data sources. However, in the case of MMR, it was observed that the estimates for separate States varied widely as compared with formerly undivided States and it was decided to drop the indicator from the Index.

• For several indicators, HMIS data and program data was used without any field verification by the IVA due to the lack of feasibility of conducting independent field surveys.

• Since the integrity of administrative data was to be measured in comparison with reliable independent data, National Family Health Survey (NFHS-4) was used, which overlapped the base and reference year period of the Index. Therefore, the same values of the indicator on data integrity measure were used for base and reference years.

• In some instances, such as the TB case notification rate, the programmatically accepted definition was used, which is based on the denominator per 100,000 population. The more refined indicator of TB cases notified per 100,000 estimated number of TB cases would have been used if data was available.

• In some cases, proxy indicators or proxy validation criteria were used. Thus, for the number of functional First Referral Units (FRUs) and 24x7 Primary Health Centers (PHCs), the annual number of C-sections and deliveries respectively were used as proxy criteria. The field validation of functionality based on available human resources and infrastructure was not viable.

• Due to unavailability of detailed records at the State level for a few indicators, such as vacancies of human resources and districts with functional CCUs, the validation agency had to rely on certified statements provided by the State.

• For a few indicators, such as vacancies of healthcare providers, the proportion of people living with HIV on ART and the average number of days for transfer of funds from the State Treasury; the State level and Central level program data was inconsistent. In such instances the data was reviewed and the most reliable source of data was considered by the IVA.

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3. Processes – from idea to practice3.1 KEY STAKEHOLDERS - ROLES AND RESPONSIBILITIES

Multiple stakeholders were involved in the entire exercise and their roles and responsibilities are summarized in Table 3.1.

5 United States Agency for International Development (USAID), Regional Resource Centre for North Eastern States (RRC-NE), Centre for Innovation in Public Systems (CIPS), The Energy Research Institute (TERI).

NITI Aayog States Technical Mentor Agencies5 Independent Validation Assistance (TA) Agency Agency (The World Bank) (IPE Global)

Development and Adopt and share Health TA to NITI Aayog in Assist States in Validation anddissemination of the Health Index with various developing the Health understanding the Health acceptance of the dataIndex along with necessary departments Index, protocols and Index, data being sought, submitted by the States forguidance in close partnership guidelines and mechanism for various indicators includingwith MoHFW providing the responses comparison with other data sources as needed

Facilitate interaction between Input data on the indicators Support to NITI Aayog to Participate in Regional Review of supportingStates and TA, mentor and as per identified sources disseminate the Health and State-level workshops documents and independent validation on web portal and submit Index in Regional/State-level organized by NITI Aayog participation in data agencies data in a timely manner workshops validation workshops with States

Host a web portal for States Co-ordination with different Technical oversight to the Provide guidance to the Submission of final to input data, its validation districts, mentor and mentor agencies, portal States for submission of validation report with Stateand dissemination of independent validation agency and the independent data by visiting State Health details to NITI AayogState-wise rankings agencies validation agency Departments/Directorates

Overall coordination and Provide technical support Follow up with States for Generation and validation management for generation of composite timely submission of data/ of ranks and final Index and report supporting documents on certification of data on the the web portal portal

Table 3.1 - Key stakeholders: Roles and responsibilities

Table 3.2 - Timeline for development of Health Index

Sr No. Step/Activity 2016 2017-18

Jun-Nov Dec Jan Feb Mar-Apr May Jun Jul Aug Sep-Oct Nov-Jan

1 Development of the Index

2 Regional workshops with States

3 Mentorship to States and submission of data on portal

4 Validation of data and validation workshops with States

5 Refinement of the Index

6 Index and rank generation

7 Report and dissemination of ranks

3.2 PROCESS FLOW

The process of development of the Health Index involved various steps (Table 3.2).

18

3.2.1 Development of Index

The initial idea of a Health Index to benchmark improvements in the States’ performance on key health outcomes originated in March 2016. Development of the Index commenced in June 2016. The selection of indicators and the methodology for the composite Index were among the most challenging tasks. For the selection of indicators, a thorough review of data sources, management information systems and similar global indices was conducted. After detailed deliberations, an initial draft with over 100 indicators was developed and shared with several stakeholders including the States, MoHFW, domestic and international experts, and development partners for review and feedback. A pre-test was conducted in two States to identify state-level issues regarding availability of data, sources for data collection and data validation. Through an iterative process, taking into account importance availability (at least annually) of reliable data, 28 indicators were included in the Health Index (Annexure 2). Once data collection and initial validation was completed, the availability and quality of data for all States was reviewed in a meeting chaired by Member, NITI Aayog. Based on the observations shared by MoHFW, the World Bank, and IVA, as well as inputs from States and experts, 23 indicators were retained and five indicators were dropped for calculating the annual incremental performance and the overall performance in the base and reference years. However, Index scores and ranks for the reference year were also calculated independently, based on 24 indicators including an additional indicator on out-of-pocket expenditure, as the data for this was available only for 2015-16 (Annexure 3).

3.2.2 Regional workshops with States

In order to guide the States on the Health Index and related processes, five regional workshops were held by a team comprising NITI Aayog, MoHFW, the World Bank, mentor agencies, and the portal agency covering all States and UTs (Table 3.3).

3.2.3 Submission of data on the portal

Mentors were assigned to most States to facilitate data collection and submission on the portal. The Empowered Action Group (EAG) States and North-Eastern States were provided dedicated mentor support which other States received on request. The mentor agencies assigned to various States are listed in Table 3.4.

Table 3.3 - Health Index regional workshops

Region Venue Date States/UTs

North New Delhi 23.12.2016 Uttar Pradesh, Haryana, Punjab, Rajasthan, Uttarakhand, Jammu and Kashmir, Himachal

Pradesh, Delhi, Chandigarh

West Goa 13.01.2017 Gujarat, Maharashtra, Madhya Pradesh, Karnataka, Goa, Dadra & Nagar Haveli, Daman & Diu

East New Delhi 27.01.2017 Bihar, Jharkhand, Odisha, Chhattisgarh, Andaman & Nicobar Islands

South Vijayawada 03.02.2017 Andhra Pradesh, Telangana, Kerala, Tamil Nadu, Lakshadweep, Puducherry

North East Shillong 10.02.2017 Meghalaya, Assam, Nagaland, Mizoram, Manipur, Arunachal Pradesh, Sikkim, Tripura,

West Bengal

19

Table 3.4 - List of mentor agencies

Agency States

United States Agency for International Uttar Pradesh, Uttarakhand, Odisha, Chhattisgarh, Punjab, Himachal Pradesh, Bihar,

Development (USAID) Jharkhand, Rajasthan, Madhya Pradesh, Haryana, Chandigarh, West Bengal

Regional Resource Centre for North Eastern Assam, Meghalaya, Arunachal Pradesh, Mizoram, Manipur, Nagaland, Sikkim, Tripura

States (RRC-NE)

Centre for Innovation in Public Systems (CIPS) Andhra Pradesh, Telangana

The Energy Research Institute (TERI) Delhi

The dedicated interactive web portal, developed and hosted by NITI Aayog includes functions for submission of data and its validation and generates and displays state-wise Index scores and ranks. Data was entered in the portal by the States and UTs, except some designated indicators pre-entered on the basis of data source identified at the outset. For State-level data entry, options were provided to the States to either enter data at the State level or assign this to the districts. However, the final submissionof data on the portal was done by the designated State-level competent authority. The process of data entry and submission by the States began in February 2017 and ended in June 2017.

3.2.4 Independent validation of data

An Independent Validation Agency (IVA), namely, IPE Global, was hired by NITI Aayog through a competitive selection process to review and validate the Health Index data and the State rankings. The data submitted on the portal was validated by the IVA from May-October 2017 as summarized in Figure 3.1.

Field visits were conducted to carry physical validation of the data in Assam, Chhattisgarh, Rajasthan, Kerala, Himachal Pradesh, Bihar and Jharkhand6. A regional workshop was also held to cover the seven North-Eastern States. The detailed note on discrepancies in data submitted and their resolution is provided in Annexure 1.

3.2.5 Index and rank generation

The data validated and finalized by the IVA after resolving issues with the States was used in Index generation and rankings. Once the data was accepted by the IVA, the ranks were automatically generated by the portal hosted by the NITI Aayog. In addition, to ensure accuracy the indices and ranks were manually calculated and cross-checked with the results from the portal and the final values were certified by the IVA. The activity of Index and rank generation was undertaken in September and October 2017.

Figure 3.1 - Steps for validating data

FLV - First level veri�cation, SLV - Second level veri�cation

DESK REVIEW(FLV)

Interaction with State Nodal Officers (FLV)

DocumentingGaps and Inconsistencies

Field Visits to States & Districts (SLV)

• Review of data for completeness, accuracy, consistancy.

Comparison with published sources like NFHS, SRS etc. as specified

• Discrepancies found during the desk review validated with State Nodal officers

• In case the nodal officer is unable to address the discrepancies, sample field visits undertaken

• Sample states and districts visited to validate results/figures provided by the state for specific indicators

6 Physical verification of the documents and meetings with State Nodal Officers were conducted by project offices of the IVA.

20

Results And Findings

Performance of Larger StatesPerformance of Smaller States

Performance of Union TerritoriesStates and UTs: Performance on indicators

21

4. Unveiling performance – encouraging actions This chapter presents the States’ overall and incremental performance on the Health Index. The results

are presented for each group of States separately: Larger States, Smaller States, and UTs. Overall performance is measured using the composite Index scores for base and reference years, and incremental performance is calculated as the change in composite Index scores from base to reference year.

4.1 PERFORMANCE OF LARGER STATES

4.1.1 Overall performance

In the base year (2014-15), the composite Health Index ranged from 28.14 in Uttar Pradesh to 80 in Kerala. On an average, modest improvement was observed between the base and reference year, with the difference between the worst and best performing States narrowing. In the reference year 2015-16, Uttar Pradesh at 33.69 remained the poorest performing State, and Kerala remained the best performing State despite a slight decline in the Health Index to 76.55.

Figure 4.1 displays the composite Index scores for base and reference years for the Larger States and ranks the States based on their overall performance. The lines depict changes in the ranking: a blue line denotes a negative change in the State’s ranking from base to reference year, a green line indicates a positive change, and a grey line indicates no change in ranking.

The top five performing States in the reference year based on the composite Index score are Kerala (76.55), Punjab (65.21), Tamil Nadu (63.38), Gujarat (61.99), and Himachal Pradesh (61.20). On the other end of the spectrum, Uttar Pradesh (33.69) scored the lowest and ranks at the bottom preceded by Rajasthan (36.79), Bihar (38.46), Odisha (39.43), and Madhya Pradesh (40.09). The EAG7 States (except Chhattisgarh) and Assam lie at the tail end of the distribution, ranking between 14th and 21st positions.

Among the 21 Larger States, only five States improved their position from base to reference year. These States are Punjab, Andhra Pradesh, Jammu & Kashmir, Chhattisgarh and Jharkhand. The most significant progress was observed in Jharkhand and Jammu & Kashmir. Both States moved up by four positions in the ranking. Meanwhile, Punjab improved its performance in the ranking by three positions. Andhra Pradesh and Chhattisgarh have shown modest improvement – both up by one position. Despite increases in the composite Health Index scores, the rankings of Maharashtra, Madhya Pradesh, Bihar, Rajasthan, and Uttar Pradesh did not change between base and reference years. Kerala continued to be at the top position and the remaining States fell in ranking by 1-2 positions.

7 Eight states namely Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Odisha, Rajasthan, Uttar Pradesh and Uttarakhand, and are referred to as the Empowered Action Group (EAG) States.

22

Note: The States are categorized on the basis of reference year Index score range: Front-runners: top one-third (Index score>62), Achievers: middle one-third (Index score between 48 and 62), Aspirants: lowest one-third (Index score<48).

Note: Lines depict changes in composite Index score rank from base to reference year. The composite Index score is presented in the circle.

Figure 4.1 - Larger States: Overall performance - Composite Index score and rank, base and reference years

Based on the composite Index scores for the reference year (2015-16), the States are grouped into three categories: Aspirants, Achievers, and Front-runners (Table 4.1). Aspirants are the bottom one-third states with an Index score below 48. These States are largely the EAG States (except Chhattisgarh) and given the substantial scope for improvement, require concerted efforts. Achievers represent the middle one-third States with an Index score between 48 and 62. Overall, these States have made good progress and can move to the next group with sustained efforts. Front-runners, the top one-third States with an Index score above 62 are the best performing States. Despite relatively good performance, however, even the Front-runners could further benefit from improvements in certain indicators as the highest observed Index score of 76.55 is well below 100.

Reference Year 2015-16

Base Year 2014-15

Kerala 80.00

Tamil Nadu 63.28

Gujarat 63.28

Himachal Pradesh 62.12

Punjab 62.02

Maharashtra 60.09

Karnataka 59.73

West Bengal 57.87

Andhra Pradesh 57.75

Telangana 54.94

Jammu & Kashmir 53.52

Haryana 49.87

Chhattisgarh 48.63

Uttarakhand 45.32

Assam 43.53

Odisha 39.23

Madhya Pradesh 38.99

Jharkhand 38.46

Bihar 34.70

Rajasthan 34.55

Uttar Pradesh 28.14

76.55 Kerala

65.21 Punjab

63.38 Tamil Nadu

61.99 Gujarat

61.20 Himachal Pradesh

61.07 Maharashtra

60.35 Jammu & Kashmir

60.16 Andhra Pradesh

58.70 Karnataka

58.25 West Bengal

55.39 Telangana

52.02 Chhattisgarh

46.97 Haryana

45.33 Jharkhand

45.22 Uttarakhand

44.13 Assam

40.09 Madhya Pradesh

39.43 Odisha

38.46 Bihar

36.79 Rajasthan

33.69 Uttar Pradesh

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Table 4.1 - Larger States: Overall performance in reference year - Categorization


Haryana Gujarat Kerala Jharkhand Himachal Pradesh Punjab Uttarakhand Maharashtra Tamil Nadu Assam Jammu & Kashmir Madhya Pradesh Andhra Pradesh Odisha Karnataka Bihar West Bengal Rajasthan Telangana Uttar Pradesh Chhattisgarh

23

Figure 4.2 - Larger States: Overall and incremental performance, base and reference years and incremental rank

4.1.2 Incremental performance

Incremental performance measures the change in the Health Index score from base to reference year, which is masked by the year-specific rankings. It is important to identify the year-on-year pace of improvement made by States. States that start at lower levels of Health Index are generally at an advantage for higher incremental progress due to diminishing marginal returns for States that start at a high Index score. This measure is particularly important for identifying States with negative incremental progress.

In Figure 4.2, the left side, presents the State-wise movement in Health Index from base to reference year along with their relative position and on the right side, actual increments are presented. Overall, the incremental performance does not appear to be associated with the overall Index score. Importantly, some of the better-performing Larger States have made negative incremental progress. Three of the top five Larger States (Kerala, Gujarat, and Himachal Pradesh) recorded negative changes in the overall performance Index score between base and reference years.

Among the 21 Larger States, 15 States displayed a positive incremental change in the Index score. The remaining six States showed negative incremental change. Except for Uttarakhand that showed a slight negative incremental performance, the EAG States registered positive incremental progress. Jharkhand (ranked at top) followed by Jammu & Kashmir and Uttar Pradesh made significant incremental progress, with more than a five-point change in Index score from base to reference year. However, for Bihar, Chhattisgarh, Punjab, Andhra Pradesh and Rajasthan, the Index score increased by 2 to 4 points. Further, limited improvement was observed in Madhya Pradesh, Maharashtra, Assam, Telangana and West Bengal. Odisha, Tamil Nadu and Uttarakhand more or less maintained their respective Health

6.87Jharkhand

Jammu & Kashmir

Uttar Pradesh

Bihar

Chhattisgarh

Punjab

Andhra Pradesh

Rajasthan

Madhya Pradesh

Maharashtra

Assam

Telangana

West Bengal

Odisha

Tamil Nadu

Uttarakhand

Himachal Pradesh

Karnataka

Gujarat

Haryana

Kerala

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

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38.46 45.33

6.83

5.55

3.76

3.39

3.19

2.41

2.24

1.10

0.98

0.60

0.45

0.38

0.20

0.10

-0.10

-0.92

-1.03

-1.29

-2.90

-3.45

34.70

48.63 52.02

62.02 65.21

57.75 60.16

34.55 36.79

38.99 40.09

60.09 61.07

43.53 44.13

54.94 55.39

57.87 58.25

39.23 39.43

63.28 63.38

45.22 45.32

61.20 62.12

58.70 59.73

61.99 63.28

46.97

20 30 40 50 60 70 80


Rank

-4 0 4 8

49.87

76.5580.00

38.46

53.52 60.35

28.14 33.69


24

Table 4.2 - Larger States: Incremental performance from base to reference year - Categorization

Among the most improved States in terms of incremental progress, Jharkhand is the top most improved State and has showed maximum gains in improvement of health outcomes from base to reference year in indicators such as U5MR (44 to 39 per 1000 live births), TFR (2.8 to 2.7), full immunization (81 to 88 percent) and institutional deliveries (61 to 67 percent). Jammu & Kashmir, ranked at second, has shown good incremental progress on health outcomes of NMR (26 to 20 per 1000 live births), U5MR (35 to 28 per 1000 live births), full immunization coverage (90 to 100 percent) and PLHIV on ART (89 to 96 percent). Similarly, Uttar Pradesh, ranked third has attained significant incremental improvement on the parameters of U5MR (57 to 51 per 1000 live births), low birth weight (11.74 to 9.60 percent), institutional deliveries (44 to 52 percent), and PLHIV on ART (51 to 58 percent).

Among the States which could not register positive incremental performance, Kerala is ranked at the bottom mainly as it had already achieved low level of NMR and U5MR and replacement level fertility, leaving very limited space for any further improvements. Additionally, Kerala also registered a decline in sex ratio at birth from base to reference year (974 to 967 females per 1000 males). Haryana with a negative incremental score performed poorly due to increase in U5MR (40 to 43 per 1000 live births) and decline in the Sex Ratio at Birth (866 to 831 females per 1000 males) from base to reference year. Gujarat registered a significant decline in sex ratio at birth (907 to 854 females per 1000 males) that dragged down its incremental progress.

The indicators where most Larger States need to focus on include addressing the issue of sex ratio at birth, establishment of functional district Cardiac Care Units, ensuring quality accreditation of public health facilities, and institutionalization of Human Resources Management Information System.

Not improved Least improved Moderately improved Most improved

Uttarakhand Madhya Pradesh Bihar Jharkhand Himachal Pradesh Maharashtra Chhattisgarh Jammu & Kashmir Karnataka Assam Punjab Uttar Pradesh Gujarat Telangana Andhra Pradesh Haryana West Bengal Rajasthan Kerala Odisha Tamil Nadu

Note: The States are categorized on the basis of incremental Index score range into categories: ‘not improved’ (incremental Index score<=0), ‘least improved’ (incremental Index score between 0.01 and 2), ‘moderately improved’ (incremental Index score between 2.01 and 4), ‘most improved’ (incremental Index score>4.0).

Index scores and made negligible incremental progress. Meanwhile, Himachal Pradesh, Karnataka, Gujarat, Haryana and Kerala showed declines in the reference year as compared to the base year, resulting in a negative incremental Index score.

Fifteen states observed positive incremental change in Index scores from base to reference year, whereas only five States (Punjab, Andhra Pradesh, Jammu & Kashmir, Chhattisgarh, and Jharkhand) increased in their overall performance ranks from base year to reference year. This depicts that only these five States made significant incremental progress leading to improvement in the overall performance position. The remaining States with modest or negative incremental progress have retained their earlier position or have moved down in the ranking.

Based on their incremental performance, States are categorized into four groups: ‘not improved’ (<= 0 incremental change), ‘least improved’ (0.01 to 2 point increase), ‘moderately improved’ (2.01 to 4 point increase), and ‘most improved’ (>4 point increase) (Table 4.2).

25

Figure 4.3 - Larger States: Overall and domain-specific performance, reference year

Figure 4.4 and Figure 4.5 present the overall performance of Larger States in the domains of Health Outcomes and Key Inputs/Processes for base and reference year. In these figures, from top to bottom, States are presented in descending order of Health Index scores for the reference year. For the Health Outcomes domain, Kerala is ranked at the top and Rajasthan is at the bottom, while for Key Inputs/Processes, Tamil Nadu earned the top position and Uttar Pradesh received the lowest ranking.

Kera

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Health Outcomes Key Inputs/Processes Overall Performance

4.1.3 Domain-specific performance

Overall performance is an aggregate measure of a State’s performance and does not reveal specific areas requiring further attention. To identify such areas, the Index is disaggregated into the domains of Health Outcomes, Governance and Information, and Key Inputs/Processes. The domain of Governance and Information is not presented in this section as it has a limited number of indicators (three) due to data limitations and thus might not be fully representative of the domain.

The overall performance of the States is not always consistent with the domain-specific performance (Figure 4.3). Some top performing States fare significantly better in one domain suggesting that there is scope to improve their performance in the lagging domain with specific targeted interventions. Most States showed a better performance on health outcomes; however, Tamil Nadu, West Bengal, Assam, Madhya Pradesh, Odisha and Rajasthan performed better in terms of Key Inputs/Processes.

26

Figure 4.4 - Larger States: Performance in the Health Outcomes domain, base and reference years

Note: States ranked based on their reference year score in the Health Outcomes domain.

Kerala

Punjab

Jammu & Kashmir

Himachal Pradesh

Telangana

Andhra Pradesh

Tamil Nadu

Karnataka

Maharashtra

Gujarat

West Bengal

Chhattisgarh

Jharkhand

Haryana

Uttarakhand

Assam

Bihar

Madhya Pradesh

Odisha

Uttar Pradesh

Rajasthan

82.33 82.89 0.56

5.33

10.05

3.27

2.12

-1.88

-1.48

-0.48

-1.19

-0.52

-2.71

1.23

6.89

-2.08

-2.35

0.73

4.82

7.13

1.08

-0.43

-0.79

56.49 66.54

65.89 67.77

61.53 64.8060.45 62.57

62.56 64.04

62.30 62.78

61.41 62.60

56.43 59.14

52.67 53.9044.93 51.82

46.05 48.13

45.56 47.91

42.02 42.75

34.01 38.83

35.92 37.0033.86 34.29

26.09 33.22

29.58

Health Outcomes Index Score Incremental Change

BaseYear (2014-15)Reference Year (2015-16)

30.37

59.78 60.30

64.54 69.87

20 30 40 50 60 70 80 90 -4 -2 0 2 4 6 8 10 12

In the domain of Health Outcomes, 11 States (Kerala, Punjab, Jammu & Kashmir, Telangana, Andhra Pradesh, Chhattisgarh, Jharkhand, Assam, Bihar, Madhya Pradesh, and Uttar Pradesh) have improved their Index score from base to reference year. The Index score has declined from base to reference year for the other States. Jammu & Kashmir saw the largest positive incremental change (10.05) followed by Uttar Pradesh (7.13) and Jharkhand (6.89), while negative changes of more than 2 points were observed in West Bengal, Haryana, and Uttarakhand.

27

In the Key Inputs/Processes domain, the Index score has improved from base to reference year in 15 of the 21 States. The Key Inputs/Processes score declined in Kerala, Karnataka, Punjab, Haryana, Telangana and Uttar Pradesh. Large incremental increases of more than 10 points were observed in Rajasthan, Chhattisgarh, Jammu & Kashmir, Bihar, and Jharkhand. Negative incremental change of more than 2 points was observed in Kerala, Haryana, Telangana and UP.

Figure 4.5 - Larger States: Performance in the Key Inputs/Processes domain, base and reference years

Note: States ranked based on their reference year score in the Key Inputs/Processes domain.

-10 -5 0 5 10 15 20

3.86

9.21

8.66

-4.55

-0.73

0.52

0.40

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-0.23

-2.45

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14.48

10.24

1.648.42

12.34

14.11

-7.34

-4.26

17.21

74.20 78.0674.17

61.99

58.6950.0357.3056.78

56.6955.96

55.1654.76

53.1747.5751.9052.13

49.8032.59

49.8043.20

48.8646.4145.2345.02

44.2929.81

42.6132.37

41.3039.6640.4932.07

32.5420.20

39.2631.9229.4115.3029.2825.02

52.78

69.62

10 20 30 40 50 60 70 80

Tamil Nadu

Kerala

West Bengal

Andhra Pradesh

Gujarat

Karnataka

Odisha

Maharashtra

Punjab

Rajasthan

Himachal Pradesh

Haryana

Assam

Chhattisgarh

Jammu & Kashmir

Madhya Pradesh

Uttarakhand

Bihar

Telangana

Jharkhand

Uttar Pradesh

Key Inputs/Processes Index Score Incremental Change

Base Year (2014-15)Reference Year (2015-16)

4.1.4 Incremental performance on indicators

Figure 4.6 captures the incremental performance on indicators and sub-indicators and provides the number of indicators and sub-indicators in each category, i.e, ‘most improved’, ‘improved’, ‘no change’,‘deteriorated’ and ‘most detriorated’. Chattisgarh has the highest proportion of indicators among Larger States (70 percent), which fall in the category of ‘most improved’ and ‘improved’. On the other hand, Haryana has the highest proportion (43 percent) of indicators which fall in the category of ‘deteriorated’ and ‘most deteriorated’. Detailed indicator-specific performance snapshot of States is presented in Annexure 4, which provides the direction as well as the magnitude of the incremental change of indicators from base year to reference year.

28

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Maharashtra

Himachal Pradesh

Odisha

Tamil Nadu

Madhya Pradesh

Punjab

Uttarakhand

Telangana

Kerala

Haryana

Number of Indicators/Sub-indicators

Stat

es

Most Improved Improved No Change Deteriorated Most Deteriorated Not Applicable

Figure 4.6 - Larger States: Number of indicators/sub-indicators, by category of incremental performance

Note: For a State, the incremental performance on an indicator is classified as not applicable (NA) in instances such as: (i) If State has achieved TFR <= 2.1 in both base and reference years; (ii) Data Integrity Measure indicator wherein the same data has been used for base year and reference year due to overlapping periods of NFHS-4; (iii) Service coverage indicators with 100 percent values in both base and reference years; (iv) The data value for a particular indicator is NA in base year or reference year or both.

29

4.2 PERFORMANCE OF SMALLER STATES


In the base year (2014-15), the overall performance among the Smaller States ranged from 45.26 in Nagaland to 71.27 in Mizoram (Figure 4.7). Both states retained their respective rankings in the reference year. Mizoram exhibited a small improvement since base year, with the Health Index score rising to 73.70 in the reference year (2015-16). Meanwhile, Nagaland’s performance worsened substantially - the State’s Health Index fell from 45.26 in the base year to 37.38 in the reference year. Tripura received a score of 43.51 and is the second-to-last State among this group. Notably, while Manipur, Meghalaya, Sikkim, Goa and Arunachal Pradesh are among the better performing Smaller States, these States scored only between 50 and 58 points on the Health Index in the reference year. This suggests that there is substantial scope for improvement even for these relatively better-performing states.

Only two States, namely Manipur and Goa, improved their position from base year to reference year - each up by two positions. Mizoram, Meghalaya, and Nagaland retained their first, third, and eighth positions, respectively. The position of Sikkim worsened by two ranks (from second to fourth) and that of Arunachal Pradesh and Tripura worsened by one position from fifth to sixth and sixth to seventh, respectively.

Based on the composite Index score range for reference year (2015-16), Tripura and Nagaland (Table 4.3) are categorized as Aspirants, and have substantial scope for improvements, while Manipur, Meghalaya, Sikkim, Goa and Arunachal Pradesh are Achievers, and though have demonstrated better performance, still need to improve. Mizoram is categorized as a Front-runner - with the highest observed performance among the Smaller States. Despite relatively good performance, even Mizoram could further benefit from improvements.


Figure 4.7 - Smaller States: Overall performance - Composite Index score and rank, base and reference years

Mizoram 71.27

Sikkim 53.39

Meghalaya 51.40

Manipur 50.60

Arunachal Pradesh 50.60

Tripura 48.35

Goa 46.46

Nagaland 45.26

73.70 Mizoram

57.78 Manipur

56.83 Meghalaya

53.20 Sikkim

53.13 Goa

49.51 Arunachal Pradesh

43.51 Tripura

37.38 Nagaland

1

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30

From base to reference year, four States (Manipur, Goa, Meghalaya and Mizoram) showed positive incremental progress, while the remaining four States (Sikkim, Arunachal Pradesh, Tripura and Nagaland) registered negative incremental performance (Figure 4.8). The States of Manipur (ranked at the top), Goa and Meghalaya made significant incremental progress – recording increases in the Health Index score of 5 points or more between the base and reference years. Mizoram also made some incremental progress with a 2.43 point change in Index scores from base to reference year. Sikkim has observed almost no change in its Health Index score between the two periods. The Index score in Arunachal Pradesh and Tripura declined by 1.09 and 4.84 points, respectively. Nagaland observed the highest negative incremental change of -7.88 points between base and reference years.

Mizoram has shown incremental progress from base to reference year and has retained the top rank. Although, three States (Manipur, Goa, and Meghalaya) have observed positive incremental change in Index scores from base to reference year, only Manipur and Goa have been able to improve their overall performance ranks from base year to reference year. The remaining States with modest or negative incremental progress retained their base year position or have moved down in the ranking.

Based on their incremental performance from base to reference year, States are grouped into four categories: ‘not improved’, ‘least improved’, ‘moderately improved’, and ‘most improved’ (Table 4.4). Manipur, Goa, and Meghalaya are among the most improved states with an incremental Index score of more than 4 points. Meanwhile, Sikkim, Arunachal Pradesh, Tripura, and Nagaland have not improved and have in fact seen their overall Index scores decline between base and reference years.


Figure 4.8 presents the incremental progress made by the States along with their relative position to each other as well as the respective increments and ranks.

Table 4.3 - Smaller States: Overall performance in reference year - Categorization


Tripura Manipur Mizoram Nagaland Meghalaya Sikkim Goa Arunachal Pradesh

Note: The States are categorized on the basis of reference year Index score range: Front-runners: top one-third (Index score>61.60), Achievers: mid one-third (Index score between 49.49 and 61.60), Aspirants: lowest one-third (Index score<49.49).

Figure 4.8 - Smaller States: Overall and incremental performance, base and reference years and incremental rank

Manipur

Goa

Meghalaya

Mizoram

Sikkim

Arunachal Pradesh

Tripura

Nagaland

57.7850.60

46.46 53.13

56.83

73.7071.27

51.40

53.20 53.39

49.51 50.60

43.51 48.35

37.38 45.26

-1030 40 50 60 70 80 5 0 5 10


Rank


7.18

6.67

5.43

2.43

-0.19

-1.09

-4.84

-7.88

1

2

3

4

5

6

7

8

31

Among the most improved States, Manipur registered maximum incremental progress from base to reference year due to good progress on indicators such as PLHIVs on ART (54 to 64 percent), average occupancy of 3 key state level officers (13 to 21 months), first trimester ANC registration (59 to 63 percent), IDSP reporting format for presumptive surveillance (P form) submission (35 to 63 percent), and CHC grading (0 to 29 percent). Further, Goa, ranked second and progress from base to reference year was notable on indicators such as low birth weight (17 to 16 percent), full immunization coverage (91 to 95 percent), average occupancy of three key State-level officers (15 to 22 months), CHC grading (25 to 75 percent), vacancy of medical officers at PHCs (31 to 14 percent) and specialists at district hospitals (43 to 40 percent).

Among the States which have not shown any improvement from base year to reference year, Nagaland, ranked at the bottom, and performed poorly on indicators such as TB treatment success rate (91 to 72 percent), average occupancy of three key State-level officers (12 to 7 months), first trimester ANC registration (47 to 36 percent) and time taken to transfer Central NHM funds from State Treasury to implementation agency (101 to 213 days). Tripura, ranked second from the bottom, and fared poorly on indicators such as full immunization coverage (87 to 84 percent), TB case notification rate (195 to 61), PLHIVs on ART (23 to 6 percent), vacancies of Auxiliary Nurse Midwives (ANMs) at sub-centres (15 to 39 percent), and level of birth registration (91 to 82 percent).

The indicators where almost all Smaller States need to focus include filling vacancies of ANMs at sub-centres, establishment of functional district Cardiac Care Units, quality accreditation of public health facilities, and institutionalization of Human Resources Management Information System.


The overall performance of the States is not always consistent with the domain-specific performance (Figure 4.9). All Smaller States showed a better performance on Health Outcomes as compared to Key Inputs/Processes.

Table 4.4 - Smaller States: Incremental performance from base to reference year - Categorization


Sikkim Mizoram Manipur Arunachal Pradesh - Goa Tripura Meghalaya Nagaland

Note: The States are categorized on the basis of incremental Index score range into categories: ‘not improved’ (incremental Index score<=0), ‘least improved’ (incremental Index score between 0.01 and 2), ‘moderately improved’ (incremental Index score between 2.01 and 4), ‘most improved’ (incremental Index score>4).

32

In the domain of Health Outcomes, five States (Mizoram, Manipur, Meghalaya, Goa and Sikkim) improved their performance from base year to reference year and the performance of the remaining three States (Arunachal Pradesh, Nagaland and Tripura) has worsened (Figure 4.10). Mizoram achieved the highest score of 92.97 in the Health Outcomes domain. However, the range of scores was wide. Manipur received a second highest score of 66.07, while the poorest performing State of Tripura scored only 39.56 points.

Figure 4.9 - Smaller States: Overall and domain-specific performance, reference year

Figure 4.10 - Smaller States: Performance in the Health Outcomes domain, base and reference years


Refe

renc

e Ye

ar (2

015-

16) S

core

100

90

80

70

60

50

40

30

20

10

0Mizoram


Manipur Meghalaya Sikkim Goa ArunachalPradesh

Tripura Nagaland

Mizoram

Manipur

Meghalaya

Goa

Sikkim

Arunachal Pradesh

Nagaland

Tripura

88.77 92.97

60.71 66.07

60.63 63.40

45.62 52.79

48.97 50.17

45.98 46.02

44.80 60.55

39.56

20 40 60 80 100 -20 -10 10 200

54.85

Health Outcomes Index Score


Incremental Change

4.20

5.36

2.77

7.17

1.20

-0.04

-15.75

-15.29

33


Figure 4.12 captures the incremental performance on indicators and sub-indicators and provides the number of indicators and sub-indicators in each category, i.e, ‘most improved’, ‘improved’, ‘no change’, ‘deteriorated’and ‘most detriorated’. Among the Smaller States, even though Goa has the highest number of indicators that have shown improvement, there are still nearly 30 percent of indicators that have either remained stagnant or deteriorated. Apart from Goa, other Smaller States did not record any improvements even in 40 percent of the indicators. Detailed indicator-specific performance snapshot of States is presented in the Annexure 4, which provides the direction as well as the magnitude of the incremental change of indicators from base year to reference year.

In the Key Inputs/Processes domain, all Smaller States performed quite poorly and the range of scores was significantly smaller. Goa received the highest score of only 44.65, while Manipur scored 32.18 points. Four States (Goa, Meghalaya, Tripura and Manipur) improved their performance; whereas the performance of the remaining four States of Mizoram, Sikkim, Arunachal Pradesh and Nagaland worsened (Figure 4.11).


Figure 4.11 - Smaller States: Performance in the Key Inputs/Processes domain, base and reference years

Goa

Mizoram

Sikkim

Arunachal Pradesh

Nagaland

Meghalaya

Tripura

Manipur

42.50 44.65


2.15

11.29

2.42

-4.44

-0.97

-2.24

-10.9244.64

41.31

41.03

40.19

27.09 38.38

36.3833.96

28.86 32.18

44.63

42.00

43.55

55.56

3.32

20 40 50 60 -15 -10 -5 0 5 10 1530

Base Year (2014-15)

Reference Year (2015-16)

34

Figure 4.12 - Smaller States: Number of indicators/sub-indicators, by category of incremental performance

Note: For a State, the incremental performance on an indicator is classi�ed as not applicable (NA) in instances such as: (i) Data Integrity Measure indicator wherein the same data has been used for base and reference years due to overlapping periods of NFHS-4; (ii) Service coverage indicators with 100 percent values in both base year and reference year; (iii) The data value for a particular indicator is NA in the base year or reference year or both.

6

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Meghalaya

Manipur

Sikkim

Tripura

Arunachal Pradesh

Nagaland

Mizoram


Stat

es


35

Some improvements were observed in the reference year, but the best and worst scores still differed by more than 30 points. Despite a modest improvement, Dadra & Nagar Haveli received the lowest score of 34.64 points, while Lakshadweep moved to first place with a score of 65.79 points (Figure 4.13).

Only two UTs, namely Lakshadweep and Andaman & Nicobar Islands, improved their position from base year to reference year - Lakshadweep from second to first and Andaman & Nicobar Islands from fifth to fourth position. Delhi has retained its third position during the period. Similarly, Daman & Diu and Dadra & Nagar Haveli did not change ranks and were ranked sixth and seventh, respectively. Puducherry and Chandigarh both fell by one position in the rankings (Puducherry from fourth to fifth, and Chandigarh from first to second).

Based on the composite Index score range for reference year (2015-16), the UTs are categorized into three categories: Aspirants, Achievers, and Front-runners. Daman & Diu and Dadra & Nagar Haveli are categorized as Aspirants, and are among the bottom one-third UTs, and have substantial scope for improvement. Chandigarh, Delhi, Andaman & Nicobar Islands and Puducherry are grouped as Achievers and also have significant room for improvement. Lakshadweep with the highest overall performance is categorized as Front-runner, and could also benefit from improvements with an Index score of 65.79, which is well below 100.

4.3. PERFORMANCE OF UNION TERRITORIES


The overall performance based on the Health Index score of UTs for the base year ranged from 31.34 points for Dadra & Nagar Haveli to 57.49 points for Chandigarh.

Figure 4.13 - Union Territories: Overall performance - Composite Index score and rank, base and reference years


Reference Year 2015-16

Base Year 2014-15

65.79 Lakshadweep

52.27 Chandigarh

50.02 Delhi

50.00 Andaman & Nicobar Islands

47.48 Puducherry

36.10 Daman & Diu

34.64 Dadra & Nagar Haveli

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Chandigarh 57.49

Lakshadweep 56.23

Delhi 48.05

Puducherry 46.54

Andaman & Nicobar Islands 46.18

Daman & Diu 44.77

Dadra & Nagar Haveli 31.34

36


Figure 4.14 shows that from base to reference year, five UTs (Lakshadweep, Andaman & Nicobar, Dadra & Nagar Haveli, Delhi and Puducherry) registered positive incremental progress and the remaining two UTs (Chandigarh and Daman & Diu) registered negative incremental change. From base year to reference year, Lakshadweep (ranked at the top) observed the highest incremental performance of 9.56 points. Andaman & Nicobar, Dadra & Nagar Haveli and Delhi saw an increase in the Health Index score of between 2 to 4 points from base year to reference year. Puducherry achieved approximately a one point incremental increase. Daman & Diu and Chandigarh reported negative changes in the Health Index score, with the Health Index score declining by 8.67 and 5.22 points, respectively, over the time period.

Furthermore, five UTs (Lakshadweep, Andaman & Nicobar, Dadra & Nagar Haveli, Delhi and Puducherry) observed positive incremental performance in the Index scores from base to reference year, but only two UTs (Lakshadweep and Andaman & Nicobar) could move up in the overall performance ranks from base year to reference year. This suggests that only these two UTs made significant incremental progress leading to improvement in its overall performance position. The remaining UTs with modest or negative incremental progress retained their earlier position or have moved down in the rankings.

Table 4.5 - Union Territories: Overall performance in reference year - Categorization


Daman & Diu Chandigarh Lakshadweep

Dadra & Nagar Haveli Delhi

Andaman & Nicobar Islands

Puducherry

Figure 4.14 - Union Territories: Overall and incremental performance, base and reference years and incremental rank

Note: The UTs are categorized on the basis of reference year Index score range: Front-runners: top one-third (Index score>55), Achievers: mid one-third (Index score between 45 and 55), Aspirants: lowest one-third (Index score<45).

Lakshadweep 56.23

46.18 50.00

34.6431.34

48.05 50.02

47.4846.54

52.27 57.49

44.7736.10

30 -10 -5 0 5 1040 6050 70

65.79 9.56 1

2

3

4

5

6

7

3.82

3.30

1.97

0.94

-5.22

-8.67



Delhi

Puducherry

Chandigarh

Daman & Diu

Overall Performance Index Score Incremental ChangeIncrementalRank


37

Lakshadweep is the most improved UT and ranked at the top with good incremental progress registered from base to reference years for indicators such as institutional deliveries (76 to 85 percent), TB treatment success rate (87 to 91 percent) and transfer of Central NHM funds from State Treasury to implementation agency (143 to 0 days). Among the UTs which did not register any incremental progress between the base and reference years, Daman & Diu fared poorly on indicators such as low birth weight (17 to 24 percent), full immunization (85 to 80 percent), institutional deliveries (75 to 72 percent), vacancy of specialists at district hospitals (38 to 47 percent), level of registration of births (98 to 76 percent), IDSP reporting format for presumptive surveillance (P-form) submission (100 to 75 percent) and IDSP reporting format for laboratory surveillance (L-form) submission (86 to 75 percent). Similarly, Chandigarh performed very poorly on first trimester ANC registration that fell from 50 percent in the base year to 37 percent in the reference year.

The indicators where almost all UTs need to focus include filling vacancies of medical officers at PHCs and specialists at district hospitals, establishment of functional First Referral Units, 24X7 PHCs, and district Cardiac Care Units, CHC grading, quality accreditation of public health facilities, and institutionalization of Human Resources Management Information System.


The overall performance of the UTs differs with the domain-specific performance and suggests some opportunities to improve the performance in the lagging domain(s) (Figure 4.15). While most UTs showed a better performance on most Health Outcomes, Daman & Diu and Dadra & Nagar Haveli performed better in terms of Key Inputs/Processes.

Note: The UTs are categorized on the basis of incremental Index score range into categories: ‘not improved’ (incremental Index score<=0), ‘least improved’ (incremental Index score between 0.01 and 2), ‘moderately improved’ (incremental Index score between 2.01 and 4), ‘most improved’ (incremental Index score>4).

The categorization of States based on incremental performance is shown in Table 4.6.

Table 4.6 - Union Territories: Incremental performance from base to reference year - Categorization


Chandigarh Delhi Andaman and Nicobar Islands Lakshadweep

Daman and Diu Puducherry Dadra and Nagar Haveli

38

In the domain of Health Outcomes, all UTs except Chandigarh and Daman & Diu have improved their performance from base year to reference year (Figure 4.16). For the Health Outcomes domain in the reference year, the range of Index scores is very wide and Lakshadweep scored highest with 74.37 points compared to Daman & Diu’s lowest score of 15.89.

In the case of the Key Inputs/Processes domain, three UTs (Delhi, Dadra & Nagar Haveli and Lakshadweep) improved their performance; whereas the performance of the remaining four UTs (Puducherry, Chandigarh, Daman & Diu and Andaman & Nicobar) has fallen. The range is smaller for the Key Inputs/Processes domain. In this domain, Puducherry scored highest with 52.99 points, while Andaman & Nicobar scored the lowest with 26.75 points. Overall, the range of scores is quite low and indicates that all UTs need to focus on this domain.

Figure 4.15 - Union Territories: Overall and domain-specific performance, reference year

Refe

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015-

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core


80

70

60

50

40

30

20

10

0

Lakshadweep Chandigarh Delhi Andaman &NicobarIslands

Puducherry Daman & Diu Dadra & NagarHaveli

Figure 4.16 - Union Territories: Performance in the Health Outcomes domain, base and reference years

Lakshadweep

Chandigarh


Delhi

Puducherry


Daman & Diu

60.15 74.37

73.1463.58

60.85

56.8353.82

40.24

53.5850.90

19.82 23.64

15.89 32.10

10 20 30 40 50 60 70 80 -20 -10 0 10 20

Health Outcomes Index Score Incremental Change


14.22

20.61

3.01

2.68

3.82

-9.56

-16.21

Note: For Chandigarh and Daman and Diu, the Key Input/Processes domain score is the same as the overall performance score.


39


Figure 4.18 captures the incremental performance on indicators and sub-indicators and provides the number of indicators and sub-indicators in each category, i.e, ‘most improved’, ‘improved’, ‘no change’, ‘deteriorated’ and ‘most deteriorated’. Though Delhi had the highest number of indicators where performance has improved between the reference and base years, it has half the indicators where the performance had remained stagnant or deteriorated. This shows that there is substantial scope of improvement for all UTs to improve their performance on various indicators. Detailed indicator-specific performance snapshot of UTs is presented in Annexure 4, which provides direction as well as the magnitude of the incremental change of indicators from base year to reference year.

Figure 4.17 - Union Territories: Performance in the Key Inputs/Processes domain, base and reference years

Puducherry

Chandigarh

Delhi


Lakshadweep

Daman & Diu

Andaman & Nicobar

52.99

52.10 56.27

45.9642.18

37.09

29.55 38.33

40.0536.11

26.75 30.13

40.97

54.28

20 40 50 60 -4 0 4 830


-1.29

3.78

3.88

8.78

-4.17

-3.94

-3.38



Figure 4.18 - Union Territories: Number of indicators/sub-indicators, by category of incremental performance

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Note: For a UT, the incremental performance on an indicators is classified as not applicable (NA) in instances such as: (i) Data Integrity Measure indicator wherein the same data has been used for base year and reference year due to overlapping periods of NFHS-4; (ii) Service coverage indicators with 100 percent values in both base and reference years; (iii) The data value for a particular indicator is NA in base year or reference year or both.

4.4 STATES AND UNION TERRITORIES: PERFORMANCE ON INDICATORS

This section presents the findings related to State-wise performance by each indicator included in the Health Index. It also draws comparisons between the base year and reference year performance by each indicator.

DOMAIN 1: HEALTH OUTCOMES

SUB-DOMAIN 1.1: KEY OUTCOMES

Indicator 1.1.1: Neonatal Mortality Rate (NMR)

40

The NMR or the number of neonatal deaths (occurring in the first 28 days of life) per 1000 live births during a specific year reflects the quality of prenatal, intrapartum, and neonatal care services. This is an important indicator as approximately 68 percent of infant deaths in India occur during the neonatal period8. The NMR is available for the Larger States and is the highest in Odisha and the lowest in Kerala for both the base year (2014) and reference year (2015). All States reported a decline in the NMR from the base year (2014) to reference year (2015) except for Haryana, Bihar and Uttarakhand where it increased marginally, remaining static in Kerala and Tamil Nadu. The most progressive decline in the NMR was observed in Himachal Pradesh and Jammu & Kashmir where the decline was approximately 23 to 24 percent. Despite reductions, the NMR remains high in many States and concerted efforts need to be made to reach the NMR national policy goal of 16 deaths per 1000 live births by 20259and 12 deaths per 1000 live births by 2030 (the SDGs). Kerala, Punjab, Tamil Nadu and Maharashtra have already attained the National Health Policy (NHP) 2017 NMR goal for 2025, while Kerala also has the notable distinction of surpassing the SDG 2030 target.

8 Office of the Registrar General and Census Commissioner (India). India SRS Statistical Report 2015. New Delhi, India.9 Ministry of Health and Family Welfare, Government of India. National Health Policy – 2017. New Delhi: MoHFW; 2017.

Figure 4.19 - Indicator 1.1.1: Neonatal Mortality Rate - Larger States

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41

Indicator 1.1.3: Total Fertility Rate (TFR)

The TFR represents the average number of children that would be born to a woman if she experiences the current age-specific fertility rate throughout her reproductive years (15-49 years). A high level of fertility is associated with extreme poverty, gender inequality, maternal mortality, and other dimensions of sustainable development. The TFR indicator is available only for the Larger States. In 2015, 12 of the 21 Larger States (Andhra Pradesh, Himachal Pradesh, Jammu & Kashmir, Karnataka, Kerala, Maharashtra, Odisha, Punjab, Tamil Nadu, Telangana, Uttarakhand and West Bengal) have achieved the replacement level fertility (TFR ≤ 2.1). The fertility rate remains at 2.7 or above in Bihar, Jharkhand, Madhya Pradesh, Rajasthan and Uttar Pradesh. The remaining three States (Assam, Gujarat, and Haryana) are close to achieving the replacement level of fertility with TFR levels between 2.2 and 2.3. A comparison between the base year (2014) and reference year (2015) indicates that six States (Chhattisgarh, Gujarat, Haryana, Jharkhand, Rajasthan and Uttar Pradesh) have showed a decline of 0.1 in TFR.

Figure 4.20 - Indicator 1.1.2: Under-five Mortality Rate - Larger States

Indicator 1.1.2: Under-five Mortality Rate (U5MR)

The U5MR reflects the probability of dying before attaining the age of 5. The U5MR or the number of deaths under the age of 5 per 1000 live births during a specific year reflects a combination of several factors, such as the nutritional status of children, health knowledge of mothers, level of immunization and oral rehydration therapy, access to maternal and child health services, income of the family, and availability of safe drinking water and basic sanitation services. The U5MR is available only for the Larger States; a comparison between the base year and reference year shows that U5MR declined in 14 States, remained stagnant in four (Kerala, Punjab, West Bengal, and Karnataka) and increased in three States (Maharashtra, Uttarakhand and Haryana). Jammu & Kashmir, Jharkhand, Bihar, and Uttar Pradesh recorded significant decline (between 9 to 20 percent) in U5MR between the base year (2014) and the reference year (2015). Kerala and Tamil Nadu have already achieved the National Health Policy 2017 U5MR target for 2025 of 23 deaths per 1000 live births. However, 12 States, namely Uttarakhand, Andhra Pradesh, Gujarat, Jharkhand, Haryana, Bihar, Chhattisgarh, Rajasthan, Uttar Pradesh, Odisha, Assam and Madhya Pradesh, with U5MR above 35 deaths per 1000 live births will require concerted effort to ensure that this target is achieved.

Source: SRS

13

21 23 27

35 30 31

36 37 36 40 41 44

40

53 49 51 57

60 66 65

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Jammu &

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42

Indicator 1.1.4: Proportion of Low Birth Weight (LBW) among newborns

The LBW (≤2.5 kg) among newborns is an important predictor of newborn health and survival. There are several risk factors related to the mother that may contribute to low birth weight, such as child bearing at a young age, multiple pregnancies, poor nutrition, heart disease or hypertension, untreated coeliac disease, and insufficient prenatal care. Reduction in the proportion of babies born with LBW therefore requires the convergence of interventions across several determinants of health. The HMIS MoHFW data for base year (2014-15) and reference year (2015-16) show that the proportion of LBW among newborns is high in many States and UTs. Among all States and UTs, Dadra & Nagar Haveli report the highest percentage of LBW (35 percent in the base year and 29 percent in the reference year). Other States with a high (≥15 percent) proportion of LBW newborns include Haryana, West Bengal, Assam, Odisha, Rajasthan, Goa and all UTs except Lakshadweep. Across all States and UTs there has been little progress in reducing the proportion of LBW newborns between the base year and the reference year and, in fact, this has increased in several States. Hence, almost all States and UTs need to focus on strategies and interventions to address this issue and break the inter-generational cycle of malnutrition.

Figure 4.22 - Indicator 1.1.4: Proportion of Low Birth Weight among newborns - Smaller States and UTs

3.9

4.1 4.

7 5.8

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10.6

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4.9

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16.1

22.5

20.9

16.9

34.7

5.6

15.5

17.2

20.8

21.4

24.4

29.4

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

Low

birt

h w

eigh

t am

ong

new

born

s (%

)

Union Territories

Base Year (2014-15) Reference Year (2015-16) Source: HMIS Source: HMIS

Manipu

r

Nagala

nd

Mizoram

Arunac

hal P

rades

h

Megha

laya

Sikkim Goa

Tripu

ra

Laksh

adwee

p

Puduc

herry

Andam

an & Nico

bar

Chand

igarh

Delhi

Daman

& Diu

Dadra

& Nagar

Haveli

Figure 4.21 - Indicator 1.1.4: Proportion of Low Birth Weight among newborns - Larger States

6.1

6.3

5.6 6.0 6.

7 7.8

7.8

11.7

10.6

10.8

10.8

11.6

8.7 10

.5

14.6

14.2

14.6

15.5

18.2

20.1

27.4

5.7

5.9 6.

7 6.9 7.2

7.3

7.4

9.6 10

.5

11.5

11.7

12.2

12.6

13.0

13.7

14.1

14.9

16.5

16.7

19.2

25.5

0.0

5.0

10.0

15.0

20.0

25.0

30.0

Low

birt

h w

eigh

t am

ong

new

born

s (%

)

Base Year (2014-15) Reference Year (2015-16) Source: HMIS

Telan

gana

Jammu &

Kashm

ir

Andhra

Prades

h

Punjab Biha

r

Uttarak

hand

Uttar P

rades

h

Karnata

ka

Gujarat

Kerala

Chhatt

isgarh

Himac

hal P

rades

h

Mahara

shtra

Haryan

a

West B

enga

l

Assam

Odisha

Rajasth

an

Tamil N

adu

Madhy

a Prad

esh

Jhark

hand

43

SUB-DOMAIN 1.2: INTERMEDIATE OUTCOMES

Indicator 1.2.1: Full immunization coverage

This indicator reflects upon the success of the immunization programme and captures the proportion of infants between the ages of 9-11 months who have received one dose of BCG, 3 doses of DPT, 3 doses of OPV, and one dose of measles vaccine. Reference year data shows that 19 States and UTs have full immunization coverage of at least 90 percent, the 2025 target specified in the National Health Policy 2017. Jammu & Kashmir, Mizoram, Andaman & Nicobar Islands and Lakshadweep have 100 percentcoverage during the reference year (2015-16). Madhya Pradesh (75 percent), Nagaland

Figure 4.23 - Indicator 1.1.5: Sex Ratio at Birth - Larger States

Indicator 1.1.5: Sex Ratio at Birth (SRB)

Sex Ratio at Birth or the number of girls born for every 1000 boys born during a specific year is an important indicator and reflects the extent to which there is reduction in the number of girl children born by sex-selective abortions. This indicator was only available for the category of Larger States. The SRB is substantially lower in almost all Larger States - 17 out of 21 States have SRB of less than 950 females per 1000 males. Further, in most States, SRB has declined between the base year (2012-14) and reference year (2013-15), except for Bihar, Punjab and Uttar Pradesh where improvements in SRB were noted, and Jammu & Kashmir where it stagnated. Chhattisgarh, Karnataka, Himachal Pradesh, Assam, Maharashtra, Rajasthan, Gujarat, Uttarakhand and Haryana recorded substantial drops (10 or more points) in this indicator. There is a clear need for States to effectively implement the Pre-Conception and Pre-Natal Diagnostic Techniques (PCPNDT) Act, 1994 and take appropriate measures to promote the value of the girl child.

!

974

973

952

953

950

938

927

919

919

907

921

910 91

8

899

870

869

896

893

907

871

866

967

961

951

950

939

924

919

918

918

916

911

902

900

899

889

879

878

861

854

844

831

750

800

850

900

950

1000

Num

ber o

f girl

s bo

rn fo

r eve

ry 1

000

boys

bor

n


Source: SRS

Kerala

Chhatt

isgarh

West B

enga

l

Odisha

Karnata

ka

Himac

hal P

rades

h

Madhy

a Prad

esh

Andhra

Prades

h

Telan

gana

Bihar

Tamil N

adu

Jhark

hand

Assam

Jammu &

Kashm

ir

Punjab

Uttar P

rades

h

Mahara

shtra

Rajasth

an

Gujarat

Uttarak

hand

Haryan

a

44

Figure 4.24 - Indicator 1.2.1: Full immunization coverage - Larger States

Figure 4.25 - Indicator 1.2.1: Full immunization coverage - Smaller States and UTs

(64 percent) and Dadra & Nagar Haveli (77 percent) have the lowest coverage among the Larger States, Smaller States and UTs respectively. From base to reference year, Maharashtra, West Bengal, Kerala, Andhra Pradesh, Telangana, Odisha, Tamil Nadu, Rajasthan, Meghalaya, Tripura and Daman & Diu reported a decline in immunization coverage. It is evident that several States need to implement specific strategies to attain the goals set out in National Health Policy 2017, which targets more than 90 percent full immunization coverage by 2025. Telangana, Jharkhand, Assam, Odisha, Uttar Pradesh, Haryana, Tamil Nadu, Rajasthan, Madhya Pradesh, Tripura, Sikkim, Arunachal Pradesh, Nagaland, Daman & Diu, Puducherry and Dadra & Nagar Haveli fall short of the target of 90 percent coverage. Importantly, while the average full immunization coverage among the Larger States is 90 percent, it is significantly lower for Smaller States at 84 percent.

89.8

96.1

91.8

98.6

92.3

100.

0

94.9

95.5

97.6

90.3

85.8

82.1

100.

0

80.8

84.1

88.0

82.9

82.5

85.5

79.0

74.3

100.

0

99.6

99.3

98.2

96.2

95.9

95.2

94.6

91.6

90.6

90.5

89.7

89.1

88.1

88.0

85.3

84.8

83.5

82.7

78.1

74.8

0.0

20.0

40.0

60.0

80.0

100.0

120.0

Full

imm

uniza

tion

cove

rage

am

ong

infa

nts

be

twee

n ag

es o

f 9-1

1 m

onth

s (%

)


Source: HMIS

Jammu &

Kashm

ir

Punjab

Uttarak

hand

Mahara

shtra

Karnata

ka

West B

enga

l

Kerala

Gujarat

Andhra

Prades

h

Chhatt

isgarh Biha

r

Telan

gana

Assam

Uttar P

rades

h

Haryan

a

Tamil N

adu

Rajasth

an

Madhy

a Prad

esh

Jhark

hand

Odisha

Himac

hal P

rades

h

100.

0

94.4

91.3

96.4

87.4

74.1

60.6

61.9

100.

0

96.3

95.2

93.3

84.3

74.4

65.0

63.9

0.0

20.0

40.0

60.0

80.0

100.0

120.0

Full

imm

uini

zatio

n co

vera

ge a

mon

g in

fant

s

betw

een

9-11

mon

ths

(%)

Smaller States


84.6

100.

0

90.9

92.3

85.0

73.9

75.5

100.

0

100.

0

96.2

93.6

79.7

77.6

77.1

0.0

20.0

40.0

60.0

80.0

100.0

120.0

Full

imm

uniza

tion

cove

rage

am

ong

infa

nts

be

twee

n 9-

11m

onth

s (%

)

Union Territories


Mizoram

Manipu

rGoa

Megha

laya

Tripu

raSikk

im

Nagala

nd

Arunac

hal P

rades

h

Andam

an & Nico

bar

Laksh

adwee

pDelh

i

Chand

igarh

Daman

& Diu

Puduc

herry

Dadra

& Nagar

Haveli

45

Figure 4.26 - Indicator 1.2.2: Proportion of institutional deliveries - Larger States

Indicator 1.2.2: Proportion of institutional deliveries

Institutional deliveries (public and private) can play a substantial role in addressing maternal and infant mortality and morbidity. In the reference year (2015-16), only six States and UTs achieved more than 90 percent coverage - Gujarat and Kerala among Larger States; Mizoram and Goa among Smaller States; and Chandigarh and Puducherry among UTs. Other States need to make substantial efforts to improve the coverage of institutional deliveries, particularly Madhya Pradesh, Chhattisgarh, Uttarakhand, Bihar, Uttar Pradesh, Meghalaya, Nagaland and Arunachal Pradesh, where less than two-thirds of deliveries currently take place at health facilities. In terms of incremental progress, approximately 40 percent of the States and UTs made modest or no progress in institutional deliveries coverage. Andhra Pradesh (64 percent) and Telangana (44 percent) made the most notable progress and the coverage increased by more than 40 percent between base year (2014-15) and reference year (2015-16).

90.8

96.0

53.1

59.2

89.2

83.2

86.0

79.9

81.5

80.8

77.1

72.7

74.7

74.8

67.5

60.5

63.1

59.6

64.3

53.0

43.6

97.8

92.6

87.1

85.4

85.3

82.3

81.8

81.3

80.5

80.3

78.8

74.3

73.9

73.5

67.5

67.4

64.8

64.5

62.6

57.1

52.4

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Inst

itutio

nal D

eliv

erie

s (%

)


Gujarat

Kerala

Andhra

Prades

h

Telan

gana

Mahara

shtra

Punjab

Tamil N

adu

West B

enga

l

Jammu &

Kashm

ir

Haryan

a

Karnata

kaAssa

m

Rajasth

an

Odisha

Himac

hal P

rades

h

Jhark

hand

Madhy

a Prad

esh

Chhatt

isgarh

Uttarak

hand

Bihar

Uttar P

rades

h

46

Figure 4.28 - Indicator 1.2.3: Total case notification rate of TB - Larger States

210

170

165

143 15

5

136

139

87

128

145

123 13

7

113 12

2

113

100

100 10

6

93

72

74

207

193

172

164

164

145

143

139

138

138

137

136

125

123

123

108

105

99

93

84

72

0

50

100

150

200

Tota

l cas

e no

tific

atio

n ra

te o

f TB

pe

r 100

,000

pop

ulat

ion


Gujarat

Kerala

Andhra

Prades

h

Telan

gana

Mahara

shtra

Punjab

Tamil N

adu

West B

enga

l

Jammu &

Kashm

ir

Haryan

a

Karnata

kaAssa

m

Rajasth

anOdis

ha

Himac

hal P

rades

h

Jhark

hand

Madhy

a Prad

esh

Chhatt

isgarh

Uttarak

hand

Bihar

Uttar P

rades

h

Source: RNTCP MIS, MoHFW

Indicator 1.2.3: Total case notification rate of tuberculosis (TB)

Total case notification rate is the number of new and relapsed TB cases notified, in both public and private facilities per 100,000 population during a specific year. It is an important indicator reflecting diagnosis and reporting of TB cases in the National Surveillance System and is an essential element for effective implementation of the End TB Strategy. The total case notification varied between 72 per 100,000 population in Jammu & Kashmir to 207 per 100,000 population in Himachal Pradesh. The total case notification rate increased by 10 cases per 100,000 population or more in Gujarat, Madhya Pradesh, Kerala, Chhattisgarh, Uttar Pradesh, Tamil Nadu, Telangana, Bihar, Tamil Nadu, Uttar Pradesh, Chhattisgarh, Kerala, Madhya Pradesh, Gujarat, Sikkim, Delhi and Daman & Diu and has decreased by 10 cases per 100,000 population or more in Nagaland, Meghalaya, Tripura, Andaman & Nicobar and Lakshadweep.

Figure 4.27 - Indicator 1.2.2: Proportion of institutional deliveries - Smaller States and UTs

100.

0

91.3

78.5

74.9

72.0

59.6

57.0

56.0

96.3

92.5

79.4

73.5

70.2

62.1

58.1

56.5

0.0

20.0

40.0

60.0

80.0

100.0

120.0

Inst

itutio

nal D

eliv

erie

s (%

) Smaller States


100.

0

100.

0

88.2

76.4

79.4

76.2

75.3

100.

0

100.

0

87.1

85.4

80.6

80.2

72.0

0.0

20.0

40.0

60.0

80.0

100.0

120.0

Inst

itutio

nal D

eliv

erie

s (%

)

Union Territories

Base Year (2014-15) Reference Year (2015-16) Source: HMISSource: HMIS

Mizoram Goa

Tripu

ra

Manipu

r

Sikkim

Megha

laya

Nagala

nd

Arunac

hal P

rades

h

Chand

igarh

Puduc

herry

Dadra

& Nagar

Haveli

Laksh

adwee

pDelh

i

Andam

an & Nico

bar

Daman

& Diu

47

Indicator 1.2.4: Treatment success rate of new microbiologically confirmed TB cases

Treatment success rate of TB cases is the proportion of new cases cured and their treatment completed against the total number of new microbiologically confirmed TB cases registered during a specific year. It is an important indicator that reflects the performance of the Revised National Tuberculosis Control Programme. The National Health Policy 2017 establishes a target of ≥85 percent for treatment success rate of TB cases, which was achieved by most States and UTs except Karnataka, Maharashtra, Manipur, Sikkim, Nagaland (dropped from base year) and Daman & Diu.

Figure 4.30 - Indicator 1.2.4: Treatment success rate of new microbiologically confirmed TB cases - Larger States

Figure 4.29 - Indicator 1.2.3: Total case notification rate of TB - Smaller States and UTs

Source: RNTCP MIS, MoHFWSource: RNTCP MIS, MoHFW

222

183

186

173

170

127

82

195 24

1

186

183

139

137

131

81

61

0 50

100 150 200 250 300

Tota

l cas

e no

tific

atio

n ra

te o

f TB

pe

r 100

,000

pop

ulat

ion

Smaller States


337

300

146 157

138

95

61

348

305

166

139

133

103

35

0 50

100 150 200 250 300 350 400

Tota

l cas

e no

tific

atio

n ra

te o

f TB

pe

r 100

,000

pop

ulat

ion

Union Territories


Sikkim

Mizoram

Arunac

hal P

rades

h

Nagala

nd

Megha

laya

Goa

Tripu

ra

Manipu

r

Delhi

Chand

igarh

Daman

& Diu

Andam

an & Nico

bar

Dadra

& Nagar

Haveli

Puduc

herry

Laksh

adwee

p

89.8

89.7

90.4

89.0

89.7

90.0

88.2

88.5

87.4

90.4

87.6

86.0

86.0

88.2

86.9

86.4

85.4

85.5

82.3

83.3

83.9

90.9

90.3

90.3

89.7

89.6

89.6

89.1

88.9

88.9

88.5

88.3

87.5

87.5

87.5

87.2

86.5

86.2

86.0

85.4

84.7

84.2

78.0

80.0

82.0

84.0

86.0

88.0

90.0

92.0

Trea

tmen

t suc

cess

rate

of n

ew m

icro

biol

ogic

ally

co

nfirm

ed T

B ca

ses

(%)

Base Year (2014) Reference Year (2015) Source: RNTCP MIS, MoHFW

Jhark

hand

Madhy

a Prad

esh

Rajasth

anBiha

r

Himac

hal P

rades

h

Telan

gana

Gujarat

Andhra

Prades

h

Odisha

Jammu &

Kashm

ir

Haryan

aKera

la

Punjab

Assam

Uttarak

hand

Tamil N

adu

Karnata

ka

Mahara

shtra

Uttar P

rades

h

West B

enga

l

Chhatt

isgarh

48

Indicator 1.2.5: Proportion of people living with HIV (PLHIV) on antiretroviral therapy (ART)

This indicator tracks progress in access to treatment for PLHIV for the category of Larger and Smaller States, but not for UTs (data not available for some UTs). The National Health Policy 2017 sets a specific goal corresponding to achieving the global target of 2020, namely to ensure that 90 percent of all people tested positive for HIV receive sustained ART. Out of 29 States, three (Jammu & Kashmir, Meghalaya and Mizoram) have achieved this target while five have 80 to 90 percent of PLHIV on ART in the reference year (2015-16). Eight states have less than 50 percent of the PLHIV on ART (reference year 2015-16), namely Rajasthan, Jharkhand, Bihar, West Bengal, Odisha, Sikkim, Arunachal Pradesh and Tripura. Apart from Tripura, the other 28 states have shown some incremental progress in this indicator. However, significant improvements are needed to achieve 90 percent coverage.

Figure 4.32 - Indicator 1.2.5: Proportion of people living with HIV on antiretroviral therapy - Larger States

Figure 4.31 - Indicator 1.2.4: Treatment success rate of new microbiologically confirmed TB cases - Smaller States and UTs

86.5

88.6

86.4

88.0

82.3

85.0

78.8

90.7

90.6

88.5

87.3

86.4

85.8

82.6

77.2

71.9

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0

Trea

tmen

t suc

cess

rate

of n

ew

mirc

obio

lgic

ally

con

firm

ed T

B ca

ses

(%)

Smaller States


85.5

86.7

88.5

86.2

85.2

89.5

83.1

91.5

91.3

89.2

86.7

86.3

85.6

79.5

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0

Trea

tmen

t suc

cess

rate

of n

ew

mic

robi

olog

ical

ly c

onfir

med

TB

case

s (%

)

Union Territories


Source: RNTCP MIS, MoHFWSource: RNTCP MIS, MoHFW

Mizoram

Tripu

ra Goa

Arunac

hal P

rades

h

Megha

laya

Manipu

r

Nagala

ndSikk

im

Andam

an & Nico

bar

Laksh

adwee

p

Puduc

herry

Delhi

Dadra

& Nagar

Haveli

Chand

igarh

Daman

& Diu

88.7

83.3

83.5

81.9

77.2

79.2

72.4

72.4

61.8

62.7

58.9

53.0

51.3

47.2

50.2

52.3

42.4

36.1

30.7

31.0

28.3

96.4

88.7

87.7

87.1

84.6

79.9

76.1

76.1

66.7

65.3

64.6

61.0

57.8

53.1

52.4

51.5

46.4

39.4

37.2

35.9

33.0

0.0

20.0

40.0

60.0

80.0

100.0

120.0

PLHI

V on

ART

(%)

Base Year (2014-15) Reference Year (2015-16) Source: Central MoHFW Data

Jammu &

Kashm

ir

Karnata

ka

Mahara

shtra

Tamil N

adu

Punjab

Himac

hal P

rades

h

Andhra

Prades

hKera

la

Telan

gana

Uttarak

hand

Assam

Madhy

a Prad

esh

Chhatt

isgarh

Haryan

a

Rajasth

an

Jhark

hand

Bihar

West B

enga

l

Odisha

Uttar P

rades

h

Gujarat

49

Indicator 1.2.6: Average out-of-pocket expenditure per delivery in public health facility

The National Family Health Survey (NFHS)-4 data on average out-of-pocket (OOP) expenditure per delivery in public health facility is considered here as a proxy indicator for overall OOP expenditure. This data is available only for 2015-16 and hence the indicator is reported only for the reference year. There is significant variation in the average OOP expenditure across the States. The expenditures range from as low as INR 471 in Dadra & Nagar Haveli to as high as INR 10,076 in Manipur. The top five States and UTs with average expenditure above INR 6,000 per delivery in a public facility are Manipur (INR 10,076), Delhi (INR 8,719), West Bengal (INR 7,782), Kerala (INR 6,901), and Arunachal Pradesh (INR 6,474). The average OOP expenditure per delivery in public health facility for Larger States is INR 3,080, for Smaller States it is INR 5,170, and for UTs it is INR 2,995. Given the number of NHM interventions targeting pregnant women, such as Janani Suraksha Yojana (JSY), Janani Shishu Suraksha Karyakram (JSSK), and Referral Transport to ensure free delivery at public health facilities, the States should aim to reduce the OOP expenditure.

Figure 4.34 - Indicator 1.2.6: Average out-of-pocket expenditure per delivery in public health facility (in INR) - Larger States

Figure 4.33 - Indicator 1.2.5: Proportion of people living with HIV on antiretroviral therapy - Smaller States

98.7

96.7

63.8

70.9

54.0

32.5

18.7

23.1

100.

0

100.

0

73.8

72.8

63.9

33.5

28.2

5.8

0.0

20.0

40.0

60.0

80.0

100.0

120.0

Meghalaya Mizoram Nagaland Goa Manipur Sikkim Arunachal Pradesh

Tripura

PLHI

V on

ART

(%)

Base Year (2014-15) Reference Year (2015-16) Source: Central MoHFW Data

1387

1476

1480

1503 1724 1890

1956

2136

2138 2399

2496 30

52

3210

3329

3487 38

93

4020

4192

4225

6901

7782

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

Aver

age

OOP

expe

nditu

re p

er d

eliv

ery

in p

ublic

hea

lth fa

cilit

y (in

INR)

Source: NFHS-4 (2015-16)

Madhy

a Prad

esh

Jhark

hand

Chhatt

isgarh

Haryan

aBiha

r

Punjab

Uttar P

rades

h

Andhra

Prades

h

Gujarat

Uttarak

hand

Tamil N

adu

Assam

Rajasth

an

Mahara

shtra

Telan

gana

Jammu &

Kashm

ir

Odisha

Kerala

West B

enga

l

Himac

hal P

rades

h

Karnata

ka

50

DOMAIN 2: GOVERNANCE AND INFORMATION SUB-DOMAIN 2.1: HEALTH MONITORING AND DATA INTEGRITY

Indicator 2.1.1: Data Integrity Measure: Institutional deliveries and ANC registered within first trimester

This indicator captures the percentage deviation of HMIS reported data from the NFHS-4 data in order to assess the quality and integrity of reported data. Specifically, data from HMIS for last 5 years (2011-12 to 2015-16) on the proportion of institutional deliveries and ANC registered within the first trimester is compared with NFHS-4 conducted during 2015-16.

Figure 4.36 - Indicator 2.1.1: Data Integrity Measure - Institutional deliveries - Larger States

Figure 4.35 - Indicator 1.2.6: Average out-of-pocket expenditure per delivery in public health facility (in INR) - Smaller States and UTs

2509 2892 43

27

4412

4836 58

34 6474

1007

6

0

2000

4000

6000

8000

10000

12000

Aver

age

OOP

expe

nditu

re

per d

eliv

ery

in p

ublic

hea

lth fa

cilit

y (i

n IN

R)

Smaller States

471 12

58 1581 19

99 2357

4580

8719

0

2000

4000

6000

8000

10000

Aver

age

OOP

expe

nditu

re

per d

eliv

ery

in p

ublic

hea

lth fa

cilit

y (in

INR)

Union Territories

Source: NFHS-4 (2015-16)Source: NFHS-4 (2015-16)

Sikkim

Megha

laya

Mizoram

Tripu

ra Goa

Nagala

nd

Manipu

r

Arunac

hal P

rades

h

Dadra

& Nagar

Haveli

Andam

an & Nico

bar

Daman

& Diu

Puduc

herry

Chand

igarh

Laksh

adwee

pDelh

i

0.3

0.7

1.2

2.1

3.7

4.6

8.0

10.9

12.4

12.4

12.4

12.7

13.8

14.9

18.2

21.1

21.2

22.3

23.1

23.5

36.6

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

Devi

atio

n of

HM

IS d

ata

with

NFH

S -4

dat

a fo

r ins

titut

iona

l del

iver

ies

(%)

Source: HMIS & NFHS-4

Assam

Gujarat

Mahara

shtra

West B

enga

l

Kerala

Haryan

a

Jhark

hand

Punjab

Tamil N

adu

Jammu &

Kashm

ir

Rajasth

an

Odisha

Himac

hal P

rades

hBiha

r

Karnata

ka

Chhatt

isgarh

Madhy

a Prad

esh

Andhra

Prades

h

Uttar P

rades

h

Uttarak

hand

Telan

gana

51

Figure 4.37 - Indicator 2.1.1: Data Integrity Measure - ANC registered within first trimester - Larger States

In the case of institutional deliveries, Uttar Pradesh, Nagaland and Puducherry have the widest discrepancy between HMIS and NFHS-4 data. The trend is somewhat different in the case of ANC registered within the first trimester, where Jharkhand, Nagaland, and Puducherry have the widest variation between the HMIS and NFHS-4 data. The States, UTs and MoHFW need to ensure that this deviation is minimized by adopting robust data quality mechanisms.

Figure 4.38 - Indicator 2.1.1: Data Integrity Measure - Institutional deliveries - Smaller States and UTs

Figure 4.39 - Indicator 2.1.1: Data Integrity Measure - ANC registered within first trimester - Smaller States and UTs

Source: HMIS & NFHS-4

.9

.1

5.6

7.3

8.2

9.2

10.0

10.8

13.5

15.4

15.8

16.3

18.4

19.1

21.2

22.1

22.8

24.9

25.9

42.4

53.5

0.0

10.0

20.0

30.0

40.0

50.0

60.0

0 2Devi

atio

n of

HM

IS d

ata

with

NFH

S -

4 da

ta fo

r ANC

regi

ster

ed w

ithin

fir

st tr

imes

ter (

%)

Uttar P

rades

h

Gujarat

Mahara

shtra

Himac

hal P

rades

h

Karnata

ka

Madhy

a Prad

esh

Punjab

Jammu &

Kashm

ir

Uttarak

hand

Andhra

Prades

h

Telan

gana

Rajasth

anBiha

r

Assam

Tamil N

adu

Kerala

Chhatt

isgarh

West B

enga

l

Jhark

hand

Haryan

a

Odisha

1.4 2.9

3.4 5.0 13

.4

22.0 29

.2

54.8

0.010.020.030.040.050.060.0

10.8

15.1

17.4

18.1

29.4

58.0

90.5

0.020.040.060.080.0

100.0

Source: HMIS & NFHS-4Source: HMIS & NFHS-4

Smaller States Union Territories

Devi

atio

n of

HM

IS d

ata

with

NF

HS -

4 da

ta fo

r ins

titut

iona

l de

liver

ies

(%)

Devi

atio

n of

HM

IS d

ata

with

NF

HS -

4 da

ta fo

r ins

titut

iona

l de

liver

ies

(%)

Arunac

hal P

rades

h

Manipu

r

Tripu

ra Goa

Megha

laya

Mizoram

Nagala

ndSikk

imDelh

i

Dadra

& Nagar

Haveli

Daman

& Diu

Andam

an & Nico

bar

Laksh

adwee

p

Puduc

herry

Chand

igarh

5.6 10

.6

10.9 18

.7 23.7 26

.8

28.2

107.

9

0.0

20.0

40.0

60.0

80.0

100.0

120.0

2.8

12.2

15.3

22.1

27.8

27.9

48.8

0.0

10.0

20.0

30.0

40.0

50.0

60.0

Source: HMIS & NFHS-4Source: HMIS & NFHS-4

Union Territories

Devi

atio

n of

HM

IS d

ata

with

NF

HS -

4 da

ta fo

r ANC

regi

ster

ed

with

in fi

rst t

rimes

ter (

%)

Smaller States

Arunac

hal P

rades

h

Megha

laya

Tripu

ra

Mizoram Goa

Sikkim

Nagala

nd

Manipu

r

Devi

atio

n of

HM

IS d

ata

with

NF

HS -

4 da

ta fo

r ANC

regi

ster

ed

with

in fi

rst t

rimes

ter (

%)

Andam

an & Nico

bar

Laksh

adwee

p

Daman

& Diu

Dadra

& Nagar

Haveli

Delhi

Chand

igarh

Puduc

herry

52

SUB-DOMAIN 2.2: GOVERNANCE

Indicator 2.2.1: Average occupancy of an officer (in months) combined for three key posts at State-level for last three years

This indicator reflects the average occupancy of key administrative officials (in months), combined for the posts of Principal Secretary, Mission Director (NHM) and Director (Health Services) in the last three years. A stable tenure for key administrative positions is very critical for effective implementation of the programs. The data reveals that the average occupancy of Principal Secretary, Mission Director (NHM), and Director (Health Services) or equivalent positions in a period of 36 months (3 years) is the highest in West Bengal (28 months) among the Larger States, Sikkim (24 months) among the Smaller States and Lakshadweep (27 months) among UTs. Many States have an average occupancy per officer for the three key administrative positions of less than 12 months - Chhattisgarh, Haryana, Uttarakhand, Telangana, Karnataka, Tripura, Mizoram, Nagaland and Delhi in the reference year (2013-16). Significant improvements (5 months or more) have been achieved in West Bengal, Uttar Pradesh, Madhya Pradesh, Goa and Manipur, but in Jammu & Kashmir, Kerala, Arunachal Pradesh, Nagaland and Andaman & Nicobar, the occupancy has declined substantially from the base year (2012-15) to the reference year (2013-16). Among the Larger States between the base year (2012-15) and reference year (2013-16), Uttar Pradesh has shown the maximum progress where the average occupancy doubled from 10 to 20 months, while Kerala has shown the maximum decline in the tenure of these officers where the tenure has almost halved from 22 to 12 months.

Figure 4.40 - Indicator 2.2.1: Average occupancy of an officer (in months) combined for three key posts at State-level for last three years - Larger States

Note: Three key posts are Principal Secretary (Health), Mission Director (NHM) and Director (Health Services).

22.0

19.0

20.2

20.0

9.6

17.7

11.9

10.8

10.9

22.8

15.0

11.4

10.2

21.8

11.1

13.0

11.4

13.8

10.7

8.7

6.9

28.0

22.0

20.7

20.4

19.6

17.5

16.5

16.0

15.7

13.8

13.0

12.4

12.1

12.0

12.0

12.0

11.4

11.2

10.4

7.8

6.5

0.0

5.0

10.0

15.0

20.0

25.0

30.0

Source: State Report

West B

enga

l

Rajasth

an

Gujarat

Punjab

Uttar P

rades

h

Andhra

Prades

h

Tamil N

adu

Mahara

shtra

Madhy

a Prad

esh

Jammu &

Kashm

irBiha

r

Assam

Himac

hal P

rades

h

Odisha

Chhatt

isgarh

Haryan

a

Uttarak

hand

Telan

gana

Karnata

kaKera

la

Jhark

hand

Aver

age

occu

panc

y of

an

offic

er

(in m

onth

s) fo

r thr

ee k

ey p

osts

fo

r las

t thr

ee y

ears


53

Indicator 2.2.2: Average occupancy of a full-time officer (in months) for all the districts in last three years - CMOs or equivalent post (heading District Health Services)

In one-third of the States and UTs, the average occupancy of a full-time Chief Medical Officer (CMO) or equivalent post heading the Health Services at the district level is 12 months or less, which hinders effective implementation of programs. A small number of States and UTs (Chhattisgarh, Mizoram, Sikkim, Daman & Diu and Puducherry) reported an average occupancy of more than 24 months. Bihar, Sikkim and Andaman & Nicobar Islands have shown a decline of five or more months in the average occupancy of the CMO from the base year (2012-15) to the reference year (2013-16). This indicator was modified for Andaman & Nicobar Islands and Dadra & Nagar Haveli, where the CMO equivalent posts of Medical Superintendent and regular medical officer were included in the calculation of average occupancy. In Lakshadweep, there was no CMO or equivalent post and hence this indicator is not applicable.

Figure 4.41 - Indicator 2.2.1: Average occupancy of an officer (in months) combined for three key posts at State-level for last three years- Smaller States and UTs

Note: Three key posts are Principal Secretary (Health), Mission Director (NHM) and Director (Health Services).

24.0

14.8

13.3

20.0

19.9

12.0

11.1

11.6

24.0

21.7

21.0

19.3

13.9

10.9

9.8

7.3

0.0

5.0

10.0

15.0

20.0

25.0

30.0

Smaller States

26.8

20.4

22.0

26.0

14.4

10.8

13.7

26.8

21.0

20.0

15.0

14.4

12.0

9.6

0.0

5.0

10.0

15.0

20.0

25.0

30.0

Union Territories

Source: State ReportSource: State Report

Aver

age

occu

panc

y of

an

offic

er

(in m

onth

s) fo

r thr

ee k

ey p

osts

at

sta

te le

vel f

or la

st th

ree

year

s

Aver

age

occu

panc

y of

an

offic

er

(in m

onth

s) fo

r thr

ee k

ey p

osts

at

UT

leve

l for

last

thre

e ye

ars

Sikkim Goa

Manipu

r

Megha

laya

Arunac

hal P

rades

h

Tripu

ra

Nagala

nd

Mizoram

Base Year (2012-15) Reference Year (2013-16) Base Year (2012-15) Reference Year (2013-16)

Laksh

adwee

p

Daman

& Diu

Puduc

herry

Andam

an & Nico

bar

Dadra

& Nagar

Haveli

Chand

igarh

Delhi

54

Figure 4.42 - Indicator 2.2.2: Average occupancy of a full-time officer (in months) for all the districts in last three years - CMOs or equivalent post - Larger States

Figure 4.43 - Indicator 2.2.2: Average occupancy of a full-time officer (in months) for all the districts in last three years - CMOs or equivalent post - Smaller States and UTs

21.9

18.7

18.1

12.3

11.6

10.3

10.0

11.6

14.8

12.8

13.4

12.3

17.6

11.7

16.5

11.2

11.7

13.9

9.1

7.9

6.9

25.4

18.1

17.6

15.6

14.2

14.1

14.0

13.9

13.2

13.2

12.6

11.9

11.9

11.8

11.7

11.5

11.2

10.5

10.2

8.0

7.3

0.0

5.0

10.0

15.0

20.0

25.0

30.0

Aver

age

occu

panc

y of

a C

MO

(in m

onth

s)

for a

ll di

stric

ts in

last

thre

e ye

ars


Chhatt

isgarh

Gujarat

Madhy

a Prad

esh

Mahara

shtra

Uttar P

rades

h

West B

enga

l

Odisha

Karnata

ka

Uttarak

hand

Andhra

Prades

h

Haryan

aBiha

r

Rajasth

anKera

la

Telan

gana

Himac

hal P

rades

h

Punjab

Assam

Tamil

Nadu

Jammu &

Kashm

ir

Jhark

hand


Daman

& Diu

Puduc

herry

Dadra

& Nagar

Haveli

Andam

an & Nico

bar

Delhi

Chand

igarh

20.5

31.5

17.4

19.3

18.6

14.3

15.5

15.0

26.0

25.5

19.9

17.5

17.3

17.3

14.8

12.0

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0 36.0

23.1

18.0

25.5

15.8

15.5

36.0

25.3

18.0

17.4

16.7

15.6

0.0 5.0

10.0 15.0 20.0 25.0 30.0 35.0 40.0



Aver

age

occu

panc

y of

a C

MO

(in m

onth

s)

for a

ll di

stric

ts in

last

thre

e ye

ars

Aver

age

occu

panc

y of

a C

MO

(in m

onth

s)

for a

ll di

stric

ts in

last

thre

e ye

ars

Mizoram

Sikkim

Nagala

nd

Arunac

hal P

rades

h

Manipu

r

Tripu

ra Goa

Megha

laya


55

DOMAIN 3: KEY INPUTS/PROCESSES

SUB-DOMAIN 3.1: HEALTH SYSTEMS AND SERVICE DELIVERY

Indicator 3.1.1: Proportion of vacant healthcare provider positions (regular + contractual) in public health facilities

Vacancies of key health staff are linked with both access to healthcare services as well as their quality. The vacancy status vis-a-vis the total sanctioned positions, for both regular and contractual healthcare providers for key positions in public health facilities including ANMs at sub-centres (SCs), staff nurses at PHCs and CHCs, medical officers (MOs) at PHCs, and Specialists at district hospitals (DHs) is provided below.

a. ANMs at sub-centres: Among the Larger States, less than 25 percent of ANM positions were vacant except for Gujarat and Bihar, which reported 28 percent and 59 percent vacancies respectively. Odisha, Uttar Pradesh, West Bengal and Kerala reported less than 5 percent vacancy of ANM positions. Similarly, among the Smaller States and UTs, less than 25 percent positions were vacant except in Manipur (30 percent), Goa (30 percent), Tripura (39 percent) and Chandigarh (29 percent). Between the base year (2014-15) and reference year (2015-16), Uttar Pradesh, Jammu & Kashmir, Andhra Pradesh, Rajasthan, Karnataka and Bihar have shown significant progress and the ANM vacancies have declined by 5 or more percentage points. Madhya Pradesh, Haryana, Gujarat, Mizoram, Arunachal Pradesh, Manipur, Goa, Tripura and Delhi have shown significant increases (5 or more percentage points) in ANM vacancies during the same period.

Figure 4.44 - Indicator 3.1.1a: Proportion of vacant healthcare provider positions - ANMs at sub-centres - Larger States

Odisha

Uttar P

rades

h

West B

enga

l

Kerala

Punjab

Assam

Chhatt

isgarh

Himac

hal P

rades

h

Mahara

shtra

Jammu &

Kashm

ir

Madhy

a Prad

esh

Andhra

Prades

h

Haryan

a

Uttarak

hand

Rajasth

an

Jhark

hand

Karnata

ka

Gujarat

Bihar

Tamil

Nadu

Telan

gana


0.0

14.1

2.2 4.

9 7.2 10

.9

12.4

8.3 12

.6 17

.7

8.6 9.7

20.6

11.8

15.5

20.2

36.1

19.6

27.9

17.1

67.9

0.0

0.0 0.8 4.

5 8.5

9.0

9.2 9.5

9.9

10.3

14.2

15.2

15.7

16.0

16.9

18.0

19.2

19.7

22.6

28.1

59.3

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

Vaca

ncy

of A

NMs

at S

Cs (%

)


56

b. Staff nurses at PHCs and CHCs: Among the Larger States, the vacancy of staff nurses in PHCs and CHCs was more than 40 percent in Haryana (43 percent), Rajasthan (47 percent), Bihar (50 percent) and Jharkhand (75 percent). From base year (2014-15) to reference year (2015-16), there was significant reduction (16 to 36 percent) in the proportion of vacant position for staff nurses in West Bengal, Karnataka, Jammu & Kashmir and Bihar. Among the Smaller States, Sikkim has the highest vacancy rate (62 percent) followed by Meghalaya (31 percent) and both these States have shown no progress in addressing the vacancies of staff nurses at PHCs and CHCs between the base year and reference year. Tripura made tremendous progress with 22 percentage points reduction in vacancies, bringing the vacancy position of staff nurses at CHCs and PHCs to zero. The vacancies of staff nurses at PHCs and CHCs has increased significantly in Manipur (from 5 to 19 percent) and Arunachal Pradesh (from 4 to 29 percent). The vacancy rate in all UTs is less than 8 percent except Delhi where it increased substantially from 32 to 41 percent.

Figure 4.45 - Indicator 3.1.1a: Proportion of vacant healthcare provider positions - ANMs at sub-centres - Smaller States

Figure 4.46 - Indicator 3.1.1b: Proportion of vacant healthcare provider positions - Staff nurses at PHCs and CHCs - Larger States

0.0

7.8 1

1.3

19.6

2.1

20.6

24.8

15.4

0.0

11.

0 16.1

20.0

22.4

29.9

30.1

38.9

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

Sikkim Nagaland Mizoram Meghalaya Arunachal Pradesh

Manipur Goa Tripura


Vaca

ncy

of A

NMs

at S

Cs (%

)


Odisha

Uttar P

rades

hKera

laAssa

m

West B

enga

l

Telan

gana

Mahara

shtra

Uttarak

hand

Tamil

Nadu

Andhra

Prades

h

Karnata

ka

Jammu &

Kashm

ir

Himac

hal P

rades

h

Punjab

Chhatt

isgarh

Haryan

a

Rajasth

anBiha

r

Jhark

hand

Madhy

a Prad

esh

Gujarat

0.0 1.9 5.

5

4.6

25.7

12.8

16.7

21.8

13.1

17.3

45.2

21.5

42.9

36.5

36.2

37.7

44.3

46.0

48.1

86.2

71.8

0.0 1.9 5.3 9.

0

9.7 12

.8

15.7

19.1

20.0

20.5

26.0

27.2

27.5

33.5

34.0

36.5

37.3

43.2

47.3

50.3

74.9

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0

Vaca

ncy

of S

Ns a

t PHC

s an

d CH

Cs (%

)

Source: State ReportBase Year (2014-15) Reference Year (2015-16)

57

c. Medical officers (MOs) at PHCs: Among the Larger States, the vacancy of MOs at PHCs is the highest in Bihar (64 percent) followed by Madhya Pradesh (58 percent), Jharkhand (49 percent), Chhattisgarh (45 percent) and West Bengal (41 percent). It is the lowest in Kerala (6 percent) followed by Tamil Nadu (8 percent) and Punjab (8 percent). From base to reference year, there has been reduction in MO vacancies in the range of 5 to 25 percentage points in Uttarakhand, Andhra Pradesh, Haryana, Uttar Pradesh, Gujarat and West Bengal. In Himachal Pradesh, MO vacancies increased by 5 percentage points. Among the Smaller States, Meghalaya, Mizoram, Arunachal Pradesh and Manipur also have a high proportion (36 to 43 percent) of vacant positions of MO at PHCs and no reduction in MO vacancies from base to reference year. Tripura and Goa have shown a reduction of 15 percentage points and 17 percentage points in vacant MO positions at PHCs respectively, whereas these have increased in Arunachal Pradesh (from 9 to 39 percent). Among the UTs, Chandigarh has the highest proportion of vacant MO positions at PHCs (69 percent) followed by Andaman & Nicobar (36 percent) with no reduction from base to reference year. There was no MO vacancy in Lakshadweep, while vacancies in the remaining UTs lay in the range of 7 to 17 percent.

Figure 4.47 - Indicator 3.1.1c: Proportion of vacant healthcare provider positions - Medical officers at PHCs - Larger States

Figure 4.48 - Indicator 3.1.1c: Proportion of vacant healthcare provider positions - Medical officers at PHCs - Smaller States

5.6 7.

6 9.8 13

.4

37.2

18.0

14.9

16.8

19.9

16.2

22.3

38.6

36.8

23.2

34.9

39.8

48.4

41.8

45.3

57.8

63.6

5.9 7.

6

7.8 11

.5

12.2

12.8

14.9

17.0

17.8

21.7

22.3

25.4

26.7

26.9

30.2

32.0

41.2

45.0

48.7

58.3

63.6

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

Vaca

ncy

of M

Os a

t PHC

s (%

)


Kerala

Tamil N

adu

Punjab

Karnata

ka

Uttarak

hand

Andhra

Prades

h

Rajasth

an

Mahara

shtra

Assam

Himac

hal P

rades

h

Telan

gana

Haryan

a

Uttar P

rades

h

Odisha

Jammu &

Kashm

ir

Gujarat

West B

enga

l

Chhatt

isgarh

Jhark

hand

Madhy

a Prad

esh

Bihar

0.0

17.0

31.1

26.9

31.9

31.6

9.4

42.8

0.0 2.

1

14.2

27.4

35.7

38.1

38.8

42.8

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

Sikkim Tripura Goa Nagaland Meghalaya Mizoram Arunachal Pradesh

Manipur

Vaca

ncy

of M

Os a

t PHC

s (%

)


58

Several Larger States have a high proportion of vacant specialist positions in district hospitals, particularly in Chhattisgarh (78 percent), Bihar (61 percent), Uttarakhand (60 percent), Gujarat (56 percent), Telangana (55 percent), Madhya Pradesh (51 percent), Jharkhand (50 percent) and Punjab (48 percent). Most States have made limited progress (<5 percentage points) in reducing the vacancies of specialists at district hospitals from base to reference year, except Odisha, Andhra Pradesh, Assam, Jharkhand and Telangana; at the same time, Maharashtra, Punjab and Uttarakhand have shown substantial increases of specialists, ranging between 11 to 26 percentage points. Among the Smaller States, the vacancies among specialist positions is high in Manipur (48 percent), Goa (40 percent) and Arunachal Pradesh (89 percent). While all specialist positions have been filled in Nagaland, specialist vacancies in the remaining States range from 15 to 40 percent. Overall, the Smaller States have shown little or no reduction in vacancies among specialists at district hospitals from base to reference year. A similar situation was observed among the UTs as shown in Figure 4.50.

d. Specialists at district hospital (Medicine, Surgery, Obstetrics and Gynaecology, Paediatrics, Anaesthesia, Ophthalmology, Radiology, Pathology, Ear-Nose-Throat, Dental, Psychiatry):

Figure 4.50 - Indicator 3.1.1d: Proportion of vacant healthcare provider positions - Specialists at district hospitals - Smaller States and UTs

Figure 4.49 - Indicator 3.1.1.d: Proportion of vacant healthcare provider positions - Specialists at district hospitals - Larger States

0.0 15

.2

29.3

34.4

42.7

47.7

87.6

0.0 15

.2

29.7

34.4

39.7

47.7

89.1

0.0 20.0 40.0 60.0 80.0

100.0

Vaca

ncy

of S

peci

alis

ts a

t DHs

(%)

Vaca

ncy

of S

peci

alis

ts a

t DHs

(%)

0.0 18

.2

23.4

38.7

38.2

76.5

100.

0

0.0 18

.2

20.6

40.2

47.1

76.5

100.

0

0.0 20.0 40.0 60.0 80.0

100.0 120.0



Nagala

nd

Mizoram

Megha

laya

Sikkim Goa

Manipu

r

Arunac

hal P

rades

h

Chand

igarh

Dadra

& Nagar

Haveli

Puduc

herry

Delhi

Daman

& Diu

Laksh

adwee

p

Andam

an & Nico

bar


0.0

17.9

43.5

23.0

22.2

20.9

24.5

19.5

40.6

35.7

62.9

41.5

21.7

55.4

50.6

59.8

51.0

38.3

65.0

78.0

0.0

16.7

19.0

20.2

21.5

21.5

22.2

30.3

30.4

32.4

41.7

45.8

47.7

50.3

51.0

54.8

55.5

60.3

60.6

77.7

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

Vaca

ncy

of S

peci

alis

ts a

t DHs

(%)


Haryan

a

Tamil N

adu

Odisha

West B

enga

l

Kerala

Karnata

ka

Jammu &

Kashm

ir

Mahara

shtra

Andhra

Prades

h

Uttar P

rades

hAssa

m

Rajasth

an

Punjab

Jhark

hand

Madhy

a Prad

esh

Telan

gana

Gujarat

Uttarak

hand

Bihar

Chhatt

isgarh

59

Indicator 3.1.2: Proportion of total staff (regular and contractual) for whom an e-payslip can be generated in the IT enabled Human Resources Management Information System (HRMIS)

It is expected that a well-functioning HRMIS leads to efficient financial and personnel management. However, in 2015-16, among the 21 Larger States, only 9 States used e-payslips to disburse staff salaries, using HRMIS. Among them, the proportion of staff receiving such payments varies from as low as 8 to 100 percent. The States with the highest rates of e-payments are Kerala (100 percent), Maharashtra (68 percent), Odisha (76 percent), Tamil Nadu (85 percent) and West Bengal (81 percent), while Andhra Pradesh, Gujarat and Karnataka are using HRMIS based e-payments for 36 to 59 percent of their staff. It is important for other States to initiate and fully operationalize HRMIS for effective human resources management. All the Smaller States except Arunachal Pradesh (39 percent) have not yet initiated HRMIS based e-payments to staff. Among the UTs, Andaman & Nicobar, Dadra & Nagar Haveli, Daman & Diu and Lakshadweep are yet to initiate e-payments. The remaining UTs are making use of HRMIS based e-payslip generation (61 to 78 percent).

Indicator 3.1.3.a: Proportion of specified type of facilities functioning as First Referral Units (FRUs)

This is a proxy indicator to assess the functionality of the FRUs and captures the number of facilities conducting a specified number of C-sections per year against the number of required FRUs per MoHFW guidelines (one FRU per 500,000 population) during a specific year. Functional FRUs provide specialized services close to the community and can help to improve access and decongest the client load at higher level facilities. The proxy criteria for a facility to be considered as fully operational FRUs is:

• For sub-district hospitals and CHCs: conducting a minimum of 60 C-Sections per year (36 C-sections per year for Hilly and North-Eastern States, except Assam).

• For district hospitals: conducting a minimum of 120 C-Sections per year (72 C-sections per year for Hilly and North-Eastern States, except Assam).

Note: The number of required FRUs is based on MoHFW guidelines.

Figure 4.51 - Indicator 3.1.3.a: Proportion of specified type of facilities functioning as First Referral Units - Larger States

180.

0

138.

2

129.

2

107.

1 121.

0

105.

7

100.

0

80.0

67.7

61.9

48.5

52.9

45.0

45.4

32.2

31.1

23.4

21.6

15.2

15.3

12.5

196.

0

141.

8

122.

9

121.

4

121.

0

116.

4

95.0

80.0

72.6

65.5

57.6

51.0

50.0

49.2

43.0

32.4

29.2

23.5

22.7

15.8

11.5

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

200.0

Func

tiona

l FRU

s as

aga

inst

requ

ired

num

ber (

%)

Source: State Report & MoHFW

Jammu &

Kashm

ir

Punjab

Tamil N

adu

Himac

hal P

rades

hKera

la

Karnata

ka

Uttarak

hand

Assam

Telan

gana

Odisha

Andhra

Prades

h

Haryan

a

West B

enga

l

Mahara

shtra

Rajasth

an

Chhatt

isgarh

Jhark

hand

Uttar P

rades

hBiha

r

Madhy

a Prad

esh

Gujarat


60

As shown in Figures 4.51 and 4.52, many States have achieved the numerical target of functional FRUs (Jammu & Kashmir, Punjab, Tamil Nadu, Himachal Pradesh, Kerala, Karnataka, Mizoram, Meghalaya, Goa, Nagaland, Arunachal Pradesh and Sikkim). However, several States (West Bengal, Gujarat, Maharashtra, Rajasthan, Chhattisgarh, Jharkhand, Uttar Pradesh and Bihar) lag behind substantially with 50 percent or less of the required functional FRUs. These States need to plan strategically for operationalizing more facilities as FRUs, which are critical for saving the lives of mothers and children. Almost all UTs have the required number of fully functional FRUs. From base to reference year, most States and UTs have either maintained the earlier level or shown minimal increase in the percentage of functional FRUs. None of the facilities in Andaman & Nicobar function as FRU despite the need of one functional FRU as per MoHFW guidelines.

Note: The number of required FRUs is based on MoHFW guidelines.

Figure 4.52 - Indicator 3.1.3.a: Proportion of specified type of facilities functioning as First Referral Units - Smaller States

Indicator 3.1.3.b: Proportion of functional 24x7 PHCs

The functioning of 24x7 PHCs is important for providing a basic package of health services to the community and for reducing the workload at higher level facilities. To assess the proportion of functional 24x7 PHCs providing all stipulated healthcare services round the clock during a specific year, the norm of at least ten (five in Hilly States) deliveries per month was considered. The required number of functional 24x7 PHCs per state was calculated using the norm of one 24x7 PHC per 100,000 population. On the basis of this norm, only Assam, Sikkim, Meghalaya, Nagaland, Mizoram, Tripura, Andaman & Nicobar and Dadra & Nagar Haveli have achieved the target of the required number of 24x7 PHCs, whereas Kerala, Chandigarh, Lakshadweep and Puducherry are yet to operationalize a single 24x7 PHC. Most Larger States need to substantially increase the number of functional 24x7 PHCs in order to reach the required target. Among the Smaller States, Manipur, Arunachal Pradesh and Goa need to deploy strategic effort to operationalize more 24x7 PHCs. From base to reference year, an increase of five or higher percentage points in functional 24x7 PHCs as against required number was observed in Assam (7 percentage points), Sikkim (50 percentage points), Meghalaya (13 percentage points), Manipur (24 percentage points), Arunachal Pradesh (22 percentage points), and Dadra & Nagar Haveli (33 percentage points), whereas a decline of five or more percentage points was observed in Karnataka (9 percentage points), Jammu & Kashmir (8 percentage points), Tamil Nadu (19 percentage points), Punjab (9 percentage points), Mizoram (55 percentage points) and Tripura (8 percentage points).

100.

0

100.

0

150.

0

100.

0

83.3

150.

0

83.3

42.9

200.

0

133.

3

125.

0

100.

0

100.

0

100.

0

66.7

57.1

0.0

50.0

100.0

150.0

200.0

250.0

Sikkim Arunachal Pradesh

Nagaland Goa Meghalaya Mizoram Manipur Tripura

Func

tiona

l FRU

s as

aga

inst

requ

ired

num

ber (

%)

Source: State Report & MoHFWBase Year (2014-15) Reference Year (2015-16)

61

Note: The number of required 24x7 PHCs is based on MoHFW guidelines.

Figure 4.53 - Indicator 3.1.3.b: Proportion of functional 24x7 PHCs - Larger States

Note: The number of required 24x7 PHCs is based on MoHFW guidelines.

Figure 4.54 - Indicator 3.1.3.b: Proportion of functional 24x7 PHCs - Smaller States

Indicator 3.1.4: Proportion of districts with functional Cardiac Care Units (CCUs)

A functioning CCU is important for the availability of specialized cardiac care services at the district level and for reducing the workload at tertiary level facilities. The State-provided data on the number of functional CCUs in district hospitals alongside the total number of districts was considered. However, CCUs in medical colleges were not considered for this indicator, except for Delhi where hospitals are not designated as district hospitals.

169.

6

73.6

70.9

78.1

67.3

58.4

56.4

48.0

53.6

36.5

54.2

33.0

27.8

30.0

33.2

27.0

35.7

17.9

5.7

5.8

0.0

176.

9

77.6

73.6

69.2

68.0

56.5

54.5

46.7

45.6

40.4

35.0

33.0

31.5

30.0

29.2

27.0

26.4

17.4

5.9

5.8

0.0

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

200.0 Fu

nctio

nal 2

4x7

PHCs

as

aga

inst

requ

ired

num

ber (

%)

Source: State Report & MoHFWBase Year (2014-15) Reference Year (2015-16)

Assam

Haryan

aBiha

r

Karnata

ka

Rajasth

an

Madhy

a Prad

esh

Uttarak

hand

Mahara

shtra

Jammu &

Kashm

ir

Chhatt

isgarh

Tamil N

adu

Jhark

hand

Gujarat

Odisha

Andhra

Prades

h

Telan

gana

Punjab

Uttar P

rades

h

West B

enga

l

Himac

hal P

rades

hKera

la

166.

7

166.

7

165.

0 190.

9

124.

3

41.4

21.4

0.0

216.

7

180.

0

165.

0

136.

4

116.

2

65.5

42.9

6.7

0.0

50.0

100.0

150.0

200.0

250.0

Sikkim Meghalaya Nagaland Mizoram Tripura Manipur Arunachal Pradesh

Goa

Func

tiona

l 24x

7 PH

Cs

as a

gain

st re

quire

d nu

mbe

r (%

)

Source: State Report & MoHFW


62

Figure 4.55 - Indicator 3.1.4: Proportion of districts with functional Cardiac Care Units - Larger States

Assam, Bihar, Jharkhand, Telangana, Uttar Pradesh, Uttarakhand, Arunachal Pradesh, Goa, Manipur, Meghalaya, Sikkim, Tripura, Andaman & Nicobar, Chandigarh, Dadra & Nagar Haveli and Daman & Diu do not have a single district with functional CCUs in public hospitals. Himachal Pradesh, West Bengal, Rajasthan, Kerala, Punjab, Tamil Nadu, Andhra Pradesh, Lakshadweep and Delhi have made satisfactory progress by establishing CCUs in 50 percent or more districts. The remaining States need to operationalize CCUs, given the increasing load of cardiovascular diseases. Among UTs, only Delhi and Lakshadweep have the required number of CCUs. From base to reference year, notable increases in the percentage of districts with CCUs was observed in Rajasthan (68 percentage points), Jammu & Kashmir (9 percentage points) and Nagaland (9 percentage points), whereas a decline of 9 percentage points was observed in Gujarat.

Indicator 3.1.5: Proportion of ANC registered within first trimester against total registrations

The ANC registration in the first trimester is a critical indicator depicting the effectiveness of a health service delivery system to enrol pregnant women in early pregnancy, this being necessary for maternal and foetal well-being. Among the 21 Larger States, 11 have more than 70 percent of ANCs registered in the first trimester. Telangana, Bihar, Jammu & Kashmir, Uttar Pradesh and Jharkhand, with less than 60 percent ANC registration in the first trimester, need to improve performance in this regard. Almost all States (except Karnataka, Telangana, Jammu & Kashmir and Uttar Pradesh) have shown incremental progress in the registration of ANCs in the first trimester.

91.7

76.9

2.9

64.3

63.6

56.3

53.9

57.7

43.3

18.2

22.9

19.1

9.8

3.7

3.3

0.0

0.0

0.0

0.0

0.0

0.0

91.7

76.9

70.6

64.3

63.6

56.3

53.9

48.5

43.3

27.3

22.9

19.1

9.8

3.7

3.3

0.0

0.0

0.0

0.0

0.0

0.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Dist

ricts

with

func

tiona

l CCU

s (%

)


Himac

hal P

rades

h

West B

enga

l

Rajasth

anKera

la

Punjab

Tamil N

adu

Andhra

Prades

h

Karnata

ka

Gujarat

Jammu &

Kashm

ir

Mahara

shtra

Haryan

a

Chhatt

isgarh

Assam

Bihar

Jhark

hand

Telan

gana

Uttar P

rades

h

Uttarak

hand

Madhy

a Prad

esh

Odisha


63

Figure 4.56 - Indicator 3.1.5: Proportion of ANC registered within first trimester against total registrations - Larger States

Figure 4.57 - Indicator 3.1.5: Proportion of ANC registered within first trimester against total registrations - Smaller States and UTs

Similarly, among the Smaller States, Sikkim (80 percent) and Mizoram (74 percent) have achieved more than 70 percent first trimester registration and the remaining States need to put in special efforts to increase first trimester registrations. From base to reference year, some incremental progress (1 to 8 percentage points) was observed in Sikkim, Mizoram, Manipur and Goa, whereas some decline was observed in Tripura (1 percentage point), Arunachal Pradesh (2 percentage points), Nagaland (11 percentage points). No change was observed in Meghalaya where the first trimester registration remains at 32 percent. Among UTs, Dadra & Nagar Haveli, Andaman & Nicobar, and Lakshadweep have achieved satisfactory performance levels (ranging between 73 to 85 percent), while the remaining UTs need to significantly improve their performance.

51.4

51.2

33.7

92.7

78.6

81.0

77.2

73.0

68.5

73.6

60.0

64.4

71.2

72.8

63.6

61.5

59.1

57.7

58.5

61.3

54.4

94.4

81.4

80.6

80.6

77.0

75.8

74.9

74.6

74.4

73.0

71.2

66.8

63.8

62.5

62.2

60.7

55.9

55.5

53.0

48.7

36.4

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0 AN

C re

gist

ered

with

in 1

st tr

imes

ter a

gain

st to

tal r

egis

tratio

ns (%

)

Source: HMISBase Year (2014-15) Reference Year (2015-16)

Tamil N

adu

Himac

hal P

rades

hKera

laAssa

m

West B

enga

l

Odisha

Gujarat

Chhatt

isgarh

Andhra

Prades

hPun

jab

Karnata

ka

Mahara

shtra

Madhy

a Prad

esh

Uttarak

hand

Haryan

a

Rajasth

an

Telan

gana

Bihar

Jammu &

Kashm

ir

Uttar P

rades

h

Jhark

hand

77.8

72.3

59.1

62.8

57.0

38.7

46.8

32.2

79.9

73.6

63.2

61.9

58.7

37.0

35.8

32.1

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0

ANC

regi

ster

ed w

ithin

1st

trim

este

r aga

inst

to

tal r

egis

tratio

ns (%

)

ANC

regi

ster

ed w

ithin

1st

trim

este

r aga

inst

to

tal r

egis

tratio

ns (%

)

47.3

77.8

74.9

47.3

45.5

49.6

34.7

84.8

76.9

73.2

49.3

39.5

36.8

33.7

Source: HMISSource: HMIS



Sikkim

Mizoram

Manipu

r

Tripu

ra Goa

Arunac

hal P

rades

h

Nagala

nd

Megha

laya

Dadra

& Nagar

Haveli

Andam

an & Nico

bar

Laksh

adwee

p

Daman

& Diu

Puduc

herry

Chand

igarh

Delhi

64

Figure 4.58 - Indicator 3.1.6: Level of registration of births - Larger States

Indicator 3.1.6: Level of registration of births

Registration of birth not only provides the child with an official identification document, but also allows for area-specific estimation of birth rates. The level of registration is defined as the proportion of births registered under the Civil Registration System (CRS) against the estimated number of births during a specific year. Seventeen States/ UTs including Andhra Pradesh, Assam, Chhattisgarh, Haryana, Kerala, Maharashtra, Punjab, Tamil Nadu, Arunachal Pradesh, Goa, Manipur, Meghalaya, Mizoram, Nagaland, Chandigarh, Puducherry and Delhi have achieved 100 percent registration of births. However, Uttarakhand, Madhya Pradesh, Jharkhand, Jammu & Kashmir, Uttar Pradesh, Bihar, Tripura, Sikkim, Daman & Diu, Andaman & Nicobar, Dadra & Nagar Haveli and Lakshadweep, (with level of registration in the range of 60 to 86 percent) need to make rapid progress in this regard. From base to reference year, the States and UTs showing a decline in registration are Telangana (4 percentage points), Gujarat (5 percentage points), Himachal Pradesh (7 percentage points), Tripura (9 percentage points), Sikkim (6 percentage points), Daman and Diu (22 percentage points), Andaman and Nicobar (25 percentage points) and Dadra and Nagar Haveli (7 percentage points). The states with 5 percentage points or more increase in birth registration are Chhattisgarh (12 percentage points), Odisha (5 percentage points), Uttarakhand (9 percentage points) and Bihar (7 percentage points).

98.5

97.7

87.8

100.

0

100.

0

100.

0

100.

0

100.

0

93.9

98.4

96.0

100.

0

100.

0

100.

0

92.8

76.6

84.1

77.7

71.8

68.6

57.4

100.

0

100.

0

100.

0

100.

0

100.

0

100.

0

100.

0

100.

0

98.5

98.2

97.8

95.6

95.0

93.1

92.5

86.0

82.6

82.0

75.5

68.3

64.2

0.0

20.0

40.0

60.0

80.0

100.0

120.0

Leve

l of r

egis

tratio

n of

birt

hs (%

)

Source: CRS

Andhra

Prades

hAssa

m

Chhatt

isgarh

Haryan

aKera

la

Mahara

shtra

Punjab

Tamil N

adu

Odisha

Rajasth

an

Karnata

ka

Telan

gana

Gujarat

Himac

hal P

rades

h

West B

enga

l

Uttarak

hand

Madhy

a Prad

esh

Jhark

hand

Jammu &

Kashm

ir

Uttar P

rades

hBiha

r


65

Figure 4.59 - Indicator 3.1.6: Level of registration of births - Smaller States and UTs

Indicator 3.1.7: Completeness of Integrated Disease Surveillance Programme (IDSP) reporting of P and L forms

This indicator captures the proportion of Reporting Units (RUs) reporting in the stipulated time for IDSP reporting format for presumptive surveillance (P form) and IDSP reporting format for laboratory surveillance (L form) during a specific year and is an important monitoring indicator reflecting the functioning of IDSP.

Seven of the Larger States (Andhra Pradesh, Telangana, Kerala, Gujarat, Karnataka, Uttarakhand and Tamil Nadu) have at least 90 percent of the reporting units submitting P form in a timely manner. The performance of Himachal Pradesh and Uttar Pradesh is poor wherein only 66 percent and 42 percent units, respectively,report in a timely manner. From base to reference year, there has been a decline in the percentage of reporting units in Assam, Haryana, Madhya Pradesh, Punjab and Uttar Pradesh, whereas reporting has increased in the remaining States, Karnataka, Tamil Nadu, Odisha, Jammu & Kashmir, West Bengal, Rajasthan and Himachal Pradesh where the increase was more than 10 percentage points. Among the Smaller States and UTs, all (except Mizoram, Dadra & Nagar Haveli, Chandigarh and Daman & Diu) had incremental progress. Manipur (63 percent), Mizoram (48 percent), Andaman & Nicobar (50 percent), Lakshadweep (0 percent) and Delhi (56 percent) need to take corrective steps to improve the reporting completeness of P form.

100.

0

100.

0

100.

0

100.

0

100.

0

100.

0

91.4

79.9

100.

0

100.

0

100.

0

100.

0

100.

0

100.

0

81.7

74.1

0.0 20.0 40.0 60.0 80.0

100.0 120.0

Leve

l of r

egis

tratio

n of

birt

hs (%

)

100.

0

100.

0

100.

0

98.4

97.2

71.8

60.0

100.

0

100.

0

100.

0

76.4

71.9

65.1

59.5

0.0

20.0

40.0

60.0

80.0

100.0

120.0

Leve

l of r

egis

tratio

n of

birt

hs (%

)

Source: CRSSource: CRS


Arunac

hal P

rades

hGoa

Manipu

r

Megha

laya

Mizoram

Nagala

nd

Tripu

raSikk

im

Chand

igarh

Puduc

herry Delh

i

Daman

& Diu

Andam

an & Nico

bar

Dadra

& Nagar

Haveli

Laksh

adwee

p

Base Year (2013) Reference Year (2014) Base Year (2013) Reference Year (2014)

66

Figure 4.60 - Indicator 3.1.7: Completeness of IDSP reporting of P form - Larger States

Figure 4.61 - Indicator 3.1.7: Completeness of IDSP reporting of P and L forms - Smaller States

The status of L form reporting is similar to the P form reporting. Thus, Rajasthan (68 percent), Himachal Pradesh (62 percent), Uttar Pradesh (57 percent), Manipur (38 percent), Mizoram (58 percent), Andaman & Nicobar (21 percent) and Lakshadweep (0 percent) need to make concerted efforts to raise the percentage of reporting units timely L form reporting.

94 94 94 96

82 88

70

92

83 77

89

66 66

81

71 65

69

77

59

41

64

99 97 96 95 95 93 90 88 88

84 84 83 80 80 79 78

73 73 73

66

42

0

20

40

60

80

100

Source: Central IDSP, MoHFW

Com

plet

enes

s of

IDSP

repo

rting

of P

form

(%)


Andhra

Prades

h

Telan

gana

Kerala

Gujarat

Karnata

ka

Uttarak

hand

Tamil N

adu

Assam

Bihar

Chhatt

isgarh

Haryan

aOdis

ha

Jammu &

Kashm

ir

Madhy

a Prad

esh

Mahara

shtra

West B

enga

l

Jhark

hand

Punjab

Rajasth

an

Himac

hal P

rades

h

Uttar P

rades

h

91

75

62

43

65 80

35 51

97

97

84

82

79

79

63

48

0 20 40 60 80

100 120

86

61 67

63

33

61 74

32

100

94

88

82

77

65

58

38

0 20 40 60 80

100 120

Source: Central IDSP, MoHFW

Sikkim

Tripu

ra

Megha

laya

Arunac

hal P

rades

hGoa

Nagala

nd

Manipu

r

Mizoram

Sikkim

Tripu

raGoa

Megha

laya

Arunac

hal P

rades

h

Nagala

nd

Mizoram

Manipu

r

Base Year (2014) Reference Year (2015) Base Year (2014) Reference Year (2015)

Com

plet

enes

s of

IDSP

repo

rting

of P

form

(%)

Com

plet

enes

s of

IDSP

repo

rting

of L

form

(%)

P form (%) L form (%)

67

Figure 4.62 - Indicator 3.1.8: Proportion of CHCs with grading above 3 points - Larger States

Indicator 3.1.8: Proportion of CHCs with grading above 3 points

CHCs are graded under the MoHFW’s grading system using the data on service utilization, client orientation, service availability, drugs and supplies, human resource and infrastructure. This indicator represents the share of CHCs that receive a score greater than 3 (out of 5 points) of the total number of CHCs in that State.

Larger States have made substantial incremental progress in increasing the proportion of CHCs with a score of more than 3 points. This, however, could be due to a reporting issue. The grading system was first introduced in 2014-15 (base year), and reporting has improved significantly in 2015-16 (reference year). Many of the Smaller States and UTs (Arunachal Pradesh, Mizoram, Nagaland, Sikkim, Tripura, Andaman and Nicobar, Dadra and Nagar Haveli, Daman and Diu, Delhi and Lakshadweep) are yet to report on this indicator.

Indicator 3.1.9: Proportion of public health facilities with accreditation certificates by a standard quality assurance program (NQAS/ NABH/ ISO/ AHPI)

To ensure a high quality of health services, the Government of India encourages public health facilities across States to apply for quality assurance programs such as National Quality Assurance Standards (NQAS), National Accreditation Board for Hospitals and Healthcare Providers (NABH), International Organization for Standardization (ISO), and Association of Healthcare Providers (India) (AHPI). The performance of health facilities is assessed against pre-determined standards. Only a few States, namely Bihar, Kerala, Odisha, Tamil Nadu, Arunachal Pradesh, Manipur, and Delhi have initiated accreditation under the standard quality assurance program, but less than 15 percent facilities have been accredited under such programs by any State.

NA

7.1 9.

0

3.2

1.6 3.

5

10.3

3.2 4.5

16.7

1.0

25.3

4.6

12.0

9.8

10.1

0.0

0.0 1.7 2.5

NA

76.1

61.9

57.2

54.5

54.4

53.7

49.4

47.7

44.1

38.5

37.2

31.3

31.1

26.7

22.8

22.0

20.3

11.

6

8.3

5.1

0.4

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

CHCs

with

gra

ding

abo

ve 3

poi

nts

(%)

Source: HMIS

Tamil N

adu

Jammu &

Kashm

ir

Madhy

a Prad

esh

Rajasth

an

Jhark

hand

West B

enga

l

Gujarat

Chhatt

isgarh

Uttar P

rades

h

Mahara

shtra

Andhra

Prades

h

Karnata

ka

Assam

Punjab

Odisha

Haryan

aBiha

r

Telan

gana

Uttarak

hand

Himac

hal P

rades

h Kera

la


68

Figure 4.63 - Indicator 3.1.10: Average number of days for transfer of Central NHM funds from State Treasury to implementation agency

(Department/ Society) based on all tranches of the last financial year - Larger States

Figure 4.64 - Indicator 3.1.10: Average number of days for transfer of Central NHM funds from State Treasury to implementation agency (Department/ Society)

based on all tranches of the last financial year - Smaller States and UTs

Indicator 3.1.10: Average number of days for transfer of Central National Health Mission (NHM) funds from State Treasury to implementation agency (Department/ Society) based on all tranches of the last financial year

This is an important indicator for assessing the system’s efficiency in timely flow of funds to the implementing agencies. The average number of days taken by the State to transfer money to the implementation agency ranged between 0 (Daman & Diu and Lakshadweep) and 287 (Telangana) days. The data came from records and analysis shared by the central NHM finance department of MoHFW. As shown in the graphs below, almost all States and UTs (except Daman & Diu and Lakshadweep) have lengthy delays in transfer of funds from the State Treasury to State health societies, thereby adversely affecting timely implementation of various NHM initiatives. There is a need to take urgent steps to reduce this delay. From base to reference year, Gujarat, Uttarakhand, Bihar, Himachal Pradesh, Rajasthan, West Bengal, Chhattisgarh, Maharashtra, Jharkhand and Punjab have shown good progress (reduction by 19 or more days), whereas delays have increased in Uttar Pradesh, Jammu & Kashmir, Kerala, Andhra Pradesh, Karnataka, Assam, Telangana and in all Smaller States (except Meghalaya and Tripura).

Source: Central NHM Finance Data

58

97

135

35

27

102

71

56 71

79

24

140

140

98

30

97

80 97

122

97

70

24

27 40

41

42

47

48

50

51

57

59

66

67 78 93

107

107 12

7 139

242

287

0

50

100

150

200

250

300

350

Aver

age

num

ber o

f day

s fo

r tra

nsfe

r o

f NHM

fund

s fro

m S

tate

Tre

asur

y

to im

plem

enta

tion

agen

cy


Gujarat

Uttarak

hand

Bihar

Madhy

a Prad

esh

Haryan

a

Himac

hal P

rades

h

Rajasth

an

Tamil N

adu

West B

enga

l

Chhatt

isgarh

Odisha

Mahara

shtra

Jhark

hand

Punjab

Uttar P

rades

h

Jammu &

Kashm

ir

Kerala

Andhra

Prades

h

Karnata

ka

Assam

Telan

gana

216

118

98

68

149

140

101

199

38

69

143 15

3

154 17

7

213

258

0

50

100

150

200

250

300

Av

erag

e nu

mbe

r of d

ays

for t

rans

fer o

f NHM

fund

s fro

m S

tate

Tre

asur

y to

impl

emen

tatio

n ag

ency

Aver

age

num

ber o

f day

s fo

r tra

nsfe

r of N

HM fu

nds

from

Sta

te T

reas

ury

to im

plem

enta

tion

agen

cy

76

143

68

101

64

147

92

0 0

35

55 62

78 89

0

20

40

60

80

100

120

140

160

Source: Central NHM Finance DataSource: Central NHM Finance Data


Megha

laya

Tripu

ra

Arunac

hal P

rades

h

Sikkim Goa

Mizoram

Nagala

nd

Manipu

r


Daman

& Diu

Laksh

adwee

p

Chand

igarh

Puduc

herry

Dadra

& Nagar

Haveli

Andam

an & Nico

bar

Delhi

69

Way Forward

70

5. Institutionalization – taking the Index ahead The composite Health Index has been prepared and disseminated as a first attempt to promote a

co-operative and competitive spirit among the States and UTs to rapidly bring about transformative action in achieving the desired health outcomes. The Health Index will be calculated and disseminated annually, with a focus on measuring and highlighting annual incremental improvements by the States and UTs. The MoHFW has underlined the importance of such an exercise to link the Index with incentives to States and UTs under the NHM. The Index is also a tool for States and UTs to identify problem areas and focus their interventions in these areas.

During the process of development of the Health Index, rich learnings have emerged which will guide the refining of the Index for the coming year. It is envisaged that a thorough review of indicators will be undertaken to include data on new thrust areas and addition of new data sources. The current methodology will also be reconsidered to address some of the limitations listed earlier.

The exercise calls for urgent improvement of the data system in health for timeliness, accuracy and relevance. The quality of HMIS and program-specific MIS data needs to be improved in terms of consistency between Center and State data, coverage of private sector data, data scrutiny, thrust area indicators and data definitions. The MIS also needs strengthening to provide appropriate denominators. For example, the HMIS captures the number of anemic women but does not provide data on the appropriate denominator (i.e. total number of women tested for anemia). Furthermore, the SRS needs to generate data in a timely manner and should explore the possibility of generating the data on key health outcomes including NMR, U5MR, TFR, MMR and SRB for all States and UTs. Data sourced at the State-level on key areas such as human resources and finances needs to be strengthened in terms of availability and its quality. Thus, in the successive rounds, continuous improvement of both the methods and the data will be undertaken to make the Index better.

71

ANNEXURES

72

Annexure 1: Discrepancies in data and resolution The data was finalized by the IVA after resolution of all discrepancies in consultation with State and

Central governments, who, after thorough review of the data and supporting documentation, identified gaps and data discrepancies which were then discussed with state nodal officers (SNOs) and State-level authorities. A State-specific validation report was prepared and shared with the Principal Secretaries, Mission Directors and SNOs highlighting the results of the validation exercise. The States were requested to review the validation report and provide feedback. Subsequently, the IVA also presented the validation results through five video conferences held during August 16-18, 2017, with groups of 7-8 States to share the findings and discuss discrepancies, data gaps, variations and deviations.

Specific issues encountered during validation were discussed with stakeholders (NITI Aayog, MoHFW, the World Bank, validation agency and subject experts) and the following decisions were taken:

• For States that have achieved replacement level of fertility (TFR≤2.1), it was decided to assign the weight of this indicator on a pro-rata basis to the remaining parameters in that sub-domain, i.e. key health outcomes.

• For service delivery indicators, such as ‘full immunization’, ‘institutional delivery’, ‘ANC registered within first trimester’, and ‘people living with HIV on antiretroviral therapy,’ in instances where percentages exceeded 100 percent, it was decided to cap them at 100 percent.

• For calculating the functionality of FRUs and 24x7 PHCs, the denominator was captured as the required number of FRUs and 24x7 PHCs as per MOHFW norms of one FRU per 500,000 population and one 24x7 PHC per 100,000 population.

• CHC grading for Dadra & Nagar Haveli (reference year), Kerala and Tamil Nadu (base year) was not available and the value against this indicator for that specific year was considered as not applicable (NA). The weight of the indicator was distributed among other indicators in that domain.

• In several States, the specified health worker positions were not sanctioned and/or overlapped with other functions. Lakshadweep for example, did not have a sanctioned position of a CMO or a Medical Superintendent. Therefore, for Lakshadweep this indicator was considered as NA. In Dadra & Nagar Haveli, the Director of Health was also in charge of the District Hospital and thus his tenure was considered for CMO as well. In Tripura and Himachal Pradesh, there were no designated specialist positions (with General Duty Medical Officers filling the positions of specialists), and hence the IVA accepted the NA entry submitted against the vacancy of specialist. In the case of Chandigarh, in place of sanctioned positions the required number of specialists was used for the denominator. Uttar Pradesh and Bihar did not share the total number of staff (regular and contractual) for Indicator 3.1.2 on HRMIS generated e-payslip and thus the IVA treated the entry as zero.

73

Domain Sub-domain Number of Weight Indicators

Health Outcomes Key Outcomes 07 700

Intermediate Outcomes 07 350

Governance and Health Monitoring and Data Integrity 01 70

Information Governance 02 60

Key Inputs/ Health Systems/Service Delivery 11 220Processes

TOTAL 28 1400

Table A.2.1 - Original Health Index indicators: A snapshot

Indicators Definition Data Source Remarks

DOMAIN 1 - HEALTH OUTCOMES

Sub-domain 1.1 - Key Outcomes (Weight – 700)

Still Birth Rate (SBR) Number of still births per thousand live SRS Excluded in births during a specific year. final Health Index

Neonatal Mortality Number of infant deaths of less than 29 SRS Rate (NMR) days per thousand live births during a specific year.

Under-five Mortality Number of child deaths of less than 5 SRSRate (U5MR) years per thousand live births during a specific year.

Maternal Mortality Number of maternal deaths from any cause SRS Excluded in final Ratio (MMR) related to or aggravated by pregnancy Health Index or its management during pregnancy, childbirth, or within 42 days of termination of pregnancy, per 100,000 live births during the specific period.

Total Fertility Rate Average number of children that would be SRS(TFR) born to a woman if she experiences the current fertility pattern throughout her reproductive span (15-49 years), during a specific year.

Proportion of Low Proportion of low birth weight (<=2.5 kg) HMISBirth Weight among newborns out of the total number ofnewborns newborns weighed during a specific year.

Sex Ratio at Birth (SRB) The number of girls born for every 1,000 SRS boys born during a specific year.

Sub-domain 1.2 - Intermediate Outcomes (Weight – 350)

Full immunization coverage Proportion of infants 9-11 months old who have received BCG, HMIS 3 doses of DPT, 3 doses of OPV and measles against estimated number of infants during a specific year.

Table A.2.2 - Original Health Index: Indicators, definitions and data sources

Annexure 2: Original Health Index At the launch of the Guidebook on Performance on Health Outcomes10 in December 2016, the Index

comprised 28 indicators. Table A.2.1 provides an overview of the original set of indicators. However, this Index was subsequently revised as described in Section 2, Table 2.3 and the revised Index has been used for the generation of ranks.

Based on issues related to availability and quality of data, certain indicators had to be excluded or modified from the original Index and the rationale for this is summarized at the end of the table.


Proportion of Proportion of deliveries conducted in HMISinstitutional deliveries public and private health facilities against the number of estimated deliveries during a specific year.

Proportion of Proportion of pregnant women aged 15-49 HMIS Excluded inpregnant women years who are anemic (<11.0 g/dl) against final Health aged 15-49 years total number of pregnant women registered Indexwho are anemic for ANC during a specific year.

Total case notification Number of new and relapsed TB cases RNTCP MIS Indicator source rate of tuberculosis notified (public + private) per 100, 000 modified as (TB) population during a specific year. ‘RNTCP MIS, MoHFW data’

Treatment success Proportion of new cured and their treatment RNTCP MIS Indicator source rate of new completed against the total number of new modified asmicrobiologically microbiologically confirmed TB cases ‘RNTCP MIS, confirmed TB cases registered during a specific year. MoHFW data’

Proportion of people Proportion of PLHIV receiving ART NACO State Excluded for living with HIV treatment against the number of Report the category(PLHIV) on estimated PLHIVs who needed ART of UTsantiretroviral therapy treatment for the specific year. (ART)

Out-of-pocket Average out-of-pocket expenditure (INR) Mother and Excluded inexpenditure on drugs on drugs and diagnostics incurred per Child final Index forand diagnostics delivery in public health facilities during Tracking incremental incurred per delivery a specific year. Facilitation ranking; in public health Centre Retained forfacilities (using (MCTFC) reference yearpregnant women as ranking onlyproxy to all patients)

DOMAIN 2 – GOVERNANCE AND INFORMATION

Sub-domain 2.1 – Health Monitoring and Data Integrity (Weight – 70)

Data Integrity Percentage deviation of reported data from HMIS andMeasure: standard survey data to assess the quality/ NFHS-4a. Institutional integrity of reported data for adeliveries specific period.b. ANC registered within first trimester


Average occupancy of Average occupancy of an officer (in State Reportan officer (in months), months), combined for following key combined for posts at State-level in last three years:following three key posts at State-level 1. Principal Secretary for last three years: 2. Mission Director (NHM) 1. Principal Secretary 3. Director (Health Services)2. Mission Director (NHM) 3. Director (Health Services)

Average occupancy of Average occupancy of a full time CMO State Report a full-time officer (in months) for all the districts in last(in months) for all three years. the districts in last three years - District Chief Medical Officers(CMOs) or equivalent post (heading District Health Services)

10 Performance on Health Outcomes, A Reference Guidebook, NITI Aayog, December 2016.

74


DOMAIN 1 - HEALTH OUTCOMES

Sub-domain 1.1 - Key Outcomes (Weight – 700)

Still Birth Rate (SBR) Number of still births per thousand live SRS Excluded in births during a specific year. final Health Index

Neonatal Mortality Number of infant deaths of less than 29 SRS Rate (NMR) days per thousand live births during a specific year.

Under-five Mortality Number of child deaths of less than 5 SRSRate (U5MR) years per thousand live births during a specific year.

Maternal Mortality Number of maternal deaths from any cause SRS Excluded in final Ratio (MMR) related to or aggravated by pregnancy Health Index or its management during pregnancy, childbirth, or within 42 days of termination of pregnancy, per 100,000 live births during the specific period.

Total Fertility Rate Average number of children that would be SRS(TFR) born to a woman if she experiences the current fertility pattern throughout her reproductive span (15-49 years), during a specific year.

Proportion of Low Proportion of low birth weight (<=2.5 kg) HMISBirth Weight among newborns out of the total number ofnewborns newborns weighed during a specific year.

Sex Ratio at Birth (SRB) The number of girls born for every 1,000 SRS boys born during a specific year.

Sub-domain 1.2 - Intermediate Outcomes (Weight – 350)

Full immunization coverage Proportion of infants 9-11 months old who have received BCG, HMIS 3 doses of DPT, 3 doses of OPV and measles against estimated number of infants during a specific year.


Proportion of Proportion of deliveries conducted in HMISinstitutional deliveries public and private health facilities against the number of estimated deliveries during a specific year.

Proportion of Proportion of pregnant women aged 15-49 HMIS Excluded inpregnant women years who are anemic (<11.0 g/dl) against final Health aged 15-49 years total number of pregnant women registered Indexwho are anemic for ANC during a specific year.

Total case notification Number of new and relapsed TB cases RNTCP MIS Indicator source rate of tuberculosis notified (public + private) per 100, 000 modified as (TB) population during a specific year. ‘RNTCP MIS, MoHFW data’

Treatment success Proportion of new cured and their treatment RNTCP MIS Indicator source rate of new completed against the total number of new modified asmicrobiologically microbiologically confirmed TB cases ‘RNTCP MIS, confirmed TB cases registered during a specific year. MoHFW data’

Proportion of people Proportion of PLHIV receiving ART NACO State Excluded for living with HIV treatment against the number of Report the category(PLHIV) on estimated PLHIVs who needed ART of UTsantiretroviral therapy treatment for the specific year. (ART)

Out-of-pocket Average out-of-pocket expenditure (INR) Mother and Excluded inexpenditure on drugs on drugs and diagnostics incurred per Child final Index forand diagnostics delivery in public health facilities during Tracking incremental incurred per delivery a specific year. Facilitation ranking; in public health Centre Retained forfacilities (using (MCTFC) reference yearpregnant women as ranking onlyproxy to all patients)

DOMAIN 2 – GOVERNANCE AND INFORMATION

Sub-domain 2.1 – Health Monitoring and Data Integrity (Weight – 70)

Data Integrity Percentage deviation of reported data from HMIS andMeasure: standard survey data to assess the quality/ NFHS-4a. Institutional integrity of reported data for adeliveries specific period.b. ANC registered within first trimester


Average occupancy of Average occupancy of an officer (in State Reportan officer (in months), months), combined for following key combined for posts at State-level in last three years:following three key posts at State-level 1. Principal Secretary for last three years: 2. Mission Director (NHM) 1. Principal Secretary 3. Director (Health Services)2. Mission Director (NHM) 3. Director (Health Services)

Average occupancy of Average occupancy of a full time CMO State Report a full-time officer (in months) for all the districts in last(in months) for all three years. the districts in last three years - District Chief Medical Officers(CMOs) or equivalent post (heading District Health Services)

75


DOMAIN 3 – KEY INPUTS/PROCESSES

Sub-domain 3.1 – Health Systems/Service Delivery (Weight – 220)

Proportion of vacant Vacant healthcare provider positions in State Reporthealth care provider public health facilities against total positions (regular + sanctioned health care provider positionscontractual) in public for following cadres (separately for eachhealth facilities cadre) during a specific year:

a. ANMs at sub-centres (SCs)

b. Staff nurse at Primary Health Centers (PHCs) and Community Health Centers (CHCs)

c. MOs at PHCs

d. Specialists at DH (Medicine, Surgery, Obstetrics and Gynaecology, Pediatrics, Anesthesia, Ophthalmology, Radiology, Pathology, ENT, Dental, Psychiatry)

Proportion of total Proportion of staff (regular + contractual)for whom an e-payslip State Report staff (regular + can be generated in the IT enabled HRMIS against totalcontractual) for whom number of staff (regular + contractual) during a specific year.an e-payslip can be generated in the IT enabled Human Resources Management Information System (HRMIS)

a. Proportion of Proportion of facilities of specified type HMIS Indicatorspecified type of conducting specified number of C-sections definitionfacilities functioning per year (FRUs) against total number of modifiedas First Referral specified type of facilities (CHCs, SDHs,Units (FRUs) DHs) during a specific year.

b. Proportion of Proportion of PHCs providing all stipulated MIS Report, Indicatorfunctional 24x7 healthcare services round the clock against MoHFW definitionPHCs total number of PHCs during a specific year. modified

Proportion of Proportion of districts with functional CCUs State Reportdistricts with [with desired equipment (ventilator,functional Cardiac monitor, defibrillator, CCU beds, portableCare Units (CCUs) ECG machine, pulse oxymeter etc.), drugs, diagnostics and desired staff as per programme guidelines] against total number of districts.

Proportion of ANC Proportion of pregnant women registered HMISregistered within for ANC within 12 weeks of pregnancyfirst trimester during a specific year.against total registrations

Level of registration Proportion of births registered under Civil CRS of births Registration System (CRS) against the estimated number of births during a specific year.

Completeness of IDSP Proportion of Reporting Units (RUs) IDSP Report Indicator sourcereporting of P and reporting in stipulated time period against modified asL forms total RUs, for P and L forms during a ‘Central IDSP, specific year. MoHFW data’

Proportion of CHCs Proportion of CHCs that are graded above HMISwith grading above 3 points against total number of CHCs3 points during a specific year.

Proportion of public Proportion of specified type of public health State Reporthealth facilities with facilities with accreditation certificates by aaccreditation standard quality assurance programcertificates by a against the total number of followingstandard quality specified type of facilities during aassurance program specific year.(NQAS/ NABH/ ISO/ 1. District hospital (DH)/ Sub-district hospital (SDH)AHPI) 2. CHC/ Block PHC

76

The estimates for SRS-related indicators such as NMR, U5MR, TFR, MMR and SRB in the Index were not available for Smaller States and UTs. Experts were consulted to generate estimates for these States and UTs from the SRS raw data obtained by NITI Aayog. However, it was decided that these estimates could not be generated due to the insufficient sample size. Further, in the Larger States category, MMR estimates were not available separately for eight states, which belonged previously to four undivided States, and also not available for Himachal Pradesh and Jammu & Kashmir. In the case of Still Birth Rate (SBR), the States as well as the IVA reported that data for this indicator was unreliable. In case of the indicator ‘proportion of pregnant women age 15-49 years who are anemic’, data on the appropriate denominator (i.e. total number of women tested for anemia) was not available in the HMIS. Besides, the indicator for ‘proportion of people living with HIV (PLHIV) on ART’ was excluded for the UTs category since no ART center was available in four UTs. For the indicator ‘proportion of NHM funds utilized by the end of 3rd quarter’, neither State nor central level data was found to be valid.

For the sake of uniformity and comparability across the States, central data was used for a few indicators such as ‘proportion of people living with HIV (PLHIV) on antiretroviral therapy (ART)’, ‘average number of days for transfer of central NHM funds from State Treasury to implementation agency’ and ‘completeness of IDSP reporting of P and L forms’. The NFHS-4 data for the indicator ‘out-of-pocket expenditure on drugs and diagnostics incurred per delivery in public health facilities’ was used in the reference year Index. However, for the base year, this data was not available and could therefore not be factored in for generating base year ranks or incremental ranks or drawing comparisons between the base and reference years.


Average number of Average time taken (in number of days) by State Report Indicator sourcedays for transfer of the State Treasury to transfer funds to modified as ‘Central NHM Central NHM funds implementation agencies during a Finance data’from State Treasury specific year. to implementation agency (Department/ Society) based on all tranches of the last financial year

Proportion of National Proportion of funds utilized against the State Report Excluded in finalHealth Mission (NHM) total funds allocated under NHM by the Health Indexfunds utilized by the end of 3rd quarter of specific year.end of 3rd quarter

77

Figure A.3.1 - Larger States: Ranking for reference year (2015-16) with and without the OOP expenditure indicator

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

Kerala 76.55

Punjab 65.21

Tamil Nadu 63.38

Gujarat 61.99

Himachal Pradesh 61.20

Maharashtra 61.07

Jammu & Kashmir 60.35

Andhra Pradesh 60.16

Karnataka 58.70

West Bengal 58.25

Telangana 55.39

Chhattisgarh 52.02

Haryana 46.97

Jharkhand 45.33

Uttarakhand 45.22

Assam 44.13

Madhya Pradesh 40.09

Odisha 39.43

Bihar 38.46

Rajasthan 36.79

Uttar Pradesh 33.69

73.77 Kerala

66.41 Punjab

64.23 Tamil Nadu

63.15 Gujarat

61.58 Himachal Pradesh

61.41 Andhra Pradesh

61.34 Maharashtra

60.16 Jammu & Kashmir

58.79 Karnataka

55.67 West Bengal

55.74 Telangana

54.08 Chhattisgarh

49.23 Haryana

47.69 Jharkhand

46.94 Uttarakhand

45.34 Assam

42.74 Madhya Pradesh

40.95 Bihar

40.15 Odisha

38.44 Rajasthan

36.23 Uttar Pradesh

Refe

renc

e Ye

ar R

anki

ng (E

xclu

ding

OOP

Indi

cato

r)

Refe

renc

e Ye

ar R

anki

ng (i

nclu

ding

OOP

Indi

cato

r)

Annexure 3: Reference Year Index (with and without the indicator on out-of-pocket expenditure) As described in the background section, the OOP expenditure data was available only for 2015-16 and

hence was used to calculate the reference year Index and rank independently. Overall, the inclusion of the OOP expenditure indicator in the Index score calculations does not substantially change the rankings (Figure A.3.1). The only exceptions are Andhra Pradesh and Bihar which, after the inclusion of OOP expenditure, move up by two and one positions, respectively; while Maharashtra, Jammu & Kashmir, and Odisha move down by one position in the ranking.

Without OOP expenditure With OOP expenditure

Note: Lines depict changes in composite Index score rank. The composite Index score is presented in the circle.

78

Figure A.3.2 - Smaller States: Ranking for reference year (2015-16) with and without OOP expenditure indicator

Mizoram 73.70

Manipur 57.78

Meghalaya 56.83

Sikkim 53.20

Goa 53.13

Arunachal Pradesh 49.51

Tripura 43.51

Nagaland 37.38

73.86 Mizoram

59.44 Meghalaya

56.41 Sikkim

54.24 Goa

53.82 Manipur

49.38 Arunachal Pradesh

45.66 Tripura

38.66 Nagaland

1

2

3

4

5

6

7

8

1

2

3

4

5

6

7

8

Refe

renc

e Ye

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anki

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xclu

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OOP

indi

cato

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Refe

renc

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OOP

indi

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For the Smaller States, the inclusion of OOP expenditure in the Health Index results in some changes in the rankings (Figure A.3.2), whereby Meghalaya, Sikkim, and Goa move up by one position, while Manipur falls by three positions (from second to fifth place).

The inclusion of the OOP expenditure indicator in calculation of the Health Index results in some changes in the reference year ranking among the UTs (Figure A.3.3). Notably, Andaman & Nicobar and Puducherry move up by one position in the ranking, while Delhi moves down by two positions. The inclusion of OOP expenditure does not affect the rankings of the other UTs.



Figure A.3.3 - Union Territories: Ranking for reference year (2015-16) with and without OOP expenditure indicator



Refe

renc

e Ye

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anki

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xclu

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OOP

indi

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1

2

3

4

5

6

7

1

2

3

4

5

6

7

Lakshadweep 65.79

Chandigarh 52.27

Delhi 50.02

Andaman & Nicobar 50.00

Puducherry 47.48

Daman & Diu 36.10

Dadra & Nagar Haveli 34.64

64.64 Lakshadweep

54.10 Chandigarh

52.98 Andaman & Nicobar

49.98 Puducherry

46.35 Delhi

39.81 Daman & Diu

39.45 Dadra & Nagar Haveli

Refe

renc

e Ye

ar R

anki

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nclu

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OOP

indi

cato

r)

79

Annexure 4: Snapshot: State-wise performance on indicators Section 4 of the report on ‘Unveiling performance - encouraging actions’, provided insights about the

State-wise overall, incremental and domain-specific performance. This Annexure presents a quick snapshot of State-wise performance on all indicators included in the Index. This can help the States to easily identify specific areas requiring attention. The tables present data for base year (BY) and reference year (RY) of each indicator for all States. The direction as well as the magnitude of incremental change in the value of indicators from the base year to reference year is depicted by categorization (‘most improved’, ‘improved’, ‘no change’, ‘deteriorated’, ‘most deteriorated’, ‘not applicable’) and is visually identifiable by appropriate color coding.

1. Incremental change in performance for an indicator is calculated by subtracting base year value from reference year value. For indicators, such as NMR, U5MR, and vacancies, a negative change from base to reference year denotes improvement, while a positive change denotes deterioration. In the case of indicators such as those that reflect service coverage, a positive change denotes improvement, while a negative change denotes deterioration. The range of improvement is calculated by subtracting the minimum value of change from the maximum value of change. This range is then divided into two equal parts and the half towards maximum value of change is termed as 'most improved' and the half towards the minimum value of change is termed as ‘improved’.

2. Similarly, the range of deterioration is calculated by subtracting the minimum value of change from the maximum value of change. This range is then divided into two equal parts and the half towards maximum value of change is termed as 'deteriorated' and the other half towards minimum value of change is termed as 'most deteriorated' respectively. If the indicator value is stagnant and there has been no incremental change from base to reference year, the indicator is labeled as ‘no change’.

3. For a State, the incremental performance on an indicator is classified as ‘not applicable’ (NA) in instances such as: (i) If State has achieved TFR <= 2.1 in both base and reference years; (ii) Data Integrity Measure indicator wherein the same data has been used for base year and reference year due to overlapping periods of NFHS-4; (iii) Service coverage indicators with 100 percent values in both base and reference years; (iv) The data value for a particular indicator is NA in base year or reference year or both.

80

Table A.4.1 - Larger States: Health Outcomes domain indicators, base and reference years

States

1.1.1 NMR (per '000 live

births)

1.1.2 U5MR (per '000 live

births) 1.1.3 TFR*

1.1.4 LBW (percentage)

1.1.5 SRB (no. of girls

born for every 1,000 boys

born) BY RY BY RY BY RY BY RY BY RY

Andhra Pradesh 26 24 40 39 1.8 1.7 5.62 6.73 919 918

Assam 26 25 66 62 2.3 2.3 18.19 16.68 918 900

Bihar 27 28 53 48 3.2 3.2 6.70 7.22 907 916

Chhattisgarh 28 27 49 48 2.6 2.5 11.61 12.15 973 961

Gujarat 24 23 41 39 2.3 2.2 10.58 10.51 907 854

Haryana 23 24 40 43 2.3 2.2 14.61 14.90 866 831 Himachal Pradesh 25 19 36 33 1.7 1.7 8.66 12.63 938 924

Jammu & Kashmir 26 20 35 28 1.7 1.6 6.33 5.93 899 899

Jharkhand 25 23 44 39 2.8 2.7 7.81 7.42 910 902

Karnataka 20 19 31 31 1.8 1.8 10.76 11.49 950 939

Kerala 6 6 13 13 1.9 1.8 10.81 11.72 974 967

Madhya Pradesh 35 34 65 62 2.8 2.8 14.16 14.10 927 919

Maharashtra 16 15 23 24 1.8 1.8 14.57 13.74 896 878

Odisha 36 35 60 56 2.1 2.0 20.10 19.16 953 950

Punjab 14 13 27 27 1.7 1.7 5.95 6.88 870 889

Rajasthan 32 30 51 50 2.8 2.7 27.43 25.51 893 861

Tamil Nadu 14 14 21 20 1.7 1.6 10.46 13.03 921 911

Telangana 25 23 37 34 1.8 1.8 6.11 5.70 919 918

Uttar Pradesh 32 31 57 51 3.2 3.1 11.74 9.60 869 879

Uttarakhand 26 28 36 38 2.0 2.0 7.77 7.26 871 844

West Bengal 19 18 30 30 1.6 1.6 15.48 16.45 952 951


**The data shown in grey color is for ‘not applicable’ category wherein the States with TFR <= 2.1 (replacement level fertility) in both base and reference years are not considered for incremental change.

81

#Data for this indicator is available and used only for reference year and hence this indicator comes under ‘not applicable’ category.

Table A.4.1 (Continued) - Larger States: Health Outcomes domain indicators, base and reference years

States

1.2.1 Full immunization (percentage)

1.2.2 Institutional deliveries

(percentage)

1.2.3 TB case notification

100,000

population)

1.2.4 TB

(percentage)

1.2.5 PLHIV on ART

(percentage)

1.2.6 OOP expenditure

(in INR)#

BY RY BY RY BY RY BY RY BY RY RY

Andhra Pradesh 97.58 91.62 53.09 87.08 136 145 90.40 88.50 72.39 76.11 2138

Assam 84.10 88.00 72.70 74.25 122 123 85.40 86.20 58.94 64.58 3210

Bihar 82.10 89.73 52.96 57.10 72 84 89.00 89.70 30.73 37.18 1724

Chhattisgarh 85.81 90.53 59.64 64.51 128 138 88.20 89.10 47.20 53.06 1480

Gujarat 90.26 90.55 90.83 97.78 170 193 88.50 88.90 50.23 52.43 2136

Haryana 82.54 83.47 80.76 80.25 165 172 86.00 87.50 52.31 51.53 1503

Himachal Pradesh 94.90 95.22 67.50 67.49 210 207 89.70 89.60 79.22 79.89 3329

89.80 100.00 81.45 80.51 74 72 87.60 88.30 88.72 96.41 4192

Jharkhand 80.82 88.10 60.52 67.36 100 108 89.80 90.90 36.07 39.40 1476

Karnataka 92.30 96.24 77.12 78.78 100 105 83.30 84.70 83.25 88.68 3893

Kerala 95.50 94.61 95.99 92.62 87 139 86.00 87.50 61.79 66.72 6901

Madhya Pradesh 74.26 74.78 63.07 64.79 143 164 89.70 90.30 53.04 61.01 1387

Maharashtra 98.55 98.22 89.19 85.30 155 164 83.90 84.20 83.46 87.71 3487

Odisha 88.03 85.32 74.76 73.49 106 99 87.40 88.90 28.33 32.95 4225

Punjab 96.08 99.64 83.23 82.33 137 136 86.90 87.20 77.22 84.62 1890

Rajasthan 78.95 78.06 74.67 73.85 139 143 90.40 90.30 42.44 46.41 3052

Tamil Nadu 85.54 82.66 85.97 81.82 113 125 82.30 85.40 81.93 87.06 2496

Telangana 100.00 89.09 59.15 85.35 113 123 90.00 89.60 72.39 76.11 4020

Uttar Pradesh 82.88 84.82 43.55 52.38 123 137 88.20 87.50 51.30 57.81 1956

Uttarakhand 91.77 99.30 64.32 62.63 145 138 85.50 86.00 62.67 65.25 2399

West Bengal 100.00 95.85 79.92 81.28 93 93 86.40 86.50 31.00 35.92 7782


Jammu & Kashmir

rate(per

treatment success rate

States

2.1.1.a Data Integrity: Institutional deliveries

(percentage)

2.1.1.b Data Integrity: First trimester ANC

registration (percentage)

2.2.1 Average occupancy: State-level 3 key posts

(in months)

2.2.2 Average occupancy: CMOs

(in months)

BY** RY BY** RY BY RY BY RY

Andhra Pradesh 23.53 23.53 15.42 15.42 17.70 17.51 12.80 13.22

Assam 0.25 0.25 21.16 21.16 10.17 12.11 7.92 7.95

Bihar 18.21 18.21 16.33 16.33 15.00 13.01 17.62 11.88

Chhattisgarh 22.34 22.34 25.90 25.90 11.39 11.40 21.88 25.40

Gujarat 0.68 0.68 2.06 2.06 20.22 20.71 18.68 18.09

Haryana 4.62 4.62 19.08 19.08 13.80 11.21 13.43 12.56

Himachal Pradesh 12.72 12.72 7.30 7.30 11.38 12.39 13.86 10.50

12.42 12.42 13.50 13.50 22.80 13.81 11.72 11.77

Jharkhand 7.95 7.95 53.48 53.48 12.98 12.00 11.19 11.46

Karnataka 21.22 21.22 8.20 8.20 6.85 6.49 14.83 13.23

Kerala 3.71 3.71 24.86 24.86 21.84 12.02 16.47 11.72

Madhya Pradesh 23.09 23.09 9.19 9.19 10.75 16.00 18.14 17.62

Maharashtra 1.16 1.16 5.61 5.61 10.86 15.74 12.25 15.64

Odisha 13.82 13.82 22.09 22.09 11.07 12.01 9.97 13.95

Punjab 12.41 12.41 9.97 9.97 20.00 20.42 9.12 10.19

Rajasthan 12.44 12.44 18.43 18.43 19.00 22.02 12.26 11.94

Tamil Nadu 10.92 10.92 22.75 22.75 11.94 16.51 6.85 7.29

Telangana 21.06 21.06 15.80 15.80 8.71 7.81 11.72 11.19

Uttar Pradesh 36.59 36.59 0.92 0.92 9.62 19.64 11.57 14.15

Uttarakhand 14.93 14.93 10.77 10.77 10.65 10.35 11.63 13.93

West Bengal 2.12 2.12 42.44 42.44 22.00 28.02 10.29 14.10


Jammu &Kashmir

82

** Same data has been used for base and reference years due to overlapping periods of NFHS-4. Hence this indicator comes under ‘not applicable’ category.

Table A.4.2 - Larger States: Governance and Information domain indicators, base and reference years

83

States

3.1.1.a Vacancy: ANMs

at SCs (percentage)

3.1.1.b Vacancy: SNs at PHCs and CHCs

(percentage)

3.1.1.c Vacancy: MOs

at PHCs (percentage)

3.1.1.d Vacancy:

Specialists at DHs

(percentage)

3.1.2 E-payslip (percentage)

BY RY BY RY BY RY BY RY BY RY

Andhra Pradesh 20.56 15.67 17.33 20.48 17.97 12.76 40.55 30.41 59.60 58.65

Assam 10.93 8.99 4.57 8.95 19.92 17.77 62.91 41.72 0.00 0.00

Bihar 67.86 59.30 86.15 50.28 63.60 63.60 64.96 60.58 0.00 0.00

Chhattisgarh 12.35 9.23 44.27 37.28 41.83 45.02 77.98 77.68 0.00 0.00

Gujarat 17.13 28.08 37.71 36.46 39.78 32.03 51.02 55.50 35.60 35.61

Haryana 9.66 15.23 45.95 43.24 38.64 25.35 0.00 0.00 0.00 0.00

Himachal Pradesh 12.57 9.87 21.51 27.19 16.19 21.73 NA NA 3.32 8.07

Jammu & Kashmir 17.65 10.28 42.88 27.48 34.92 30.15 24.52 22.22 0.00 0.00

Jharkhand 19.57 19.73 71.80 74.94 45.29 48.67 55.37 50.32 0.00 0.00

Karnataka 27.85 22.59 45.20 25.97 13.35 11.48 20.90 21.53 48.89 49.35

Kerala 4.88 4.49 5.54 5.30 5.59 5.86 22.15 21.48 88.61 100.00

Madhya Pradesh 8.58 14.23 36.45 33.50 57.81 58.34 50.56 50.98 0.00 0.00

Maharashtra 8.25 9.46 16.74 15.67 16.82 16.96 19.47 30.34 66.55 67.60

Odisha 0.00 0.00 0.00 0.00 23.17 26.91 43.53 19.04 75.79 75.79

Punjab 7.17 8.48 36.22 33.98 9.83 7.77 21.74 47.72 0.00 0.00

Rajasthan 36.12 19.24 48.12 47.26 14.93 14.86 41.47 45.77 0.00 0.00

Tamil Nadu 11.82 15.97 21.78 19.09 7.56 7.58 17.86 16.73 84.62 84.72

Telangana 20.20 18.01 12.79 12.79 22.31 22.31 59.83 54.81 0.00 0.00

Uttar Pradesh 14.06 0.00 1.89 1.89 36.83 26.73 35.74 32.41 0.00 0.00

Uttarakhand 15.47 16.88 13.11 20.02 37.16 12.19 38.30 60.33 0.00 0.00

West Bengal 2.16 0.77 25.72 9.70 48.43 41.23 22.97 20.18 81.78 81.23


Table A.4.3 - Larger States: Key Inputs/Processes domain indicators, base and reference years

84

States

3.1.3.a Functional FRUs

(percentage)

3.1.3.b Functional 24x7

PHCs (percentage)

3.1.4 Districts with functional

CCUs (percentage)

3.1.5 Proportion of first trimester

ANC (percentage)

3.1.6 Level of birth



Andhra Pradesh 48.48 57.58 33.20 29.15 53.85 53.85 64.42 74.38 98.50 100.00

Assam 67.74 72.58 169.55 176.92 0.00 0.00 77.24 80.55 97.70 100.00

Bihar 12.50 11.54 70.89 73.58 0.00 0.00 51.43 55.47 57.40 64.20

Chhattisgarh 21.57 23.53 36.47 40.39 3.70 3.70 59.99 74.60 87.80 100.00

Gujarat 32.23 42.98 27.81 31.46 57.69 48.48 73.58 74.91 100.00 95.00

Haryana 52.94 50.98 73.62 77.56 19.05 19.05 57.68 62.20 100.00 100.00

Himachal Pradesh 107.14 121.43 5.80 5.80 91.67 91.67 78.62 81.39 100.00 93.10

Jammu & Kashmir 180.00 196.00 53.60 45.60 18.18 27.27 54.37 52.95 71.80 75.50

Jharkhand 15.15 22.73 33.03 33.03 0.00 0.00 33.67 36.36 77.70 82.00

Karnataka 105.74 116.39 78.07 69.23 43.33 43.33 72.82 71.22 96.00 97.80

Kerala 120.90 120.90 0.00 0.00 64.29 64.29 80.98 80.63 100.00 100.00

Madhya Pradesh 44.83 49.66 58.40 56.47 9.80 9.80 61.54 63.79 84.10 82.60

Maharashtra 31.11 32.44 48.04 46.71 22.86 22.86 63.58 66.82 100.00 100.00

Odisha 61.90 65.48 30.00 30.00 3.33 3.33 68.48 75.75 93.90 98.50

Punjab 138.18 141.82 35.74 26.35 63.64 63.64 71.16 73.01 100.00 100.00

Rajasthan 23.36 29.20 67.30 68.03 2.94 70.59 58.50 60.66 98.40 98.20

Tamil Nadu 129.17 122.92 54.23 34.95 56.25 56.25 92.72 94.35 100.00 100.00

Telangana 80.00 80.00 26.99 26.99 0.00 0.00 61.26 55.90 100.00 95.60

Uttar Pradesh 15.25 15.75 17.92 17.42 0.00 0.00 51.19 48.72 68.60 68.30

Uttarakhand 100.00 95.00 56.44 54.46 0.00 0.00 59.06 62.47 76.60 86.00

West Bengal 45.36 49.18 5.70 5.91 76.92 76.92 73.03 77.00 92.80 92.50


Table A.4.3 (Continued) - Larger States: Key Inputs/Processes domain indicators, for base and reference years

85

States

3.1.7 IDSP reporting of

(percentage)


(percentage)

3.1.8 CHC grading

(percentage)

3.1.9 Quality accreditation

DH-SDH (percentage)


CHC-PHC (percentage)

3.1.10 Fund

transfer (no. of days)

BY RY BY RY BY RY BY RY BY RY BY RY

Andhra Pradesh 94 99 94 99 1.02 37.24 0.00 0.00 0.00 0.00 97 127

Assam 92 88 92 88 4.64 31.13 0.00 0.00 0.00 0.00 97 242

Bihar 83 88 83 87 0.00 20.34 27.16 27.16 2.36 1.52 135 40

Chhattisgarh 77 84 66 82 3.23 47.74 0.00 0.00 0.00 0.00 79 57

Gujarat 96 95 98 96 10.25 49.40 6.35 2.99 1.24 0.60 58 24

Haryana 89 84 90 88 10.09 22.02 0.00 0.00 0.00 0.00 27 42

Himachal Pradesh 41 66 35 62 2.53 5.06 0.00 1.37 0.00 0.00 102 47

Jammu &Kashmir 66 80 61 75 7.14 61.90 0.00 0.00 0.00 0.00 97 107

Jharkhand 69 73 68 72 1.55 54.40 0.00 0.00 0.00 0.00 140 67

Karnataka 82 95 82 94 25.34 31.27 0.00 0.53 0.00 0.00 122 139

Kerala 94 96 93 96 NA 0.44 10.00 10.00 5.07 6.52 80 107

Madhya Pradesh 81 80 82 80 8.98 57.19 0.00 0.00 0.29 0.57 35 41

Maharashtra 71 79 72 76 16.67 38.52 0.00 0.00 0.27 0.27 140 66

Odisha 66 83 63 74 9.81 22.81 15.25 15.25 0.00 0.00 24 59

Punjab 77 73 93 85 12.00 26.67 0.00 0.00 0.00 0.00 98 78

Rajasthan 59 73 57 68 3.19 54.48 0.00 0.00 0.00 0.00 71 48

Tamil Nadu 70 90 72 87 NA 76.10 0.74 4.29 7.27 4.94 56 50

Telangana 94 97 94 95 0.00 11.63 0.00 0.00 0.00 0.00 70 287

Uttar Pradesh 64 42 70 57 4.53 44.13 0.00 0.00 0.00 0.00 30 93

Uttarakhand 88 93 84 93 1.67 8.33 0.00 0.00 0.00 0.00 97 27

West Bengal 65 78 72 80 3.49 53.74 0.00 0.00 0.00 0.00 71 51


form P form L

Table A.4.3 (Continued) - Larger States: Key Inputs/Processes domain indicators, base and reference years

86

States 1.1.4 LBW

(percentage)



(percentage)

1.2.5 PLHIV on ART

(percentage)


(in INR)#

BY RY BY RY BY RY BY RY BY RY BY RY RY Arunachal Pradesh 5.79 6.55 60.58 64.95 55.99 56.46 186 183 88.00 86.40 18.69 28.19 6474

Goa 16.72 15.56 91.26 95.24 91.27 92.46 127 131 86.40 87.30 70.92 72.75 4836

Manipur 3.90 3.53 94.39 96.32 74.93 73.47 82 81 85.00 82.60 53.95 63.87 10076

Meghalaya 8.19 7.65 96.43 93.34 59.57 62.11 170 137 82.30 85.80 98.66 100.00 2892

Mizoram 4.73 4.65 100.00 100.00 100.00 96.29 183 186 86.50 90.60 96.68 100.00 4327

Nagaland 4.10 3.89 61.91 63.86 56.95 58.07 173 139 90.70 71.90 63.81 73.80 5834

Sikkim 6.78 7.76 74.07 74.44 71.96 70.19 222 241 78.80 77.20 32.45 33.51 2509

Tripura 10.56 11.11 87.43 84.33 78.48 79.36 195 61 88.60 88.50 23.14 5.80 4412

1.2.3 TB case

notificationrate (per 100,000

population)

1.2.4 TBtreatment

success rate(percentage)

Table A.4.4 - Smaller States: Health Outcomes domain indicators, base and reference years

States

2.1.1.a Data Integrity: Institutional deliveries

(percentage)

2.1.1.b Data Integrity: First trimester ANC



(in months)


(in months)

BY** RY BY** RY BY RY BY RY Arunachal Pradesh 1.36 1.36 5.62 5.62 19.85 13.87 19.29 17.50

Goa 5.01 5.01 23.74 23.74 14.84 21.69 15.00 12.00

Manipur 2.87 2.87 28.19 28.19 13.29 21.02 18.64 17.31

Meghalaya 13.44 13.44 10.56 10.56 19.99 19.25 15.49 14.76

Mizoram 22.00 22.00 18.71 18.71 11.12 9.77 20.51 25.98

Nagaland 54.79 54.79 107.87 107.87 11.61 7.25 17.43 19.94

Sikkim 29.16 29.16 26.76 26.76 24.00 24.02 31.50 25.52

Tripura 3.35 3.35 10.89 10.89 11.99 10.87 14.32 17.26


Table A.4.5 - Smaller States: Governance and Information domain indicators, base and reference years



87

States

3.1.1.a Vacancy: ANMs at SCs (percentage)

3.1.1.b Vacancy: SNs at PHCs and

CHCs (percentage)

3.1.1.c Vacancy: MOs at PHCs (percentage)

3.1.1.d Vacancy: Specialists at DHs

(percentage)

3.1.2 E-payslip

(percentage)

BY RY BY RY BY RY BY RY BY RY Arunachal Pradesh 2.07 22.37 4.05 28.78 9.38 38.75 87.55 89.11 45.89 38.75

Goa 24.75 30.10 12.54 11.68 31.11 14.22 42.71 39.70 0.00 0.00

Manipur 20.57 29.89 5.08 18.98 42.76 42.76 47.67 47.67 0.00 0.00

Meghalaya 19.56 20.00 30.90 31.05 31.85 35.67 29.28 29.73 0.00 0.00

Mizoram 11.33 16.07 6.11 6.11 31.58 38.10 15.22 15.22 0.00 0.00

Nagaland 7.80 11.01 0.00 0.00 26.89 27.36 0.00 0.00 0.00 0.00

Sikkim 0.00 0.00 61.96 61.96 0.00 0.00 34.38 34.38 0.00 0.00

Tripura 15.37 38.90 22.20 0.00 17.03 2.06 NA NA 0.00 0.00

Table A.4.6 - Smaller States: Key Inputs/Processes domain indicators, base and reference years

States


(percentage)

3.1.3.b Functional 24x7 PHCs

(percentage)

3.1.4 Districts with

functional CCUs

(percentage)


ANC (percentage)

3.1.6 Level of birth registration

(percentage)


Arunachal Pradesh 100.00 133.33 21.43 42.86 0.00 0.00 38.66 36.99 100.00 100.00

Goa 100.00 100.00 0.00 6.67 0.00 0.00 57.00 58.74 100.00 100.00

Manipur 83.33 66.67 41.38 65.52 0.00 0.00 59.07 63.23 100.00 100.00

Meghalaya 83.33 100.00 166.67 180.00 0.00 0.00 32.24 32.07 100.00 100.00

Mizoram 150.00 100.00 190.91 136.36 11.11 11.11 72.26 73.61 100.00 100.00

Nagaland 150.00 125.00 165.00 165.00 0.00 9.09 46.80 35.83 100.00 100.00

Sikkim 100.00 200.00 166.67 216.67 0.00 0.00 77.81 79.89 79.90 74.10

Tripura 42.86 57.14 124.32 116.22 0.00 0.00 62.75 61.85 91.40 81.70


Table A.4.6 (Continued) - Smaller States: Key Inputs/Processes domain indicators, base and reference years


88

States


P form (percentage)

3.1.7 IDSP reporting of L

form (percentage)

3.1.8 CHC grading

(percentage)


DH-SDH (percentage)



3.1.10 Fund transfer

(no.of days)

BY RY BY RY BY RY BY RY BY RY BY RY Arunachal Pradesh 43 82 33 77 0.00 0.00 5.00 5.00 0.00 0.00 98 143

Goa 65 79 67 88 25.00 75.00 0.00 0.00 0.00 0.00 149 154

Manipur 35 63 32 38 0.00 29.41 12.50 12.50 0.00 0.00 199 258

Meghalaya 62 84 63 82 3.70 7.41 0.00 0.00 0.00 0.00 216 38

Mizoram 51 48 74 58 0.00 0.00 0.00 0.00 0.00 0.00 140 177

Nagaland 80 79 61 65 0.00 0.00 0.00 0.00 0.00 0.00 101 213

Sikkim 91 97 86 100 0.00 0.00 0.00 0.00 0.00 0.00 68 153

Tripura 75 97 61 94 0.00 0.00 0.00 0.00 0.00 0.00 118 69


Table A.4.6 (Continued) - Smaller States: Key Inputs/Processes domain indicators, base and reference years

UTs 1.1.4 LBW

(percentage)



(percentage)


(in INR)#

BY RY BY RY BY RY BY RY BY RY RY


16.13 17.17 84.62 100.00 76.21 80.20 157 139 85.50 91.50 1258

Chandigarh 22.49 20.77 92.30 93.58 100.00 100.00 300 305 89.50 85.60 2357

Dadra & Nagar Haveli 34.70 29.39 75.48 77.06 88.20 87.09 138 133 85.20 86.30 471

Daman & Diu 16.91 24.37 85.04 79.67 75.29 72.00 146 166 83.10 79.50 1581

Delhi 20.85 21.43 90.88 96.21 79.41 80.60 337 348 86.20 86.70 8719

Lakshadweep 4.85 5.56 100.00 100.00 76.44 85.40 61 35 86.70 91.30 4580

Puducherry 18.48 15.50 73.93 77.60 100.00 100.00 95 103 88.50 89.20 1999


1.2.3 TB case

notificationrate (per 100,000

population)

1.2.4 TBtreatment

success rate(percentage)

Table A.4.7 - Union Territories: Health Outcomes domain indicators, base and reference years


89


UTs

2.1.1.a Data Integrity: Institutional

deliveries (percentage)

2.1.1.b Data Integrity: First trimester ANC registration

(percentage)


(in months)


(in months)

BY** RY BY** RY BY RY BY RY Andaman &

Nicobar Islands 18.05 18.05 2.84 2.84 26.00 15.01 25.49 17.43

Chandigarh 57.98 57.98 27.88 27.88 10.80 12.01 15.53 15.55

Dadra & Nagar Haveli 15.11 15.11 22.12 22.12 14.40 14.41 18.00 18.01

Daman & Diu 17.43 17.43 15.27 15.27 20.40 21.02 36.00 36.03

Delhi 10.76 10.76 27.77 27.77 13.70 9.63 15.82 16.72

Lakshadweep 29.35 29.35 12.19 12.19 26.77 26.79 NA NA

Puducherry 90.52 90.52 48.82 48.82 21.96 19.98 23.05 25.32

Table A.4.8 - Union Territories: Governance and Information domain indicators, base and reference years

UTs

3.1.1.a Vacancy: ANMs

at SCs (percentage)

3.1.1.b Vacancy: SNs at PHCs and

CHCs (percentage)

3.1.1.c Vacancy: MOs at PHCs (percentage)

3.1.1.d Vacancy: Specialists at DHs

(percentage)

3.1.2 E-payslip

(percentage)

BY RY BY RY BY RY BY RY BY RY Andaman &

Nicobar Islands 7.84 7.84 7.45 7.45 36.36 36.36 100.00 100.00 0.00 0.00

Chandigarh 31.25 29.41 6.19 6.19 69.17 69.17 0.00 0.00 59.97 61.33

Dadra & Nagar Haveli 0.00 0.00 4.88 4.88 16.67 16.67 18.18 18.18 0.00 0.00

Daman & Diu 13.56 11.86 2.38 0.00 7.14 7.14 38.24 47.06 0.00 0.00

Delhi 4.88 19.75 32.00 40.75 8.33 14.21 38.74 40.21 0.00 68.81

Lakshadweep 0.00 0.00 0.00 0.00 0.00 0.00 76.47 76.47 0.00 0.00

Puducherry 7.23 8.73 1.19 2.38 12.78 12.78 23.36 20.56 80.74 78.35


Table A.4.9 - Union Territories: Key Inputs/Processes domain indicators, base and reference years

90

UTs


(percentage)

3.1.3.b Functional 24x7

PHCs (percentage)

3.1.4 Districts with functional CCUs

(percentage)


ANC (percentage)

3.1.6 Level of birth registration

(percentage)

BY RY BY RY BY RY BY RY BY RY Andaman &

Nicobar Islands 0.00 0.00 500.00 500.00 0.00 0.00 77.84 76.94 97.20 71.90

Chandigarh 150.00 150.00 0.00 0.00 0.00 0.00 49.63 36.79 100.00 100.00

Dadra & Nagar Haveli 100.00 100.00 100.00 133.33 0.00 0.00 47.27 84.77 71.80 65.10

Daman & Diu 100.00 100.00 50.00 50.00 0.00 0.00 47.32 49.26 98.40 76.40

Delhi 91.18 100.00 0.60 0.60 90.91 90.91 34.74 33.69 100.00 100.00

Lakshadweep 100.00 100.00 0.00 0.00 100.00 100.00 74.88 73.24 60.00 59.50

Puducherry 300.00 200.00 0.00 0.00 25.00 25.00 45.53 39.54 100.00 100.00

Table A.4.9 (Continued) - Union Territories: Key Inputs/Processes domain indicators, base and reference years

UTs


P form (percentage)

3.1.7 IDSP reporting of L

form (percentage)

3.1.8 CHC grading

(percentage)


DH-SDH (percentage)



3.1.10 Fund

transfer (no. of days)

BY RY BY RY BY RY BY RY BY RY BY RY Andaman &

Nicobar Islands

12 50 5 21 0.00 0.00 0.00 0.00 0.00 0.00 147 78

Chandigarh 84 78 93 88 100.00 100.00 0.00 0.00 0.00 0.00 68 35

Dadra & Nagar Haveli 100 91 100 89 0.00 NA 0.00 0.00 0.00 0.00 64 62

Daman & Diu 100 75 86 75 0.00 0.00 0.00 0.00 0.00 0.00 76 0

Delhi 40 57 42 56 0.00 0.00 1.79 8.93 0.00 0.00 92 89

Lakshadweep 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 143 0

Puducherry 82 90 77 88 25.00 25.00 0.00 0.00 0.00 0.00 101 55


Table A.4.9 (Continued) - Union Territories: Key Inputs/Processes domain indicators, base and reference years

Healthy States, Progressive India - NITI Aayog

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