ENDLINE SURVEY FINAL REPORT SAVE THE CHILDREN, MALAWI ... · RAcE Endline Survey Final Report vi...

ENDLINE SURVEY

FINAL REPORT

SAVE THE

CHILDREN,

MALAWI

ENDLINE SURVEY

FINAL REPORT

SAVE THE

CHILDREN,

MALAWI

Prepared by ICF and Save the

Children for WHO Rapid Access

Expansion (RAcE) Program

MARCH 31, 2017

AUTHORS: Kirsten Zalisk, Tanya

Gunther, Emmanuel Chimbalanga,

Humphreys Nsona

pared by ICF and Save the Children

for WHO Rapid Access Expansion

(RAcE) Program

MARCH 31, 2017

AUTHORS: Kirsten Zalisk, Tanya

Gunther, Emmanuel Chimbalanga,

Humphreys Nsona

RAcE Endline Survey Final Report ii

ACKNOWLEDGEMENTS

ICF and Save the Children would like to thank the National Statistics Office and the Malawi Ministry of

Health for their contributions to this work. We would also like to thank the health surveillance

assistants (Malawi’s community health workers), who work hard to provide services to caregivers and

children in communities, and to the caregivers who give so much to ensure and improve the health of

their children. This work was made possible by the World Health Organization through funding by the

Canadian Government.

RAcE Endline Survey Final Report iii

TABLE OF CONTENTS

ABBREVIATIONS ............................................................................................................................................................. iv

EXECUTIVE SUMMARY .................................................................................................................................................. v

1 BACKGROUND .................................................................................................................................................... 11

1.1 RAcE Program Goals and Objectives ....................................................................................................... 11

1.2 Save the Children, Malawi Project Background ..................................................................................... 11

1.3 Endline Survey Objectives ........................................................................................................................... 14

2 SURVEY METHODS .............................................................................................................................................. 15

2.1 Survey Implementation and Partnership .................................................................................................. 15

2.2 Survey Design ................................................................................................................................................. 15

2.3 Survey Questionnaire ................................................................................................................................... 16

2.4 Selection and Training of Survey Staff ...................................................................................................... 17

2.5 Data Collection .............................................................................................................................................. 18

2.6 Data Entry and Management ...................................................................................................................... 18

2.7 Data Analysis .................................................................................................................................................. 19

2.8 Survey Indicators ........................................................................................................................................... 19

2.9 Survey Limitations ......................................................................................................................................... 19

3 FINDINGS ................................................................................................................................................................ 21

3.1 Characteristics of Sick Children and Caregivers ................................................................................... 21

3.2 Caregiver Knowledge and Their Perceptions of CCM-Trained HSAs ............................................. 23

3.3 Decision-Making ............................................................................................................................................ 25

3.4 Care-Seeking................................................................................................................................................... 26

3.5 Assessment ..................................................................................................................................................... 28

3.6 Treatment Coverage .................................................................................................................................... 30

3.7 First Dose of Treatment and Counseling from HSA ............................................................................ 32

3.8 Referral Adherence ....................................................................................................................................... 33

3.9 Sick Child Follow-Up .................................................................................................................................... 33

3.10 Illness Management and Diagnostics by Sex ........................................................................................... 34

4 DISCUSSION .......................................................................................................................................................... 35

Annex A. List of Key Persons Involved in the Survey............................................................................................. 39

Annex B. Endline Sample ............................................................................................................................................... 40

Annex C1. Endline Survey Household Questionnaire ............................................................................................ 45

Annex C2. Endline Survey HSA Questionnaire........................................................................................................ 46

Annex D. Training Schedule .......................................................................................................................................... 47

Annex E. Key Indicator Summary Tables for Sub-Areas ........................................................................................ 52

Annex F. Illness Management and Diagnostics by Sex Results Tables ................................................................ 62

Annex G. Supplementary 60 Cluster Results Tables .............................................................................................. 65

Annex H. Results of Endline HSA Survey .................................................................................................................. 74

RAcE Endline Survey Final Report iv

ABBREVIATIONS

ACT artemisinin-based combination therapy

CCM community case management

EA enumeration area

HSA health surveillance assistant

HTRA hard-to-reach area

iCCM integrated community case management

IMCI Integrated Management of Child Illnesses

MOH Ministry of Health

mRDT malaria rapid diagnostic test

NSO National Statistics Office

ORS oral rehydration solution

RAcE Rapid Access Expansion

WHO World Health Organization

RAcE Endline Survey Final Report v

EXECUTIVE SUMMARY

Since April 2013, Save the Children has been leading the implementation of the Rapid Access Expansion

(RAcE) program in Malawi, managing a consortium of organizations that includes D-tree International

and Medical Care Development International and working in close collaboration with the Ministry of

Health (MOH) Integrated Management of Childhood Illness (IMCI) unit, which is providing oversight.

The RAcE project began in four districts: Dedza, Mzimba North, Ntcheu, and Ntchisi. In 2014, the

project expanded geographically to include the districts of Likoma, Lilongwe Rural, Nkhatabay, and

Rumphi. The project helped to address challenges that the Malawi’s national integrated community case

management (iCCM) program faced, including supporting HSAs with supplies and supervision, expand

iCCM services to more communities, and update the iCCM protocol to align with World Health

Organization recommendations for management of fever and suspected pneumonia.

In August 2016, the National Statistics Office conducted the RAcE endline survey in the four original

project districts, with technical assistance from ICF and technical, logistical, administrative, and financial

support from Save the Children. We compared baseline and endline data to assess changes in sick child

care-seeking, assessment, and treatment coverage as well as caregivers’ knowledge of childhood illnesses

and perceptions of health surveillance assistant (HSA) services, and used the information to make

inferences about project accomplishments.

The survey results show that caregivers were less likely to be aware of a community case management

(CCM)-trained HSA in their community at endline compared to baseline (p<0.05), and perceptions of

the HSAs as trusted, convenient providers of high iCCM services also decreased from baseline to

endline (see Table 1, indicators 4, 5 and 7). Although these results could indicate that iCCM service

availability and quality deteriorated during the implementation of the RAcE project, the survey results

also show increases in indicators measuring HSAs as the first source of care for cases of cough with

difficult or fast breathing, malaria testing, and respiratory rate assessment over the course of the project.

More increases may not have been seen because the baseline survey was not a “true” pre-iCCM

baseline; more than 400 CCM-trained HSAs were already working in the project districts at the time of

the baseline survey. We, therefore, cannot expect to see increases over the course of the project that

might accompany the introduction of iCCM services. Furthermore, the survey results were likely diluted

because iCCM services were not available in all 60 clusters surveyed at endline. Many areas targeted for

iCCM at baseline, as RAcE was beginning, ultimately did not gain access to iCCM by the time of the

endline survey; only 33 (55 percent) of surveyed clusters had an active CCM-trained HSA present at

endline. Several HSA posts were vacant, and some district managers did not allow HSAs who were not

residents of their catchment areas to attend iCCM trainings and provide iCCM services. In addition, the

HSA survey revealed that only one-quarter of HSAs providing iCCM services met the strict definition of

functionality: being a resident in their catchment area and providing iCCM services at least five days per

week.

The survey data were explored further through sub-analyses of the 33 clusters confirmed to have an

active CCM-trained HSA and the 27 clusters confirmed not to have an active CCM-trained HSA at

RAcE Endline Survey Final Report vi

endline.1These sub-analyses show that at endline in the 33 clusters with an active iCCM HSA there were

higher levels of care-seeking from HSAs and more positive perceptions of services provided by HSAs

compared to the 27 clusters without an active iCCM HSA.

Despite iCCM being a mature program in Malawi, large service gaps remain due to the absence of fully

functional CCM-trained HSAs in eligible communities. Addressing HSA deployment issues, however, will

require dealing with issues beyond the control of the MOH IMCI unit, which does not manage the

broader HSA program. Implementation of the RAcE project in Malawi will soon be winding down, and

the MOH will continue to implement iCCM services on its own. The findings of the household and HSA

surveys highlight the importance of ensuring that HSAs are deployed in hard-to-reach areas and also that

they are available at their village clinics so that caregivers can access their services. Going forward, the

MOH IMCI unit and partners need to find ways to ensure the availability of HSAs at their village clinics

and maintain the quality of their services. They need to better understand why caregivers prefer seeking

care from providers other than HSAs when their children are sick. The findings also show that there are

some illness management patterns that need to be explored and better understood, including why HSAs

do not prescribe zinc more often and why HSAs and health facility staff are not using malaria diagnostic

tests more often to assess cases of fever.

Table 1. Summary of key indicators

Indicators highlighted in green had a statistically significant increase from baseline to endline, determined by a p-value of less than 0.05. Indicators highlighted in red had a statistically significant decrease from baseline to endline, determined by a p-value of less than 0.05.

Indicator Baseline Endline

% point change

p-value % (CI %) % (CI %)

Caregiver knowledge

1

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who are aware of the presence of the CCM-trained HSA in their community

90.0 (83.3 - 94.2)

83.4 (74.7 - 89.6)

-6.6 0.0355

2

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who know the role of the CCM-trained HSA in their community

35.0 (29.6 - 40.9)

34.0 (28.7 - 39.7)

-1.0 0.7930

3

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who know two or more signs of childhood illness that require immediate assessment by an appropriately trained provider

97.5 (96.1 - 98.4)

95.7 (93.5 - 97.1)

-1.8 0.0824

Caregiver perceptions of iCCM services

1 Confirmation was obtained through a mapping exercise that Save the Children conducted in January 2017.

RAcE Endline Survey Final Report vii

4

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who view CCM-trained HSAs as trusted health care providers

82.3 (77.5 - 86.2)

70.3 (62.8 - 76.8)

-12.0 0.0004

5

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who believe CCM-trained HSAs provide quality services

68.4 (63.7 - 72.7)

57.6 (52.3 - 62.7)

-10.8 0.0007

6

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who found the CCM-trained HSA at first visit

86.5 (79.3 - 91.5)

84.0 (78.2 - 88.4)

-2.5 0.5414

7

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who cite the CCM-trained HSA as a convenient source of treatment

59.6 (52.5 - 66.3)

47.3 (39.9 - 54.8)

-12.3 0.0045

Sick child care-seeking

8

Percentage of children age 2-59 months who have been sick in the two weeks preceding the survey for whom advice or treatment was sought from an appropriate provider

Overall 65.6

(60.7 - 70.1) 70.0

(65.4 - 74.2) 4.5 0.0740

Fever 70.3

(64.4 - 75.6) 73.9

(68.9 - 78.4) 3.6 0.2575

Diarrhea 64.0

(57.9 - 69.7) 69.8

(63.9 - 75.0) 5.8 0.1202

Cough with difficult or fast breathing 61.9

(55.5 - 67.9) 65.6

(59.8 - 71.1) 3.7 0.2465

9

Percentage of children age 2-59 months who were sick in two weeks preceding the survey taken to a CCM-trained HSA as first source of care

Overall 25.7

(20.2 - 32.1) 33.4

(27.1 - 40.3) 7.7 0.0278

Fever 26.4

(20.2 - 33.6) 34.0

(27.2 - 41.5) 7.6 0.0547

Diarrhea 30.8

(24.0 - 38.5) 37.5

(30.5 - 45.1) 6.7 0.0925


(15.5 - 27.5) 29.5

(23.2 - 36.6) 8.6 0.0246

Sick child assessment

10 Percentage of children age 2-59 months with fever in the two weeks preceding the survey who had finger or heel stick

35.6 (30.0 - 41.7)

59.0 (53.7 - 64.2)

23.4 0.0000

RAcE Endline Survey Final Report viii

11

Percentage of children age 2-59 months for whom their caregiver received the results of the malaria diagnostic test of the children who had a finger or heel stick in the two weeks preceding the survey

96.9 (92.6 - 98.7)

97.3 (95.0 - 98.6)

0.4 0.7610

12

Percentage of children age 2-59 months with cough and difficult or rapid breathing (suspected pneumonia) in the two weeks preceding the survey who had their respiratory rate counted to assess fast breathing

25.6 (20.6 - 31.4)

38.5 (33.5 - 43.7)

12.8 0.0007

Sick child assessment by HSA

13

Percentage of children age 2-59 months with fever in the two weeks preceding the survey who had a finger or heel stick by an HSA (among those who sought care from an HSA)

0 61.7

(52.7 - 70.0) 61.7 0.0000

14

Percentage of children age 2-59 months for whom their caregiver received the results of the malaria diagnostic test of the children who had a finger or heel stick by an HSA in the two weeks preceding the survey (among those who sought care from an HSA)

0* 98.4

(93.3 - 99.6) 98.4 na

15

Percentage of children age 2-59 months with cough and difficult or rapid breathing (suspected pneumonia) in the two weeks preceding the survey who had their respiratory rate counted to assess fast breathing by an HSA (among those who sought care from an HSA)

29.6 (21.0 - 40.0)

55.8 (46.0 - 65.1)

26.2 0.0003

Sick child treatment

16

Percentage of children age 2-59 months who have been sick in two weeks preceding the survey who received appropriate treatment

Overall 42.7

(38.2 - 47.2) 47.1

(43.3 - 51.0) 4.5 0.0720

Fever (ACT within 24 hours)* 61.9

(54.8 - 68.4) 59.2

(52.5 - 65.7) -2.6 0.5721

Diarrhea (ORS and zinc) 18.4

(13.8 - 24.1) 21.2

(16.9 - 26.3) 2.8 0.3976

Cough with difficult or fast breathing (Baseline-cotrimoxazole; endline-

amoxicillin)

53.3 (47.3 - 59.2)

61.8 (56.4 - 66.9)

8.5 0.0165

17

Percentage of children age 2-59 months who have been sick in the two weeks preceding the survey who received appropriate treatment from a CCM-trained HSA

Overall 13.9

(10.3 - 18.6) 16.6

(12.6 - 21.5) 2.7 0.3085

RAcE Endline Survey Final Report ix

Fever (ACT within 24 hours)* 29.3

(21.9 - 37.9) 24.8

(17.4 - 34.1) -4.5 0.3708


(4.3 - 11.6) 10.6

(7.2 - 15.4) 3.5 0.1828


amoxicillin)

12.0 (8.2 - 17.3)

17.4 (13.4 - 22.3)

5.4 0.0922

18

Percentage of children age 2-59 months who have been sick in the two weeks preceding the survey who received the first dose of treatment in the presence of an HSA

Overall 37.3

(27.4 - 48.4) 49.4

(41.9 - 56.8) 12.1 0.0531

Fever (ACT) 39.2

(29.6 - 49.7) 56.2

(45.1 - 66.7) 17.0 0.0209


(11.8 - 40.3) 22.0

(11.7 - 37.3) -1.1 0.9056


amoxicillin)

41.5 (25.0 - 60.2)

54.1 (43.9 - 64.0)

12.6 0.2539

19

Percentage of sick children age 2-59 months for whom their caregivers received counseling on how to provide the treatment(s) among those who received prescription medicines for a CCM condition in the two weeks preceding the survey

Overall 100 97.8

(94.0 - 99.2) -2.2 0.1369

Fever (ACT) 100 99.1

(93.0 - 99.9) -1.0 0.4176

Diarrhea (ORS and zinc) 100 95.1

(81.7 - 98.8) -4.9 0.2467


amoxicillin) 100

97.7 (90.7 - 99.4)

-2.4 0.2751

Sick child referral and follow-up

20

Percentage of sick children age 2-59 who were referred in the two weeks preceding the survey whose caregiver adhered to referral advice

88.6 (77.6 - 94.6)

87.1 (80.0 - 92.0)

-1.5 0.7981

21

Percentage of sick children age 2-59 months receiving treatment from an HSA in the two weeks preceding the survey whose caregiver followed up with the HSA after the initial consultation

19.4 (13.8 - 26.6)

21.7 (17.1 - 27.1)

2.3 0.5028

na = not applicable; ORS=oral rehydration solution *Appropriate fever treatment includes presumptive malaria treatment at baseline by HSAs; confirmed malaria treatment at endline by HSAs; confirmed malaria treatment by all other providers at baseline and endline. Presumptive treatment includes cases in which ACT was given but no there was no finger prick or heel stick. Confirmed malaria treatment includes cases in which ACT was given, there was a finger or heel stick, and the result of the test was positive. Appropriate treatment for fever cases was restricted to include only children aged 5–59 months.

RAcE Endline Survey Final Report x

RAcE Endline Survey Final Report 11

1 BACKGROUND

1.1 RAcE Program Goals and Objectives

In 2013, the World Health Organization (WHO) launched the Rapid Access Expansion (RAcE) program

in five sub-Saharan African countries—Democratic Republic of Congo, Malawi, Mozambique, Niger, and

Nigeria. The goal of the program was to increase coverage of diagnostic, treatment, and referral services

for malaria, pneumonia, and diarrhea to decrease overall mortality and the number of severe cases

among children aged 2-59 months. The program would accomplish this goal through the following

objectives:

Catalyze the scale-up of integrated community case management (iCCM) as an integral part of

government-provided health services in sub-Saharan Africa.

Stimulate policy review and regulatory update in each country on disease case management.

Accelerate adaptation of supply management and surveillance systems to include services at the

community level.

This effort came at a time when there was great momentum for iCCM at the country level and a high

degree of interest among the global health community to understand how to best measure success and

how to build country ownership and capacity to sustain iCCM interventions.

1.2 Save the Children, Malawi Project Background

The under-five child mortality rate in Malawi has been decreasing steadily since 1992, from 234 deaths

per 1,000 live births in 1992 to 64 deaths per 1,000 live births in 2015.2 Despite this progress, large

numbers of children continue to die from conditions that are easily preventable and treatable. Malaria,

diarrhea, and pneumonia account for approximately half of the deaths among children aged

1-59 months.3 Pneumonia alone accounts for more than 13 percent of the deaths in hospitalized children

under 5 years of age.4

To address the issue of preventable deaths of children under five, the Government of Malawi started an

iCCM program through the Ministry of Health (MOH) Integrated Management of Childhood Illness

(IMCI) unit in 2008. Health surveillance assistants (HSAs) offer iCCM services at village clinics in hard-

to-reach areas (HTRAs). In a country where human resources for health care are in short supply, HSAs

often serve as the first line of defense against childhood illnesses.

HSAs are a community-based cadre who were meant to serve approximately 1,000 residents, but in

practice they often have much larger catchment areas of 2,000 residents or more. They are centrally

recruited and on the payroll of the MOH, but they are deployed to and stationed in the communities

2 UNICEF and World Health Organization. 2015. Countdown to 2015 maternal, newborn & child survival: A

decade of tracking progress for maternal, newborn and child survival—The 2015 report. Available at

http://www.countdown2015mnch.org/documents/2015Report/Countdown_to_2015_final_report.pdf. 3 WHO, Malawi neonatal and child health country profile. Available at

http://www.who.int/maternal_child_adolescent/epidemiology/profiles/neonatal_child/mwi.pdf. 4 Bjornstad, et al. Determining the quality of IMCI pneumonia care in Malawian children. 2014. Paedeatrics and

International Child Health, 34(1).

http://www.who.int/maternal_child_adolescent/epidemiology/profiles/neonatal_child/mwi.pdf


that they serve. For supervision and support purposes, HSAs are attached to the nearest health facility.

HSAs are also expected to perform specific tasks at health facilities, such as HIV counseling,

administration of immunizations, and growth monitoring, among others.

HSAs initially provided iCCM services to communities in HTRAs located more than eight km from a

health facility. In 2013, the Government of Malawi changed the definition of HTRAs, decreasing the

distance to the nearest health facility from eight km to five km. The change in definition means that

communities located more than five km from a health facility are now eligible to receive iCCM services.

Since April 2013, RAcE has supported iCCM in four districts in Malawi: Dedza, Mzimba North, Ntcheu,

and Ntchisi. Save the Children is the lead implementing partner. It manages a consortium of

organizations that includes D-tree International and Medical Care Development International and works

in close collaboration with the MOH IMCI unit, which is providing oversight.

When RAcE started in 2013, HSAs trained in iCCM were already working in the four project districts.

Through RAcE, Save the Children is expanding iCCM coverage and strengthening iCCM implementation

in HTRAs of the project districts.

Within the project districts, Save the Children supports iCCM by training HSAs, HSA supervisors, and

HSA mentors; organizing community mobilization activities; and procuring and distributing key iCCM

commodities to village clinics. Save the Children also has staff members who serve as district

coordinators and work in close collaboration with the district health management team in each project

district. At the national level, the project has shared experiences and collaborated with other

organizations implementing iCCM activities, contributed to strategies such as the Child Health Strategy,

and helped improve iCCM data availability in DHIS2. Save the Children has also rolled out iCCM

interventions to align with changes in national policy. For example, it replaced cotrimoxazole with

amoxicillin after the MOH IMCI unit approved amoxicillin as the first-line treatment for cough with fast

breathing at the community level. It also moved from presumptive malaria treatment at village clinics to

having HSAs use malaria rapid diagnostic tests (mRDTs) to confirm that a child with fever needs

artemisinin-based combination therapy (ACT) treatment.

The project expanded geographically in 2014 to include the districts of Likoma, Lilongwe Rural,

Nkhatabay, and Rumphi. In 2014, Save the Children also introduced a community-based maternal and

newborn care component to the project in Ntcheu district.

As of September 2016, the project is supporting 810 HSAs, covering a total population of 2,298,981

across the 8 project districts, including 390,827 children under 5 years of age. Table 2 contains key

project implementation indicators as of September 2016.


Table 2. Key project implementation indicators, September 2016

Indicator Value*

Target population**

Total population in HTRAs of the eight project districts 2,298,981

Under five population in HTRAs of the eight project districts 390,827

Training

Number of HSAs trained in iCCM 1,121

Number of HSA supervisors trained to support iCCM 364

Community treatment

Percentage of trained HSAs providing services 90%

(810/896)

Number of malaria cases treated by HSAs 136,295

Number of fast breathing cases treated by HSAs 54,736

Number of diarrhea cases treated by HSAs 33,532

HSA reporting and activity levels

Percentage of HSA monthly iCCM reports received 86%

(697/810)

Supervision

Percentage of HSA supervision visits completed 81%

(656/810)

Note: These indicators were extracted from Save the Children’s Year 4 Semiannual Narrative Report submitted to WHO on November 15, 2016.

* All reported percentages are averages of monthly data for the first two quarters of Save the Children’s fourth year of implementation. The numbers of cases treated are cumulative values for the first two quarters of Save the Children’s fourth year of implementation.

** According to Save the Children’s Year 1 Annual Report Annex 1, Project Context, in the four original project districts, the target area population is 1,189,741, including 190,359 children under 5 years of age.

The RAcE project had planned to train 1,356 HSAs across the targeted districts but did not reach these

targets primarily because of deployment issues related to the broader HSA program in Malawi, which is

managed by a unit other than the IMCI unit that implements the iCCM program. The Government of

Malawi last recruited HSAs in 2008. When the iCCM program was introduced, HSAs who already

existed in HTRAs were trained to implement iCCM services. Over time, the number of HSAs has

decreased due to several factors, including drop out, change of career, transfer, and death. Some HSAs

who were assigned HTRAs have since been promoted to senior HSAs and are based at facilities. In

other cases, targeted HSAs did not reside in their catchment areas, and the districts did not agree to

train them in iCCM unless they resided full-time in their catchment area. Because of this, there are

HTRAs eligible for iCCM that do not have access to iCCM services.

Save the Children, in collaboration with the National Statistics Office (NSO) and with technical support

from ICF, conducted the RAcE baseline household survey in September 2013 in the four original project

districts.


1.3 Endline Survey Objectives

The objective of the RAcE endline household survey is to assess care-seeking behavior for sick children,

iCCM coverage, and caregiver knowledge, attitudes, and practices related to pneumonia, diarrhea, and

malaria in the RAcE Malawi intervention areas. We compared baseline and endline data to assess

changes in sick child care-seeking, assessment, and treatment coverage as well as caregivers’ knowledge

of childhood illnesses and perceptions of HSA services, and used the information to make inferences

about project accomplishments.


2 SURVEY METHODS

2.1 Survey Implementation and Partnership

Save the Children conducted the RAcE endline survey in collaboration with NSO and with technical

assistance from ICF. NSO is experienced in implementing all aspects of large household surveys,

including enumerator recruitment, training, data collection, data entry, and analysis, and NSO also led

the baseline survey implementation for RAcE Malawi. NSO worked with Save the Children and ICF to

finalize the endline questionnaire; led the training of enumerators, data entry operators, and supervisors;

conducted data collection and data entry; and provided oversight to the entire implementation process.

The survey protocol received ethical approval from ICF’s Institutional Review Board and from Malawi’s

National Health Sciences Research Committee.

Annex A contains a complete list of the key people involved in the survey and their roles.

2.2 Survey Design

Household survey: This was a cross-sectional cluster-based household survey, targeting primary

caregivers of children aged 2–59 months who had recently been sick with diarrhea, fever, or cough with

difficult or fast breathing. All primary caregivers of children aged 2–59 months reported to have

experienced diarrhea, fever, or cough with fast breathing in the two weeks before the interview were

considered eligible for inclusion in the survey. ICF developed standardized sampling guidance for all

RAcE projects, which was adapted for Save the Children Malawi.

To be able to detect a 20 percent difference at 90 percent power with a two-tailed test and 95 percent

confidence using cluster sampling, 263 cases were needed for each disease. ICF rounded up to 300 cases

to ensure a consistent number of interviews per cluster and a slight increase in the precision of the

coverage estimates.

Save the Children Malawi used a 60 x15 multi-stage cluster sampling methodology. The entire RAcE

project area, iCCM-eligible areas—more than five km from a health facility—in the four original project

districts comprised the target population. The primary sampling units selected at the first stage were the

census enumerations areas (EAs) defined for the 2008 Malawi Population and Housing Census that were

eligible for iCCM (located at least five km from a health facility). EAs, which have an average of about

235 households, are the smallest operational areas established for the census with well-defined

boundaries. The listing of all EAs for each of the four study districts was obtained from NSO, and all EAs

located within five km of a health facility were excluded from the sampling frame. A total of 60 EAs were

randomly selected proportional to population size across the project districts. The same EAs, or

clusters, visited for the baseline survey were visited for the endline survey.

Within each cluster, interviewers visited all households to explain the nature and purpose of the endline

survey. Each visited household was assigned an identification number. The interviewers administered a

screening questionnaire to the household head or its nominated representative to establish the numbers

and ages of all usual members of the household and any lodgers or people who sleep there regularly to

identify the number of caregivers of children aged 2–59 months and number of children aged 2–59

months. If the interviewer was unable to make contact with a responsible adult in a household, or if the

household representative requested time to discuss participation in the interview, then the household


was visited one more time before the household information was considered to be unobtainable. After

listing all the households, the team crossed out all ineligible households (those households with no

children under five who have been sick with diarrhea, fever, or cough with difficult or fast breathing in

the past two weeks before the survey).

The survey team then randomly selected 15 households to visit from that listing. They also selected a

backup group of 15 households to visit in case the survey team did not find the required number of

illness cases in the first group of 15. The survey team visited each selected household in the first group

of 15, even if all required cases of illness were attained before the fifteenth household.5 If after the first

15 households were visited, the survey team did not have 5 cases of diarrhea, fever, and cough with fast

breathing, the team went down the list of backup households that were also randomly selected from the

cluster household listing until 5 cases of that illness were found.

In each cluster, at least 5 interviews were conducted for each of the 3 illness modules—diarrhea, fever,

and fast breathing—for a total of at least 15 interviews per cluster, or 300 interviews per each illness

across the project area.

At each household, the interviewer first determined if an eligible child lived there. An eligible child was

aged 2–59 months and had been sick with diarrhea, fever, cough with fast breathing, or any combination

of the three illnesses in the two weeks preceding the survey.

If there was an eligible child in the household, the interviewer administered the questionnaire, including

all applicable illness modules, to the caregiver of the eligible child. If more than one child was eligible, and

they were sick with different illnesses, their caregiver was asked about each instance of illness. If there

was more than one eligible child in the household for an illness, the interviewer randomly selected one

of the eligible children and interviewed his or her caregiver. If there were multiple children selected for

inclusion in the survey, and the children had different primary caregivers, each primary caregiver of the

selected children was interviewed, but one of the caregivers was randomly selected to answer the

household asset questions.

The clusters included in the baseline and endline surveys are listed in Annex B.

HSA survey: As part of the endline survey, Save the Children conducted a survey of HSAs alongside the

household survey to assess the implementation strength and quality of iCCM services delivered by

HSAs. The objective of the HSA survey was to gain a better understanding of the HSAs’ background

characteristics, activity levels, and support and supervision received to help interpret the results of the

household survey. The HSAs serving the 60 clusters selected for the endline household survey formed

the sample population for the HSA survey. The EAs did not align perfectly with HSA catchment areas,

and in some cases more than one HSA was associated with a given cluster or the EA did not have any

community case management (CCM)-trained or active HSAs providing services. If a selected EA had

more than one HSA who was trained in CCM, only one HSA was randomly selected for the interview.

2.3 Survey Questionnaire

ICF developed a standard household questionnaire for all RAcE grantees to use for their baseline

surveys. Each grantee adjusted the questionnaire to fit the local iCCM program and country context. In

5 Otherwise, the sample will be biased toward households with more types of diseases.


Malawi, Save the Children replaced the template terminology with the appropriate local terminology for

community health workers, care-seeking locations, and treatment options. The same questionnaire used

for the baseline survey was used at endline, with the addition of two questions to each illness module to

gather information about reasons caregivers did not seek care at all or did not seek care from an HSA.

The survey questionnaire contains seven modules: caregiver and household background information;

caregivers’ knowledge of iCCM activities in their community; caregivers’ knowledge of childhood illness

danger signs; household decision-making; and a module for each major childhood illness: fever, diarrhea,

and fast breathing. In addition to collecting information about caregiver knowledge, care-seeking, and

treatment coverage, the questionnaire collects standard Demographic and Health Survey data on

household ownership of selected assets, materials used for housing construction, and types of water

access and sanitation facilities, which ICF will analyze and use for the final evaluation.

The survey questionnaire was translated into the local language, Chichewa, by NSO and Save the

Children. The survey took approximately one hour to administer in each household, depending on the

number of modules to which each caregiver responded.

The household survey was pretested in communities that were not in the survey sample, in the local

language, during enumerator and supervisor training. A few minor adjustments were identified as

necessary to the questionnaire during field testing.

The HSA survey questionnaire was developed based on tools used in the previous iCCM program

funded by CIDA from 2009 to 2012. The questionnaire was translated to Chichewa by NSO and Save the

Children and pretested during the enumerator and supervisor training (same as the household survey

questionnaire). Trained enumerators administered the questionnaire to selected HSAs alongside the

household survey (when the team was in the selected EA).

Annex C1 contains the endline household survey questionnaire, and Annex C2 contains the HSA

questionnaire.

2.4 Selection and Training of Survey Staff

NSO recruited data collectors, supervisors, and data keyers. All survey staff were required to have a

Malawi Schools Certificate with at least a credit pass in English and mathematics. Most of the recruited

supervisors, enumerators, and data entry clerks were full-time NSO staff, and a number of them had

participated in the baseline survey.

Data collectors and supervisors received a 12-day training, which covered the following:

Overview of the RAcE project goals and activities

Review of how the data to be collected related to the project’s objectives

Review of the translated questionnaire and the questions and the topics covered by the

questionnaire, including consistency of the questions asked

Practice on the techniques of interviewing and the informed consent form

Practice on the techniques of collecting data from respondents

Overview of the roles of interviewers and supervisors

An ICF staff member provided in-person technical support during the second week of training. Two days

of the interviewer training session, day 4 and day 12, were devoted to field testing the translated


questionnaire and informed consent form and practicing interviewing techniques. The areas selected for

field testing were not areas included in the survey. All interviewers were also trained on precautions and

avoidance of harm while in the field.

Annex D contains the survey training schedule.

2.5 Data Collection

Twenty-seven trained interviewers were divided into nine survey teams, each led by a supervisor. NSO

and Save the Children staff managed the day-to-day implementation of the survey. An ICF staff member

provided in-person technical support during the first week of data collection. Data were collected over

25 days, from August 5 to 29, 2016. There was not an official fieldwork schedule to include in this

report; teams were assigned a set of clusters and moved from cluster to cluster as they completed their

interviews. Each survey team was assigned approximately eight clusters, and each cluster took about

three days to complete.

Written informed consent was obtained for household interviews with primary caregivers of children

aged 2–59 months who had been sick with diarrhea or fever or cough with difficult or fast breathing in

the past two weeks in all study districts and for HSAs associated with the selected EA. Participation in

the study was voluntary, and there was no penalty for non-participation. Study respondents were not

compensated for their time away from income-earning activities or daily duties for participating in the

endline data collection.

Supervisors were responsible for ensuring that the survey team followed protocols throughout data

collection in the field. At the end of each day, supervisors in the field reviewed each completed

questionnaire and addressed any concerns or issues regarding the data quality. A quality assurance team

traveled among the clusters to ensure that data collection conformed to agreed-upon protocol and to

address any sampling issues. The quality assurance team also collected completed questionnaires from

the field and delivered them to the data entry supervisor.

2.6 Data Entry and Management

Data entry training took place over a five-day period after data collection was completed. Many of the

enumerators also served as keyers. Data entry took place over a month, from September 5 to

October 3. Data entry operators double-entered the survey data into a database using a CSPro tool

developed by ICF for the baseline and endline surveys. After two data entry operators entered the data

separately for a cluster, the data entry supervisor ran a quality check built into the CSPro tool to

compare the first and second entries for the cluster. If the check found any discrepancies, the data entry

operators used the paper questionnaires to verify the correct values and then resolved the

discrepancies using the CSPro tool. The supervisor again ran the quality check, and if it resulted in no

discrepancies, the data for the cluster were considered clean.

Names of participants were only collected for purposes of listing but were not used during any stage of

data analysis. Data entered could not be traced back to the individuals. Access to data was restricted to

authorized personnel only. After data for all clusters were entered and validated, NSO stripped the final

dataset of any identifying information and shared it with ICF for analysis.


2.7 Data Analysis

ICF analyzed the survey data using Stata v14 and Microsoft Excel. The ICF analyst imported the endline

household CSPro data files into Stata and merged them into one file. The baseline data file was

appended to the endline data file, and the merged file was checked, cleaned, and coded for the analysis.

The ICF analyst calculated point estimates and 95 percent confidence intervals accounting for cluster

effects. To test for statistically significant changes between indicators at baseline and endline, a Pearson’s

chi-squared test was used for binary and categorical variables and regression for continuous variables.

Indicators with p-values less than 0.05 show a statistically significant change between baseline and

endline.

ICF conducted the initial analysis of the HSA survey and provided tables with point estimates and

95 percent confidence intervals for a set of indicators developed by Save the Children. Save the Children

reviewed the tables and conducted additional analyses as needed. The detailed results of the HSA survey

are included in Annex H.

2.8 Survey Indicators

The household survey collected 21 key indicators related to caregiver knowledge of HSAs and child

illnesses; caregiver perceptions of HSAs; and sick child care-seeking, assessment, treatment, referral

adherence, and follow-up. The survey also collected information on household and caregiver

characteristics and household decision-making.

The HSA survey collected 22 indicators related to HSA residency, functionality, medicine and

diagnostics availability, supervision, service availability and activity levels, recording completeness,

knowledge, and data display and use. The survey also collected information on HSA background

characteristics.

2.9 Survey Limitations

The survey provides estimates for the four original RAcE project districts as a whole; it is not powered

to provide district-specific estimates and does not include the four project expansion districts.

Furthermore, the endline survey included areas not receiving RAcE interventions, thus diluting the

changes measured over the project implementation period. The sampling frame was based on census

EAs, which do not align perfectly with iCCM-eligible areas, so some of the EAs included in the sampling

frame may have included areas not eligible for iCCM. Save the Children also noted that it was not able

to implement RAcE activities in all iCCM-eligible areas of the four original districts because several HSA

posts were vacant, and in some districts, the district managers did not allow HSAs who did not reside in

their catchment areas to be trained in iCCM and implement iCCM services. As a result, several of the

60 EAs included in the survey either did not have an active CCM-trained HSA providing services or had

an active CCM-trained HSA serving only a subset of the EA at the time of the endline survey.

Through a mapping exercise conducted after the survey, Save the Children confirmed that 33 of the 60

clusters had an active CCM-trained HSA at the time of the endline survey, but 27 clusters did not. Key

indicators for sub-analyses of the 33 clusters with an active CCM-trained HSA and the 27 clusters

without an active CCM-trained HSA are included in Annex E. Relevant results are also highlighted in the

discussion section of the narrative.


During supervision of the endline data collection, the quality assurance team reported that the survey

attracted more interest than anticipated from communities. When community members noticed the

teams were only interviewing caregivers whose children were sick, some may have stated that their

child had recently been sick to participate even though the child had not been sick in the two weeks

prior to the survey. The quality assurance team was unsure how widespread the issue was, but they

dealt with the issue as soon as it was recognized. Via the WhatsApp group created for communication

with and among the data collection teams, they advised survey teams to intensify caregiver screening to

ensure only children who had been sick in the two weeks prior to the survey were included.

Lastly, there are known potential biases and limitations with the indicators that assess caregiver recall of

malaria diagnostic testing and coverage of appropriate treatment for children with fever and cough with

difficult or fast breathing. The potential biases and limitations of these indicators are further detailed in

the findings section.


3 FINDINGS

3.1 Characteristics of Sick Children and Caregivers

As shown in Table 3, 807 children were included in the baseline survey, and 873 children were included

in the endline survey. Of the sick children included, approximately 46 percent had diarrhea and

60 percent had cough with difficult or fast breathing in the two weeks preceding the survey. At baseline,

approximately 60 percent had fever in the two weeks preceding the survey, but at endline slightly more

than 70 percent had fever in the same time period.

Approximately half of the children were male in both surveys, and their age breakdown by year was

consistent across the surveys as well, with the smallest percentage of children in the oldest age category

(48–59 months).

Among the children surveyed, the baseline survey had 455 cases of fever, 364 cases of diarrhea, and 441

cases of cough with difficult or fast breathing; the endline survey had 571 cases of fever, 387 cases of

diarrhea, and 489 cases of cough with difficult or fast breathing.

Table 3. Characteristics of sick children included in survey

Characteristic Baseline % (CI %)

Endline % (CI %)

Sex of sick children included in survey

Male, % 51.4

(47.7 - 55.2) 49.8

(46.7 - 52.9)

Female, % 48.6

(44.8 - 52.3) 50.2

(47.1 - 53.3)

Age (months) of sick children included in survey

2–11 months, % 22.1

(19.1 - 25.7) 22.1

(19.5 - 25.0)

12–23 months, % 24.7

(21.7 - 27.8) 24.6

(22.1 - 27.3)

24–35 months, % 22.7

(19.9 - 25.7) 20.3

(17.5 - 23.4)

36–47 months, % 17.2

(14.9 - 19.9) 20.3

(17.5 - 23.4)

48–59 months, % 13.3

(10.7 - 16.3) 14.8

(12.6 - 17.3)

Two-week history of illness of children included in survey

Had fever, % 59.9

(56.4 - 63.2) 70.7

(66.9 - 74.2)

Had diarrhea, % 46.5

(43.7 - 49.2) 46.1

(43.3 - 48.9)

Had cough with difficult or fast breathing, % 58.5

(55.4 - 61.6) 60.0

(56.6 - 63.3)

Average number of illnesses, N 1.6 1.8

Total number of sick children included in survey 807 873

Cases of illness included in survey Fever, N 455 571 Diarrhea, N 364 387 Cough with difficult or fast breathing, N 441 489

Total number of sick child cases included in survey 1,260 1,447


At baseline, 720 primary caregivers of sick children were interviewed, and at endline, 783 primary

caregivers of sick children interviewed. As shown in Table 4, the mean age and highest education level of

the caregivers were similar in the surveys. A larger percentage of caregivers were married at the time of

the baseline survey (85 percent) than at the time of the endline survey (75 percent); however, the

percentage of caregivers either married or living with a partner as if married was similar in both surveys.

Table 4. Caregiver characteristics

Characteristic Baseline % (CI%)

Endline % (CI%)

Age (years)

15–24 35.8

(32.7 - 39.1) 40.2

(36.4 - 44.2)

25–34 44.3

(40.6 - 48.1) 40.0

(36.7 - 43.4)

35–44 15.6

(13.3 - 18.1) 15.7

(13.2 - 18.6)

45–76 4.3

(2.9 - 6.4) 4.1

(2.7 - 6.2) Mean age (years) 28.6 years 28.3 years

Highest level of education

None 14.4

(11.1 - 18.6) 12.1

(9.5 - 15.4)

Primary, ≤ year 4 32.2

(28.4 - 36.3) 36.0

(31.8 - 40.5)

Primary, ≥ year 5 43.5

(38.6 - 48.5) 39.1

(34.3 - 44.1)

Secondary or higher 9.9

(7.6 - 12.7) 12.8

(10.2 - 15.8)

Marital status

Currently married 84.9

(81.1 - 88.0) 75.4

(71.4 - 78.9)

Not married but living with partner 3.8

(2.2 - 6.4) 9.2

(6.4 - 13.1)

Not in union 11.4

(8.9 - 14.5) 15.5

(13.1 - 18.1)

Partner living with caregiver (among those in union)*

Yes 88.6

(85.2 - 91.2) 89.0

(86.1 - 91.3)

Total number of caregivers 720 783

*638 caregivers in a union at baseline, and 662 caregivers in a union at endline

On average, caregivers reported that they lived 10.5 km from the nearest health facility at baseline and

9.4 km from the nearest health facility at endline (see Table 5). Interestingly, at both baseline and

endline, approximately 10 percent of caregivers reported that they lived fewer than 5 km from the

nearest health facility, which means that they lived in areas that were not classified as hard-to-reach and

therefore technically did not live in areas that qualified for iCCM services, although they may have still

accessed iCCM services.

The majority of caregivers reported walking to the health facility in both surveys, with most stating that

it took more than an hour to reach the nearest health facility. On average, it took caregivers

approximately two hours to reach the nearest health facility in at both baseline and endline.


Table 5. Reported distance and mode of transport to nearest health facility

Travel to nearest facility Baseline Endline

% (CI%) % (CI%)

Distance to nearest facility

< 5 km

9.0 (4.8 - 16.4)

13.0 (7.9 - 20.5)

5-9 km

20.6 (15.1 - 27.4)

50.1 (41.2 - 58.9)

10-14 km

46.5 (38.9 - 54.2)

22.0 (15.7 - 29.8)

15-19 km

17.8 (12.6 - 24.5)

6.9 (4.5 - 10.6)

>= 20 km

6.2 (3.6 – 10.1)

8.1 (4.5 – 14.2)

Mean distance to nearest facility 10.5 km 9.4 km Number of caregivers 719 779

Mode of transport

Walk 78.8

(72.8 - 83.7) 70.5

(63.7 - 76.4)

Motorbike/taxi/bus 17.0

(12.7 - 22.4) 23.0

(17.8 - 29.2)

Other 4.2

(1.7 - 9.9) 6.5

(3.4 - 12.2) Number of caregivers 716 782

Time to nearest facility (among those who go to the facility)

< 30 minutes

5.5 (3.0 - 9.7)

3.3 (1.7 - 6.3)

30 – 59 minutes

5.6 (3.4 - 9.0)

12.4 (8.9 - 17.1)

1 – < 2 hours

24.1 (19.1 - 30.0)

34.3 (28.2 - 41.1)

2 – < 3 hours

43.6 (37.3 - 50.1)

23.9 (20.5 - 27.8)

3 hours or more

21.3 (15.5 - 28.6)

26.0 (19.7 - 33.5)

Mean time to nearest facility

1 hour 58 minutes

1 hour 59 minutes


3.2 Caregiver Knowledge and Their Perceptions of CCM-Trained

HSAs

Caregiver knowledge of childhood illnesses was high at baseline and remained high at endline, as shown

by the indicators in Table 6. Among the illness signs that caregivers stated as reasons to seek treatment

for their child, fever was the most commonly mentioned (approximately 95 percent at baseline and

88 percent at endline). Diarrhea with dehydration (approximately 45 percent in both surveys) and child

vomits everything (approximately 42 percent in both surveys) were the two next most common

responses. A complete list of child illness signs included in the survey questionnaires and responses that

caregivers gave is included in Annex G, Table G1.


Table 6. Caregiver knowledge of childhood illnesses

Caregiver knowledge Baseline Endline


Knows 2+ child illness signs 97.5

(96.1 - 98.4) 95.7

(93.5 - 97.1) 0.0824

Knows 3+ child illness signs 73.8

(69.3 - 77.7) 75.6

(70.9 - 79.8) 0.5506

Knows cause of malaria 90.7

(86.9 - 93.5) 86.0

(82.6 - 88.7) 0.0461

Knows fever is a sign of malaria 85.7

(82.9 - 88.1) 88.4

(85.3 - 90.9) 0.1845

Knows malaria treatment 90.1

(87.0 - 92.6) 95.3

(93.5 - 96.6) 0.0002


As shown in Table 7, the percentage of caregivers who knew that a CCM-trained HSA worked in their

community decreased from 90 percent at baseline to 83 percent at endline (p<0.05). At both baseline

and endline, approximately one-third of caregivers could name at least two curative services that HSAs

offered, with the most common service being to provide treatment for malaria (39 percent at baseline

and 32 percent at endline). A complete listing of HSA activities included in the survey questionnaires and

responses that caregivers gave is included in Annex G, Table G2.

Table 7. Caregiver knowledge of HSA

Caregiver knowledge Baseline Endline


Knows CCM-trained HSA works in community 90.0

(83.3 - 94.2) 83.4

(74.7 - 89.6) 0.0355


Knows location of HSA* 93.4

(87.8 - 96.5) 93.6

(86.2 - 97.1) 0.9523

Knows 2+ HSA curative services* 35.0

(29.6 - 40.9) 34.0

(28.7 - 39.7) 0.7930


*Only asked of caregivers who stated that there was a CCM-trained HSA in their community

Among caregivers who knew that a CCM-trained HSA worked in their community, perceptions of HSAs

as trusted, convenient health care providers of quality services decreased between the baseline and

endline surveys (see Table 8). The reasons for these decreases are unclear. At baseline, HSAs treated

malaria presumptively, meaning that any child presenting with fever received ACT, whereas at endline

HSAs tested children with fever using mRDTs before administering ACT. If HSAs did not have mRDTs

in stock, the child was supposed to be referred to a health center (even if the HSA had ACTs in stock).

It is possible that these shifts in the treatment protocol may have contributed to the perception of

lower-quality services by caregivers who had become used to presumptive treatment.


Table 8. Caregiver perceptions of CCM-trained HSAs

Caregiver perceptions Baseline Endline


View CCM-trained HSAs as trusted health care providers 82.3

(77.5 - 86.2) 70.3

(62.8 - 76.8) 0.0004

Believe CCM-trained HSAs provide quality services 68.4

(63.7 - 72.7) 57.6

(52.3 - 62.7) 0.0007

Cite the CCM-trained HSA as a convenient source of treatment 59.6

(52.5 - 66.3) 47.3

(39.9 - 54.8) 0.0045

Found the CCM-trained HSA at first visit (for all instances of care-seeking included in survey)*

86.5 (79.3 - 91.5)

84.0 (78.2 - 88.4)

0.5414

Total number of caregivers 648 653 * Denominator is 230 caregivers at baseline and 312 caregivers at endline—only those who sought care from an HSA for at least one sick child are included.

3.3 Decision-Making

Among caregivers who were married or living with a partner as if married, there were increases in joint

decision-making indicators over the course of the project (see Table 9). At baseline, 10 percent of

caregivers reported that they decided how to use household income jointly with their partner, and at

endline 39 percent of caregivers reported doing so (p<0.001). Also at baseline, 21 percent of caregivers

reported that they decided when to seek healthcare outside of the home jointly with their partner, and

at endline, 44 percent of caregivers reported doing so (p<0.001). Although joint household-level

decision-making increased over the project implementation period, the percentage of sick child cases for

which the decision to seek care was made jointly by the children’s caregiver and their partner did not

change. Table 10 shows that for nearly half (47 percent) of all sick child cases, caregivers reported that

they made the decision to seek care for their sick child jointly with their partner at baseline. This was

consistent among all three iCCM illnesses, and the percentages at endline were similar.

Table 9. Usual decision-maker in household around income and care-seeking

Decision-maker

Income decisions

p-value

Care-seeking decisions

p-value Baseline Endline Baseline Endline % (CI%) % (CI%) % (CI%) % (CI%)

Caregiver 16.6

(13.5 - 20.3) 11.9

(9.2 - 15.4) 43.8

(38.9 - 48.8) 32.9

(28.0 - 38.1) Caregiver’s husband or partner

72.1 (67.9 - 76.0)

47.1 (41.6 - 52.8)

35.6 (31.1 - 40.3)

23.3 (19.2 - 27.9)

Caregiver and partner jointly

10.0 (7.6 - 13.1)

39.4 (34.0 - 45.1)

0.0000 20.6

(17.2 - 24.5) 43.8

(38.4 - 49.4) 0.0000

Other 1.3

(0.6 - 2.7) 1.5

(0.7 - 3.2) 0.0 0.0

Total number of caregivers

638 662

635 657


Table 10. Joint decision-making to seek care for sick child

Illness Baseline Endline

p-value Baseline

N Endline

N % (CI %) % (CI %)

Overall 47.3

(42.5 - 52.1) 46.4

(41.0 - 52.0) 0.8063 1,115 1,223

Fever 48.6

(42.8 - 54.5) 47.9

(41.4 - 54.5) 0.8569 401 486

Diarrhea 46.0

(39.5 - 52.6) 44.1

(37.7 - 50.8) 0.6601 322 324


(41.6 - 52.3) 46.5

(40.4 - 52.7) 0.9102 392 413

3.4 Care-Seeking

Care-seeking from an appropriate provider (hospital, health center, health post, nongovernmental

organization center, or HSA) increased slightly between baseline and endline, but the change was not

statistically significant (see Table 11). However, the percentage of sick child cases in which caregivers

sought care first from an HSA increased significantly between baseline (26 percent) and endline (33

percent) (p<0.05). The increases across the three illnesses were consistent—approximately 7 to 9

percentage points—although only the increase for care-seeking for cases of cough with difficult or fast

breathing was statistically significant (p<0.05).

Table 11. Care-seeking behavior among all sick child cases

Illness

Sought care from appropriate provider*

p-value

HSA was first source of care

p-value Baseline

N Endline

N Baseline Endline Baseline Endline

% (CI %) % (CI %) % (CI %) % (CI %)

Overall 65.6

(60.7 - 70.1) 70.0

(65.4 - 74.2) 0.0740

25.7 (20.2 - 32.1)

33.4 (27.1 - 40.3)

0.0278 1,260 1,447

Fever 70.3

(64.4 - 75.6) 73.9

(68.9 - 78.4) 0.2575

26.4 (20.2 - 33.6)

34.0 (27.2 - 41.5)

0.0547 455 571

Diarrhea 64.0

(57.9 - 69.7) 69.8

(63.9 - 75.0) 0.1202

30.8 (24.0 - 38.5)

37.5 (30.5 - 45.1)

0.0925 364 387

Cough with difficult or fast breathing

61.9 (55.5 - 67.9)

65.6 (59.8 - 71.1)

0.2465 20.9

(15.5 - 27.5) 29.5

(23.2 - 36.6) 0.0246 441 489

* Appropriate providers included hospital, health center, health post, nongovernmental organization center, and HSA

Among cases of illness for which caregivers sought any care, those who went to an HSA first increased

significantly between baseline and endline for all three illnesses (see Table 12), with increases ranging

from 10 to almost 12 percentage points. Figure 1 shows where care was sought for sick child cases in

which any care was sought. Traditional practitioners and “other” sources were omitted from the figure

because when combined they accounted for less than 5 percent of responses for both source of care

and first source of care. The figure highlights the increase in care-seeking from HSAs at endline and

corresponding decreases in care-seeking from public facilities and stores/pharmacies.


Table 12. Care-seeking behavior among those who sought any care

Illness

HSA was first source of care among those who sought any care

p-value Baseline

N Endline

N Baseline Endline

% (CI %) % (CI %)

Overall 30.1

(23.7 - 37.4) 40.5

(33.2 - 48.2) 0.0123 1,076 1,194

Fever 29.3

(22.5 - 37.2) 39.2

(31.6 - 47.4) 0.0290 409 495

Diarrhea 38.6

(30.3 - 47.7) 48.5

(40.0 - 57.1) 0.0362 290 299


24.4 (18.2 - 31.9)

36.0 (28.6 - 44.2)

0.0114 377 400

Figure 1. Care-seeking sources among those who sought care

As shown in Table 13, the percentage of illness cases in which caregivers did not seek care for their sick

child did not significantly change from baseline (14.6 percent) to endline (17.5 percent). At endline, the

most commonly cited reason for not seeking any care6 was that the caregiver did not believe that the

illness was serious (30 percent). The two other most common responses were that caregivers did not

have money (21 percent) or could treat the condition at home or with medicines already on hand (22

percent). Other responses included 15 percent who said that the place of care was too far, 13 percent

who said that the condition passed, and 7 percent who said that they did not have the time. Annex G,

Table G3, contains a complete list of reasons caregivers did not seek care from any source.

The percentage of illness cases in which caregivers sought care but sought care from a source other

than an HSA decreased between baseline (68 percent overall) and endline (59 percent overall) (p<0.05).

This almost 10 percentage point decrease may be primarily explained to the significant increase in care-

seeking from an HSA for cases of cough with difficult or fast breathing (see Table 13). Among those who

6 This question was only included in the endline survey; caregivers were allowed to give multiple responses.

45

8

3225

43

12

41

17

39

5

3023

35

9

41

15

Public facility Private clinic HSA Store, pharmacy ormarket

Per

cen

tage

of

sick

ch

ild c

ases

Source of care - baseline Source of care - endline

First source - baseline First source - endline


sought care but did not go to an HSA at endline,7 the majority (80 percent) stated that they preferred to

go to another provider. The next most common reasons cited were that the HSA was not available (18

percent) and that the HSA was too far away (5 percent). Few caregivers indicated that they thought the

condition was too serious (3 percent), that the HSA did not have medicines or supplies (1 percent), or

that they did not trust the HSA to provide care (1 percent). Annex G, Table G4, contains a complete

list of reasons caregivers did not seek care from any source.

Table 13. Did not seek care or sought care from sources other than HSA

Illness

Did not seek care Sought care but not

from HSA

Baseline % (CI %)

Endline % (CI %)

p-value Baseline % (CI %)

Endline % (CI %)

p-value

Overall 14.6

(11.9 - 17.8) 17.5

(14.9 - 20.4) 0.0874

68.3 (60.8 - 75.0)

59.1 (51.3 - 66.4)

0.0277

Fever 10.1

(7.3 - 13.9) 13.3

(10.4 - 17.0) 0.1668

69.2 (61.0 - 76.3)

60.4 (52.1 - 68.2)

0.0524

Diarrhea 20.3

(15.7 - 25.9) 22.7

(18.5 - 27.6) 0.4947

59.7 (50.7 - 68.1)

51.2 (42.6 - 59.7)

0.0752


14.5 (10.8 - 19.3)

18.2 (15.0 - 21.9)

0.0844 74.0

(65.8 - 80.8) 63.3

(54.9 - 70.8) 0.0266

Total number of sick child cases

1,260 1,447 1,076 1,194

3.5 Assessment

The percentage of fever cases in which blood was taken for testing increased significantly between

baseline and endline, both among all fever cases and among fever cases managed by an HSA at a village

clinic (see Table 14). mRDTs were not available for HSAs to use at village clinics at the time of the

baseline survey; at baseline, cases of fever received presumptive malaria treatment. mRDTs were

gradually rolled out as part of the iCCM program in the RAcE project districts in 2014 and 2015. Thus

among cases managed by an HSAs at a village clinics at baseline, none of the 126 fever cases for which

care was sought from an HSA had blood drawn. At endline, approximately 60 percent of fever cases

were tested, both by any provider and by HSAs at village clinics. It is important to note, though, that

studies have shown caregiver recall of malaria diagnostic testing to be poor, so the assessment

indicators should be interpreted with caution.8

Although the percentage of fever cases tested for malaria improved between baseline and endline, about

40 percent of cases managed by HSAs at endline did not receive an mRDT. The HSA survey results

show that most HSAs had mRDTs in stock at the time of the survey (89 percent) and that stockouts of

mRDTs in the previous month was also not a large issue (13 percent HSAs had stockout of mRDTs)

(see Annex H), suggesting that mRDT stockouts is only part of the explanation for the relatively low

percentage of cases of fever tested.

When a malaria diagnostic test was given at endline, in most cases (approximately 97 percent),

caregivers received the result of the blood test from the provider, and approximately three-quarters of

the test results were reported to be positive for malaria. Among fever cases that had a positive test

7 This question was only included in the endline survey; caregivers were allowed to give multiple responses. 8 The Maternal and Child Health Integrated Program. 2013. Indicator Guide: Monitoring and Evaluating Integrated

Community Case Management.


result at endline, the majority received ACT (92 percent overall and 90 percent of cases managed by

HSAs).

Although HSAs are not supposed to provide ACTs to children aged 2–4 months with fever, they are

supposed to administer an mRDT and refer to a health facility. Among the 14 fever cases in which care

was sought from an HSA for children aged 2–4 months at endline, 6 caregivers reported that their child

had blood drawn. Of these, 5 caregivers received the result of the test, and all 4 fever cases that tested

positive for malaria received ACT from the HSA. In addition, one fever case for a child under five

months who did not have blood taken received ACT from an HSA. Neither of the two fever cases

among children aged 2–4 months for which care was sought from an HSA at baseline were referred to a

health facility by the HSA, and only 1 of 12 fever cases among children aged 2–4 months was referred at

endline.

Table 14. Malaria assessment among children with fever

Fever assessment

Cases managed by HSA at village clinic

p-value All cases

p-value Baseline Endline Baseline Endline

% (CI %) % (CI %) % (CI %) % (CI %)

Child had blood drawn* 0 61.7

(52.7 - 70.0) 0.0000

35.6 (30.0 - 41.7)

59.0 (53.7 - 64.2)

0.0000

Caregiver received result of blood test

na 98.4

(93.3 - 99.6) na

96.9 (92.6 - 98.7)

97.3 (95.0 - 98.6)

0.7610

Blood test positive for malaria na 79.8

(70.6 - 86.7) na

77.7 (69.9 - 84.0)

74.4 (69.1 - 79.1)

0.4020

Received ACT among those who had a positive blood test result

na 89.5

(79.8 - 94.8) na

84.4 (77.0 - 89.8)

92.2 (87.7 - 95.2)

0.0365

Total number of fever cases 126 196 455 571 na = not applicable *For cases in which child had blood drawn among cases managed by HSA, only cases in which the caregiver reported the test being done by an HSA at the village clinic were included in the numerator. Three caregivers reported that their children had blood taken by an HSA at a village clinic in the baseline survey, but Save the Children Malawi confirmed that this was not possible because malaria blood tests were not available at that time.

Among cases of cough with difficult or fast breathing, there was a statistically significant increase in the

percentage that had their respiratory rate assessed comparing baseline to endline, both among all cases

and among cases managed by an HSA at a village clinic (p<0.001) (see Table 15). The overall increase in

assessment of respiratory rate by any provider was driven by the large increase respiratory rate

assessment by HSAs. At baseline, 27 percent of cases of cough with difficult or fast breathing that had

their respiratory rate assessed had it done at by an HSA at a village clinic, and over the course of the

project this increased to 45 percent. Conversely, the percentage of cases that had their respiratory rate

assessed at a government hospital decreased, from 62 percent at baseline to 46 percent at endline.

Annex G contains tables with the location (Table G5) and provider (Table G6) of sick child assessments.


Table 15. Fast breathing assessment

Respiratory rate assessment

Cases managed by HSA at village clinic

p-value All cases

p-value Baseline Endline Baseline Endline % (CI %) % (CI %) % (CI %) % (CI %)

Respiratory rate assessed 31.0

(22.4 - 41.2) 56.1

(46.4 - 65.4) 0.0004

25.6 (20.6 - 31.4)

38.5 (33.5 - 43.7)

0.0007

Total number of cough with difficult or fast breathing cases

100 148 441 489

3.6 Treatment Coverage

Appropriate treatment for fever is defined as receiving ACT the same day or day after the fever started

among children aged 5–59 months who had a positive malaria diagnostic test result for treatment

provided by all providers at endline and by all providers except HSAs at baseline. At baseline,

presumptive malaria treatment by an HSA was considered appropriate because that was the policy at

the time. According to national iCCM policy, HSAs can give children aged 2–4 months with fever an

mRDT, but they are supposed to refer them to a health facility for treatment. Appropriate treatment

for diarrhea was considered receiving both ORS and zinc, and appropriate treatment for cough with

difficult or fast breathing was considered receiving cotrimoxazole at baseline and amoxicillin at endline.

As with the fever assessment indicators, the appropriate treatment coverage indicators should be

interpreted with caution. The overall and fever indicators include confirmed malaria cases, and as stated

in the assessment section, caregiver recall of malaria diagnostic testing has been shown to be poor. In

addition, the HSA protocol for malaria treatment at endline was different from that at baseline.

Furthermore, pneumonia treatment, for which the cough with difficult or fast breathing appropriate

treatment indicator is a proxy, is globally recognized to have validity issues because diagnosis of

presumptive pneumonia is often inaccurate in comparison with a clinical diagnosis of pneumonia at

health facilities.9 Therefore, the number of cases of cough with difficult or fast breathing is likely an

overestimate of actual clinical pneumonia cases, and the percentage of these treated with amoxicillin

can, and should, reasonably not be 100 percent.

As shown in Table 16, among all sick child cases, appropriate treatment coverage did not change

significantly from baseline (43 percent) to endline (47 percent). Likewise, appropriate treatment

coverage of diarrhea cases and fever cases did not change over the course of the project, but

appropriate treatment of cases of cough with difficult or fast breathing increased significantly, from 53

percent at baseline to 62 percent at endline (p<0.05). The small non-significant decreases in the

appropriate fever treatment indicators may be related to the introduction of mRDTs, which impacted

the measurement of all appropriate fever treatment indicators as well as the overall appropriate

treatment indicators. Among cases of illness for which care was sought from an HSA, there were not

9 Campbell H, el Arifeen S, Hazir T, O'Kelly J, Bryce J, Rudan I, et al. 2013. Measuring coverage in MNCH:

Challenges in monitoring the proportion of young children with pneumonia who receive antibiotic treatment. PLoS

Med, 10(5): e1001421. doi:10.1371/journal.pmed.1001421


any statistically significant increases in appropriate treatment coverage by an HSA when comparing

baseline to endline (see Table 17).

Table 16. Appropriate treatment coverage among all sick child cases

Illness (treatment)

Received appropriate treatment from HSA p-

value

Received appropriate treatment p-

value Baseline

N Endline

N Baseline Endline Baseline Endline % (CI %) % (CI %) % (CI %) % (CI %)

Overall 13.9

(10.3 - 18.6) 16.6

(12.6 - 21.5) 0.3085

42.7 (38.2 - 47.2)

47.1 (43.3 - 51.0)

0.0720 1,020 1,114

Fever (ACT same or next day)*

29.3 (21.9 - 37.9)

24.8 (17.4 - 34.1)

0.3708 61.9

(54.8 - 68.4) 59.2

(52.5 - 65.7) 0.5721 215 238

Diarrhea (ORS and zinc)

7.1 (4.3 - 11.6)

10.6 (7.2 - 15.4)

0.1828 18.4

(13.8 - 24.1) 21.2

(16.9 - 26.3) 0.3976 364 387

Cough with difficult or fast breathing (cotrimoxazole/ amoxicillin)

12.0 (8.2 - 17.3)

17.4 (13.4 - 22.3)

0.0922 53.3

(47.3 - 59.2) 61.8

(56.4 - 66.9) 0.0165 441 489

*Appropriate fever treatment includes presumptive malaria treatment at baseline by HSAs, confirmed malaria treatment at endline by HSAs, confirmed malaria treatment by all other providers at baseline and endline. Presumptive treatment includes cases in which ACT was given but no there was no finger prick or heel stick. Confirmed malaria treatment includes cases in which ACT was given, there was a finger or heel stick, and the result of the test was positive. Appropriate treatment for fever cases was restricted to include only children aged 5–59 months.

Table 17. Appropriate treatment coverage among those who sought care from an HSA

Illness (treatment) Baseline Endline

p-value Baseline N Endline N % (CI %) % (CI %)

Overall 46.1

(39.2 - 53.2) 45.9

(39.8 - 52.1) 0.9635 308 401

Fever (ACT same or next day) * 67.7

(58.1 - 76.1) 54.6

(43.7 - 65.1) 0.0679 93 108


(14.1 - 33.3) 27.4

(20.0 - 36.3) 0.4207 117 146

Cough with difficult or fast breathing (cotrimoxazole/amoxicillin)

54.1 (41.2 - 66.5)

57.8 (50.8 - 64.5)

0.6284 98 147


In addition to treatment with ORS and zinc, diarrhea cases should receive continued fluids and feeding

during the illness, and HSAs and other health providers are trained to counsel providers accordingly.

Among cases of diarrhea, approximately 50 percent were offered the same amount or more to drink,

and approximately 35 percent were offered the same amount or more to eat at both baseline and

endline (see Annex G, Table G7).

Because the iCCM fever assessment and malaria treatment protocol changed with the introduction of

mRDTs, additional analyses were conducted to look at treatment with ACT when malaria diagnostic

test results were reported to be positive and reported to be negative, and also when no diagnostic test

was given. These are not standard indicators, and have validity issues including poor caregiver recall as

described above. These results are provided in Annex G, Table G8.


Annex G also includes tables that detail treatments taken for diarrhea (Table G9), fever (Table G10),

and cough with difficult or fast breathing (Table G11) and source of ACT (Table G12), ORS (Table

G13), zinc (Table G14), and cotrimoxazole/amoxicillin (Table G15).

3.7 First Dose of Treatment and Counseling from HSA

As shown in Table 18, there was not a significant increase in the percentage of cases of illness provided

the first dose of treatment in presence of an HSA, but the increase in cases of fever provided the first

dose of treatment in presence of an HSA was statistically significant (p<0.05).

Table 18. First dose of treatment in presence of HSA

Illness (treatment)

First dose received in presence of HSA

p-value Baseline

N Endline

N Baseline Endline % (CI %) % (CI %)

Overall* 37.3

(27.4 - 48.4) 49.4

(41.9 - 56.8) 0.0531 153 231

Fever (ACT)** 39.2

(29.6 - 49.7) 56.2

(45.1 - 66.7) 0.0209 74 105

Diarrhea (ORS) 31.7

(24.9 - 39.4) 32.5

(23.6 - 42.8) 0.8937 101 117

Diarrhea (zinc) 36.7

(21.3 - 55.3) 27.9

(16.6 - 43.0) 0.3805 30 43

Diarrhea (ORS and zinc)*** 23.1

(11.8 - 40.3) 22.0

(11.7 - 37.3) 0.9056 26 41


41.5 (25.0 - 60.2)

54.1 (43.9 - 64.0)

0.2539 53 85

* Overall calculation includes confirmed malaria (ACT), diarrhea (ORS and zinc), and cough with difficult or fast breathing (cotrimoxazole/amoxicillin) ** Baseline includes presumptive treatment, which was the policy at the time *** Includes only cases in which child received both ORS and zinc

As shown in Table 19, among sick child cases that received treatment from an HSA, all caregivers

received counseling on how to administer the medicine to their children from the HSA at baseline, and

almost all (97 percent) of caregivers received this counseling at endline.

Table 19. Counseling on treatment administration by HSA

Illness (treatment)

Counseled on treatment administration

p-value Baseline

N Endline

N Baseline Endline % (CI %) % (CI %)

Overall* 100 97.8

(94.0 - 99.2) 0.1369 153 231

Fever (ACT)** 100 99.1

(93.0 - 99.9) 0.4176 74 105

Diarrhea (ORS) 98.0

(86.8 - 99.7) 99.2

(94.0 - 99.9) 0.5384 101 117

Diarrhea (zinc) 100 95.4

(82.5 - 98.9) 0.2234 30 43

Diarrhea (ORS and zinc)*** 100 95.1

(81.7 - 98.8) 0.2467 26 41


100 97.7

(90.7 - 99.4) 0.2751 53 85

* Overall calculation includes confirmed malaria (ACT), diarrhea (ORS and zinc), and cough with difficult or fast breathing (cotrimoxazole/amoxicillin) ** Baseline includes presumptive treatment, which was the policy at the time *** Includes only cases in which child received both ORS and zinc


3.8 Referral Adherence

Among sick child cases for which care was sought from an HSA, 79 of 340 cases of illness were referred

to a health facility by an HSA at baseline (23 percent), and 101 of 489 cases of illness were referred to a

health facility by an HSA at endline (21 percent). Of those referred, there was no change in referral

adherence over the project implementation period; approximately 88 percent adhered to the referral

advice at both baseline and endline (see Table 20).

Table 20. Caregiver adherence to HSA referral


p-value Baseline

N Endline

N % (CI %) % (CI %)

Overall 88.6

(77.6 - 94.6) 87.1

(80.0 - 92.0) 0.7981 79 101

Fever 93.1

(74.5 - 98.4) 80.0

(67.8 - 88.4) 0.1431 29 40

Diarrhea 87.1

(64.0 - 96.2) 92.6

(73.9 - 98.2) 0.5320 31 27


84.2 (58.2 - 95.3)

91.2 (75.6 - 97.2)

0.4568 19 34

At baseline, the most common reason that caregivers cited for not adhering to the HSA’s referral was

that the child improved (78 percent of sick child cases). At endline, the most common reasons that

caregivers cited for not adhering to the HSA’s referral were that the child improved (46 percent of sick

child cases) and that they did not have money (31 percent of sick child cases). Annex G, Table G16,

contains a complete list of reasons caregivers did not adhere to the HSA’s referral.

3.9 Sick Child Follow-Up

According to the national iCCM protocol, HSAs are to encourage caregivers to return for follow-up

within three days after the initial consultation. Among sick child cases for which care was sought from an

HSA, approximately 22 percent returned to the HSA for a follow-up visit after the initial sick child

consultation at baseline and endline (see Table 21). Thus there was no change over the project

implementation period. It is important to note that the children included in the survey were sick

sometime during the two weeks preceding the caregiver’s interview, so they may not have yet returned

for follow-up by the time of the survey.

Of those sick child cases taken for follow-up with an HSA at baseline, most followed up three days after

the initial consultation (35 percent); otherwise the timing of the visits varied from one day to more than

five days after the initial consultation. At endline, children were most commonly taken for follow-up two

days (31 percent) or three days (25 percent) after the initial consultation. Annex G, Table G17, contains

a complete list of when follow-up visits occurred.

Table 21. Sick child follow-up


p-value Baseline N Endline N % (CI %) % (CI %)

Overall 21.6

(15.2 - 29.8) 22.7

(16.8 - 29.9) 0.7784 236 309

Fever 20.6

(14.3 - 28.8) 19.9

(15.3 - 25.4) 0.8419 126 196

Diarrhea 20.7

(13.7 - 30.0) 23.3

(17.0 - 31.0) 0.6044 116 146


Cough with fast breathing 16.3

(10.1 - 25.4) 22.5

(16.0 - 30.5) 0.1977 98 147

3.10 Illness Management and Diagnostics by Sex

Endline data for care-seeking and treatment of fever, diarrhea, and cough with difficult or fast breathing

were disaggregated by sex. The following four results showed statistically significant differences between

males (boys) and females (girls):

Caregivers were more likely to seek any care for girls with diarrhea (81 percent) than for boys with

diarrhea (74 percent) (p<0.05).

Caregivers were more likely to seek care from an appropriate provider for girls with fever

(77 percent) than for boys with fever (71 percent) (p<0.05).

Girls with fever were more likely to have their blood taken to test for malaria (62 percent) than

boys with fever (56 percent) (p<0.05).

Boys with a positive malaria diagnostic test result were more likely to receive ACT the same day or

day after the onset of fever (65 percent), compared to girls with a positive malaria diagnostic test

result (54 percent) (p<0.05).

The complete sex-disaggregated result tables can be found in Annex F.


4 DISCUSSION

When RAcE started in 2013, iCCM was already well-established across Malawi. As of September 2011,

3,296 HSAs had completed iCCM training from an estimated 3,452 HTRAs targeted for iCCM by the

MOH.10 However, the MOH-led program faced challenges supporting HSAs with supplies and

supervision, and there was a need to expand iCCM services to more communities and to update the

iCCM protocol to align with WHO recommendations for management of fever and suspected

pneumonia. The RAcE project supported this expansion by training additional HSAs in iCCM who were

located in areas between five and eight km from a health facility. RAcE also supported the MOH to

introduce mRDTs at village clinics and to replace cotrimoxazole with amoxicillin as first-line treatment

for pneumonia.

The 2016 RAcE endline survey results show significant increases in indicators measuring HSAs as the

first source of care for cases of cough with difficult or fast breathing, malaria testing, and respiratory

rate assessment over the course of the project. The baseline survey, however, was not a “true”

pre-iCCM baseline; more than 400 CCM-trained HSAs were already working in the project districts at

the time of the baseline survey, so we cannot expect to see increases that might accompany the

introduction of iCCM services over the course of the project. Furthermore, the survey results were

likely diluted because iCCM services were not available in all 60 clusters surveyed at endline. Save the

Children was unable to implement RAcE activities in all HTRAs of their project districts as initially

planned because several HSA posts were vacant, and some district managers did not allow HSAs who

were not residents of their catchment areas to attend iCCM trainings or to provide iCCM services.

Therefore, the endline survey data were explored further through sub-analyses of the 33 clusters

confirmed to have an active CCM-trained HSA (referred to as active clusters) and the 27 clusters

confirmed not to have an active CCM-trained HSA at endline (referred to as inactive clusters).11

The survey results show that caregiver perceptions of HSAs as trusted sources of care and providers of

high-quality care decreased over the course of the project. However, in the 33 active clusters, the

endline results were similar to the baseline results, indicating that there was no change in the

perceptions of HSAs as trusted sources of care and providers of high-quality services over the project

implementation period. It follows that the presence of a CCM-trained HSA in a community is related to

perceptions of trust in HSAs, but it is a topic worth investigating further to understand what factors are

contributing to the lowered confidence in the quality of care provided by HSAs. The HSA survey results,

for example, indicate that iCCM services are not regularly available in many areas where HSAs trained in

iCCM work. Although most HSAs interviewed (94 percent) met the MOH definition for functionality

(providing iCCM services in last month and providing iCCM at least two days per week), only

26 percent were providing regular iCCM services (residing in their catchment areas, providing iCCM

services in the last month, and providing iCCM services at least 5 days per week). Across the full survey

sample (including areas known not to have an active CCM-trained HSA), only 20 percent of clusters had

10 Nsona et al. 2012. Scaling up integrated community case management of childhood illness: Update from Malawi.

Am. J. Trop. Med. Hyg., 87(Suppl 5), 54–60. 11 Confirmation was obtained through a mapping exercise that Save the Children conducted in January 2017.


access to a resident HSA providing iCCM at least 5 days per week, and 70 percent had access to an

HSA providing iCCM at least 2 days per week (see Annex H for details).

Care-seeking from an appropriate provider did not change over the course of the project among all

cases of illness (approximately 70 percent at both baseline and endline), with 41 percent of cases seeking

care from an HSA at endline (55 percent in active clusters, 23 percent in inactive clusters). Among cases

of illness for which care was sought, but not from an HSA, 80 percent of caregivers reported a

preference for another provider. This finding is consistent across the full survey sample and sub-analyses

of active and inactive clusters. The reasons why caregivers prefer providers other than HSAs require

further exploration.

The percentage of cases for which caregivers sought care from an HSA first among those who sought

any care increased significantly for all three iCCM illnesses (p<0.05). At endline, HSAs were the first

source of care for 41 percent of cases of illness for which care was sought (54 percent in active clusters,

23 percent in inactive clusters), indicating that if caregivers sought care from an HSA, the HSA was

almost always the first source of care.

In terms of illness assessment, survey results show improvements in the assessment of fever cases for

malaria and of cough with difficult or fast breathing cases for high respiratory rate for age. The

percentage of fever cases that were tested for malaria nearly doubled over the course of the project,

from 36 percent at baseline to 59 percent at endline for all fever cases, with HSAs performing more

than a third of all tests (37 percent). The majority of caregivers received the results of the test, and

nearly all fever cases that tested positive for malaria received ACTs at endline (89 percent).

The protocol for fever management changed during the project implementation period with the

introduction of mRDTs, and thus appropriate fever treatment was different at endline than it was at

baseline, which makes interpretation of this indicator difficult. On the whole, however, results suggest

improved management of fever cases, with statistically significant increases from baseline to endline in

the percentage of fever cases tested for malaria and the percentage of mRDT-positive fever cases that

received ACTs, as well as significant reductions in the percentage of mRDT-negative fever cases that

received ACTs (see Annex G, Table G8).

Although the use of mRDTs increased between baseline and endline, presumptive treatment of malaria

by all providers was still reported at endline. At endline, about 30 percent of all fever cases for which

care was sought and 38 percent of fever cases managed by HSAs did not have a malaria diagnostic test

performed. Among fever cases managed by HSAs but not tested using an mRDT, 26 percent still

received ACTs. Results of the HSA survey showed that 89 percent of HSAs had mRDTs in stock at the

time of interview, and 87 percent had not experienced a stockout of mRDTs in the month before the

survey, suggesting that stockouts of mRDTs were likely not the reason for presumptive treatment. It is

possible that HSAs may have felt pressure to provide ACT treatment for fever from caregivers as was

done under the old iCCM protocol. Limitations of caregiver recall may also contribute to this finding.

The percentage of cases of cough with difficult or fast breathing that had their respiratory rate assessed

increased significantly, from 26 percent at baseline to 39 percent at endline for all cases (p<0.001), and

from 30 percent at baseline to 56 percent at endline for cases managed by HSAs (p<0.001).

Furthermore, of cases of cough with difficult or fast breathing that received cotrimoxazole or amoxicillin

from an HSA, 45 percent had their respiratory rate assessed by an HSA at baseline, and 60 percent had

their respiratory rate assessed by an HSA at endline. The endline percentage is positive sign, because


respiratory rate assessment by HSAs was a focus of the project, but this should be interpreted with

caution because of the small sample size (53 cases at baseline and 85 cases at endline).

Appropriate treatment coverage of sick child cases increased but not significantly from baseline to

endline for all cases and for cases managed by HSAs. Overall, appropriate treatment of sick child cases

by HSAs is low; 17 percent of all sick child cases received appropriate treatment from an HSA at

endline. Sub-analyses show appropriate treatment from an HSA was, as expected, higher in active iCCM

clusters (23 percent) and lower (only 9 percent) in clusters where HSAs were not providing iCCM

services. These findings indicate that, where active, HSAs provide a larger percentage of total

appropriate treatment. Among those that sought care from an HSA, approximately 45 percent reported

receiving appropriate treatment from the HSA. These findings were consistent across both the active

and inactive clusters.

Appropriate treatment coverage for diarrhea (5 percent at baseline and 7 percent at endline) continues

to lag far behind the treatment for other illnesses targeted by iCCM. Provision of zinc was the limiting

factor in providing appropriate treatment, and many more cases of diarrhea received ORS regardless of

source of care. Although caregivers reported that their child received ORS in approximately 70 percent

of diarrhea cases, the percentage of caregivers who reported that their child received zinc was much

lower (only 21 percent of diarrhea cases at baseline and 24 percent of diarrhea cases at endline). The

HSA survey shows that most HSAs had zinc in stock at the time of the survey (83 percent) and few

reported stockouts in the month before the survey (19 percent). The reasons for low provision of zinc

by HSAs are unclear, but Save the Children Malawi staff noted that HSAs and health facility staff may not

consider zinc an essential drug for treatment of diarrhea; providers seem to give zinc as a supplement

and not necessarily as treatment. HSAs, therefore, likely do not prioritize giving zinc when treating

children with diarrhea. Further follow-up with HSAs, health facility staff, and community members would

be helpful to better understand the barriers to appropriate treatment for diarrhea.

Among fever cases managed by HSAs, the survey results show an improvement in the provision of the

first dose of ACT in the presence of an HSA (p<0.05), and counseling on treatment administration

remained high (at or close to 100 percent) for all three illnesses. Caregiver adherence to HSA referrals

and follow-up after an initial HSA consultation did not change over the course of the project. Adherence

to referrals made by HSAs was high at both baseline and endline, with caregivers reporting completing

referrals as recommended in more than 85 percent of cases. In contrast, at both baseline and endline,

less than 25 percent of caregivers returned to HSAs for follow-up as recommended in the national

iCCM protocol.

Many areas targeted for iCCM at baseline, as RAcE was beginning, ultimately did not gain access to

iCCM by the time of the endline survey; only 33 (55 percent) of surveyed clusters had an active

CCM-trained HSA present. Furthermore, the HSA survey revealed that only a quarter of HSAs

providing iCCM services met the strict definition of functionality: being a resident in their catchment

areas and providing iCCM at least five days per week. Sub-analysis of the 33 clusters with active

CCM-trained HSAs showed higher levels of care-seeking from HSAs and more positive perceptions of

services provided by HSAs, compared to the 27 clusters without active CCM-trained HSAs at the time

of the endline survey. Addressing these HSA deployment issues, however, will require dealing with

issues beyond the control of the MOH IMCI unit, which does not manage the broader HSA program.


Despite iCCM being a mature program in Malawi, large service gaps remain due to the absence of fully

functional CCM-trained HSAs in eligible communities. Implementation of the RAcE project in Malawi will

soon be winding down, and the MOH will continue to implement iCCM services on its own. The

findings of the household and HSA surveys highlight the importance of ensuring that HSAs are deployed

in HTRAs, that they are trained in iCCM, and also that they are available at their village clinics so that

caregivers can access their services. Going forward, the MOH and partners need to find ways to ensure

the availability of HSAs at their village clinics and maintain the quality of their services. They need to

better understand why caregivers prefer seeking care from providers other than HSAs when their

children are sick. The findings also show that there are some illness management patterns that need to

be explored and better understood, including why HSAs do not prescribe zinc more often and why

HSAs and health facility staff are not using malaria diagnostic tests more often to assess cases of fever.


ANNEX A. LIST OF KEY PERSONS INVOLVED IN THE SURVEY

Name Organization Role

1. Emmanuel Chimbalanga Save the Children Malawi Survey coordinator

2. George Kasawala Save the Children Malawi RAcE project manager

3. Gomezgani Jenda Save the Children Malawi RAcE senior child health advisor

4. Enoce Nyanda Save the Children Malawi Data collector trainer and field work supervisor

5. Humphreys Nsona MOH, IMCI Provider of overall leadership

6. Fannie Kachale MOH, RHD Provider of technical input on community-based maternal and newborn care survey component

7. Tiope Mleme NSO Data collection coordinator

8. Lewis Gombwa NSO Data quality assurance coordinator and data entry lead

9. Kirsten Zalisk ICF Provider of remote technical support

10. Lwendo Moonzwe ICF Provider of in-country technical support

11. Debra Prosnitz ICF RAcE project manager


ANNEX B. ENDLINE SAMPLE

The table in this annex contains the endline survey clusters, along with the district, traditional authority,

enumeration area and villages associated with each – as well as the number of households listed in each

cluster. The iCCM implementation status of the cluster is listed in the last column. The status

sometimes varies by village within a cluster; if the status is the same for the entire cluster, it list listed

once, but if the status varies, it is listed for each village. Implementation status is defined as follows:

Yes: there is an active CCM-trained HSA

No – Vacant: there is not an active CCM-trained HSA, and the HSA post is vacant

No – HSA: there is not an active CCM-trained HSA, but there is an HSA

Yes but transferred: there was an active CCM-trained HSA, likely within the past year but had been

transferred by the time of the endline survey

The same clusters were used in the baseline survey but the number of households listed in each cluster

and the implementation status of the cluster may have been different at the time of the baseline survey.

Table B1. Endline survey cluster information

District Traditional Authority

EA Cluster Villages Households Listed

Implementation status

Mzimba TA Mtwalo 3 1 Mwelekete Wankhama Kumwenda

145 Yes

Mzimba TA Mtwalo 31 2 Jacob Chakuluntha Kalama Estate N’dili Nthembe ya Mwana

266 Yes but transferred

Mzimba TA Mtwalo 48 3 Saulosi Mofat Shadreck Makwakwa


Mzimba TA Mtwalo 51 4 Longwe Residence Makhetani Singini Mkopeka Khowoya Msekeni Nkabelani Yesaya Chinombo Jere

278 No – Vacant

Mzimba TA Mtwalo 67 5 Bich Moyo Jalani Khongolo Paulosi Khongolo

230 No – Vacant

Mzimba TA Mtwalo 95 6 Kabindula Nkhonjera Mabwanya Liche Muntwani Hara Nyandolo Ziba Safari Ziga Tembo

149 Yes

Mzimba TA Mtwalo 100 7 David Sibande Mateyu Ng’oma Muhlolo Ndolo

131 Yes

Mzimba TA Mpherembe 21 8 Chiminyira Bota Kalema Estate Mtambalika Nkhawanawo Estate Wombe Bota

204 Yes





Mzimba TA Mpherembe 38 9 Chauluma Nyirenda Chibula Mandhlopa Chilinkhu Farm Hannock Botha Langa Mgemezulu Nemoni Mlotha Sandres Mlotha

275 Yes

Ntchisi TA Chikho 2 10 Chibwenje Chipokosa Katola Masache Mtongo Ndudu Nyanga

400 Yes No – Vacant Yes Yes No – Vacant Yes Yes

Ntchisi TA Chikho 8 11 Masache 216 Yes

Ntchisi TA Kalumo 3 12 Bingamvula Chimbalu Chiopsa Kalasamkuwa

279 Yes No – HSA No – HSA Yes

Ntchisi TA Kalumo 30 13 Chithonje Kachelenga Kachilanduzi Kapichila Kasakula Lambulira Machira Maguya Makwesa Maluwa Mbuluma Mwamulo

605 No – HSA No – HSA Yes No – HSA No – HSA No – HSA No – HSA No – HSA No – HSA No – HSA No – HSA No – HSA

Ntchisi TA Kalumo 59 14 Chapuchapu Chawanda Mkambisi Mphanda

249 No – Vacant

Ntchisi STA Chilooko 8 15 Kavulala Liwenga Mkwindo

144 No – HSA No – HSA No – Vacant

Ntchisi STA Chilooko 14 16 Chisamba Mankhaka Mndesi Mndesi Farm

229 Yes

Ntchisi STA Chilooko 32 17 Kafulu Mateche Mayembe

189 No – HSA

Ntchisi STA Chilooko 40 18 Chankhozi Estate Chimbili Kandale

210 Yes

Ntchisi STA Chilooko 47 19 Lumbe Malambo M’njale Mwinama Nduwa Nsulu

325 No – HSA No – HSA No – HSA Yes No – HSA No – HSA





Dedza TA Pemba (now TA Kachere)

39 20 Chingalunyamuka Bamusi Mkwaila Ndinga Willie Themuka

391 Yes

Dedza STA Chilikumwendo 29 21 Chidewere Trading Centre Chimkokota Kaluzi Kumalawi Kumtengo Mkwezalamba Mwambula Mzumazi Wandawanda

148 Yes

Dedza STA Chilikumwendo 49 22 Chimodzi Chipeni Magomero Trading Centre Moses Rufesi


Dedza TA Kaphuka 14 23 Falikile Kamkodo Mkanda Mngongonda Zakalamba

264 Yes

Dedza TA Kaphuka 31 24 Chipampha Mlamba Mlinga Nkhanganya

367 Yes

Dedza TA Kaphuka 38 25 Chagalawanda Chakhala Chiphoola Kambuzi Kamitengo Nyombe

495 No – HSA

Dedza TA Kaphuka 58 26 Chimpeni Kabango Mtsimba Phalula

412 No – HSA

Dedza TA Kaphuka 63 27 Katsache Kudemela Mwasadzu Paiwe

527 Yes

Dedza TA Kaphuka 80 28 Dzololo Hinda

448 Yes

Dedza TA Kaphuka 85 29 Kachala Malindima Mananga Ngunda

201 Yes

Dedza TA Kaphuka 93 30 Chilopa Kanyemba Kanyosole Kumano Mang'umbi Nyangu

377 Yes

Dedza TA Kaphuka 97 31 Kambewa Mwachalo Njolo

426 No – HSA





Dedza TA Tambala 6 32 Chete, Chioza Kazembe Liu Mchalo Mpombe Tsuchi

365 Yes

Dedza TA Tambala 801 33 Chiphwanya Gosheni Kwizyo Mdendere, Mkajenda

533 No – Vacant

Dedza TA Kasumbu 8 34 Adini Chapola Chembe Kambwiri Mbimbi Mdala Mzoola

508 No – Vacant

Dedza TA Kasumbu 31 35 Boko Chigome Damison Gwazaudwale Maluwa Pinji


Dedza TA Kasumbu 49 36 Chakana Kayendele Mkhalapadzuwa Mpalale Ngwere

321 No – HSA

Dedza TA Kachindamoto 35 37 Dziko Galuanenenji

422 Yes

Dedza TA Kachindamoto 46 38 Diena Estate Kapiri 2 Msuka Sitolo 2

263 Yes

Dedza TA Kachindamoto 54 39 Abraham Asani

290 Yes

Dedza TA Kamenyagwaza 21 40 Khanganya 249 No – HSA

Ntcheu TA Phambala 5 41 Kanzati Kapulula Magombo Malota

262 Yes but moved out early 2016

Ntcheu TA Phambala 53 42 Kambalame 152 Yes

Ntcheu TA Phambala 58 43 Bayani Katsalam'bande

345 Yes

Ntcheu TA Makwangwala 1 44 Kalimbirana Loti Chinsinula

509 No – HSA

Ntcheu TA Makwangwala

9 45 Akubilila I Menyani Penga Penga

410 Yes

Ntcheu TA Makwangwala 24 46 Kukhola Mlambwadza

239 Yes

Ntcheu TA Makwangwala 53 47 Kalimanjira III Mwenda Wilson II

210 Yes





Ntcheu TA Makwangwala 58 48 Chasasa Helani Kayinga Ntentha

394 No – Vacant Yes Yes Yes

Ntcheu TA Njolomole 21 49 Ben Zikagoya Kazembe Magola Zande

502 Yes

Ntcheu TA Njolomole 28 50 Bonga Chinkwandala Kanzende Mulodzanyama Zimenyana

354 Yes

Ntcheu TA Goodson Ganya 25 51 Manjanja Thunga

396 No – Vacant

Ntcheu TA Goodson Ganya 39 52 Kadam'manja Matapila

151 Yes

Ntcheu TA Goodson Ganya 57 53 Machaka 164 Yes

Ntcheu TA Goodson Ganya 63 54 Zande 262 Yes

Ntcheu TA Goodson Ganya 85 55 Chawanje 298 No – Vacant

Ntcheu TA Goodson Ganya 90 56 Sanjani 259 No – Vacant

Ntcheu TA Goodson Ganya 96 57 Kaimaima 414 Yes

Dedza12 TA Masasa 13 58 Kalumo Nsamala Pitala

342 No – Vacant

Ntcheu TA Masasa 17 59 Chikhumba Chiwembu, Foso

467 Yes

Ntcheu TA Masasa 24 60 Masese II 183 Yes

12 Was mistakenly noted as in Ntcheu district rather than in Dedza district


ANNEX C1. ENDLINE SURVEY HOUSEHOLD QUESTIONNAIRE

See attached.


ANNEX C2. ENDLINE SURVEY HSA QUESTIONNAIRE

See attached.


ANNEX D. TRAINING SCHEDULE

Monday 25 July

Time Topic Facilitator

Day 1

(Materials needed: copies of training schedule; Training manuals, Questionnaires)

09:00 Session1: Orientation (Duration: 1hr)

- Opening statements

- Personal introductions

- Review of the training schedule

T Mleme

10:00 Session 2: RAcE Project (Duration: 30 min)

- RAcE Survey Objectives

-

E Chimbalanga

10:30 Session 3: Roles and responsibilities of the interviewer

(Duration: 45 min)

- Overview of Survey Modules, Teams and Roles

- Introduction to interviewers roles and responsibilities

- Regulations for Survey team

S Wachepa

11:15 BREAK (Duration: 15 min)

11:30 Session 4: Field work procedures (Duration: 1hr)

- Selection of households and respondents in the household, Daily Assignment sheets, making call backs

- Ensuring confidentiality

- Data quality checks (questionnaire review)

L Gombwa

12:30 LUNCH (Duration: 1hr)

13:30 Session 5: Interview procedures and tips (Duration: 2hr)

- Approach to the household

- Identify the respondent and administer informed consents

- Conducting the interview

F Matumula


15:45 Session 6: Household questionnaire (Duration: 30min)

- Child Identifier

T Mleme

16:15 Session 7: Questions/ Concerns (Duration 15min)

16:30 ADJOURN


Tuesday 26 July


Day 2: Paper Questionnaires

(materials needed: printed questionnaire and manual for each participant)

08:30 Review Day 1/ Answer any questions (Duration 30 min) OK Banda

09:00 Session 8: Household questionnaire (Duration: 1 hr)

- Care giver's background

- Care giver's Decision making

- Care giver's knowledge of CCM trained HSAs & illness

S Wachepa

10:00 Session 9: Household questionnaire (Duration: 30 min)

- Diarrhoea & Fever

E Nyanda


10:45 Session 10: Household questionnaire (Duration: 1 hr)

- Rapid Breath & Observations

E Nyanda

11:45 Session 11: Questions/ Concerns (Duration 30min) S Wachepa


13:15 Session 12: Practice (Duration : 2hr)

- Enter paper questionnaires

- Mock interviews

ALL


15:30 Session 13: QUIZ (1 hr) ALL

16:30 ADJOURN

Wednesday 27 July


Day 3: Questionnaires Practice

(Materials needed: questionnaires and manuals)

08:30 Review Day 2/ Answer any questions (Duration 30 min) E Dandaula

09:00 Session 14: Practice (Duration: 2hr)


- Mock Interviews

ALL





- Mock Interviews

ALL




- Mock Interviews

ALL




- Mock Interviews

ALL

16:45 ADJOURN

Thursday 28 July


Day 4: (Materials needed: paper questionnaires, pens

07:30 Preparation for Field Practice (Duration 30 min) F Matumula

08:00 Session 17: Field Practice (Duration: Full day) ALL

15:00 Session 18: Review of field practice (Duration: 1hr) S Wachepa

16:00 ADJOURN

Friday 29 July


Day 5: (Materials needed: questionnaires and manuals)

8:30 Review Day 4/ Answer any questions (Duration 30 min) T Maonga

09:00 Session 19: Test Review (Duration: 1hr) ALL




- Mock Interviews

ALL





- Mock Interviews

ALL


15:30 Session 22: TEST (Duration:1hr)

ALL

16:30 ADJOURN

Saturday 30 July


Day 6: (Materials needed: paper questionnaires, pens

07:30 Preparation for Field Practice (Duration 30 min) F Matumula

08:00 Session 23: Field Practice (Duration: Full day) ALL

15:00 Session 24: Review of field practice (Duration: 1hr) ALL

16:00 ADJOURN

Monday 01 August


Day 7: HSA Questionnaire and Supervisors Training (Supervisors Only in room A)

(materials needed: Supervisor manual, HSA questionnaire)

09:00 Session 1: Supervisor Role and Duties (2hr)

- Team Leadership

- Selection of Households

T Mleme


11:15 Session 2: HSA questionnaire (Duration: 1h)

- HSA Identifier

- HSA background

- HSA Supervision

L Gombwa



13:15 Session 3: HSA questionnaire (Duration: 2hr)

- iCCM Medicines and Supplies

- iCCM Activities and Register Review

- Data display templates and data use

Romas

E Chimbalanga


15:30 Session 4: HSA questionnaire (Duration: 1hr)

- Training and Knowledge of Newborn Health

- Newborn Health, Equipment, Supplies and Register Review

- Newborn Health Supervision

Romas

16:30 ADJOURN

Tuesday 02 August

Time Topic Presenter

Day 8: Interviewers and Supervisors supplements (materials needed: questionnaire and manuals)

08:30 Review Day 6/ Answer any questions (Duration 30 min)

09:00 Session 25: Listing and Mapping (Duration: 2h) Frank matumula


11:15 Session 26: Field Stationary and Forms Completion (Duration: 1hr)

OK Banda


13:15 Session 27: Preparations for Fieldwork and Departure S Wachepa

16:00 END OF TRAINING


ANNEX E. KEY INDICATOR SUMMARY TABLES FOR SUB-AREAS

E.1 Key Indicator Summary Table Comparing 33 Active Clusters and 27 Inactive

Clusters

Indicator Active Inactive % point

change % (CI %) % (CI %)

Caregiver knowledge

1


93.1 (87.4 - 96.3)

72.1 (55.7 - 84.2)

21.0

2


35.0 (27.8 - 42.8)

32.6 (24.7 - 41.6)

2.4

3


96.2 (93.3 - 97.9)

95.0 (90.9 - 97.4)

1.2


4


77.8 (68.3 - 85.1)

59.0 (47.2 - 69.9)

18.8

5


62.0 (55.3 - 68.2)

51.0 (42.7 - 59.1)

11.0

6


84.1 (76.5 - 89.6)

83.5 (73.8 - 90.1)

0.6

7


60.1 (52.0 - 67.7)

32.3 (22.2 - 44.5)

27.8


8


Overall 73.9

(67.6 - 79.4) 65.3

(58.3 - 71.7) 8.6

Fever 76.5

(69.9 - 82.0) 70.6

(62.4 - 77.8) 5.9

Diarrhea 72.6

(64.3 - 79.7) 66.3

(57.5 - 74.1) 6.3


(63.4 - 79.0) 58.7

(50.4 - 66.5) 13.1

9


Overall 45.8

(37.4 - 54.5) 18.4

(12.0 - 27.2) 27.4




Fever 47.0

(37.6 - 56.6) 17.5

(11.1 - 26.4) 29.5

Diarrhea 48.1

(38.7 - 57.7) 24.6

(15.8 - 36.1) 23.5


(33.8 - 51.6) 14.8

(9.0 - 23.3) 27.7



60.8 (53.5 - 67.7)

56.8 (48.3 - 64.8)

4.0

11

Percentage of children age 2-59 months for whom their caregiver received the results of the malaria diagnostic test of the children who had had finger or heel stick in the two weeks preceding the survey

96.9 (93.4 - 98.6)

97.9 (93.2 - 99.4)

-1.0

12


44.4 (37.7 - 51.4)

31.7 (24.9 - 39.5)

12.7


13

Percentage of children age 2-59 months with fever in the two weeks preceding the survey who had a finger or heel stick by an HSA at a village clinic (among those who sought care from an HSA)

61.2 (50.6 - 70.8)

63.6 (44.4 - 79.4)

-2.4

14

Percentage of children age 2-59 months for whom their caregiver received the results of the malaria diagnostic test of the children who had a finger or heel stick by an HSA at a village clinic in the two weeks preceding the survey (among those who sought care from an HSA)

97.9 (91.2 - 99.5)

100 -2.1

15

Percentage of children age 2-59 months with cough and difficult or rapid breathing (suspected pneumonia) in the two weeks preceding the survey who had their respiratory rate counted to assess fast breathing by an HSA at a village clinic (among those who sought care from an HSA)

57.5 (45.3 - 68.9)

51.4 (36.7 - 65.9)

6.1


16


Overall 50.8

(45.5 - 56.1) 42.7

(37.3 - 48.2) 8.1

Fever (ACT with 24 hours) * 61.3

(51.6 - 70.2) 56.4

(46.5 - 65.9) 4.9


(18.3 - 32.1) 17.1

(11.6 - 24.6) 7.4

Cough with difficult or fast breathing (Baseline-cotrimoxazole; endline-amoxicillin)

66.8 (59.0 - 73.8)

56.1 (48.6 - 63.3)

10.7

17


Overall 22.7

(17.1 - 29.4) 9.3

(5.0 - 16.7) 13.4


(23.8 - 45.1) 12.9

(4.9 - 29.9) 20.7





(8.7 - 20.9) 6.9

(3.0 - 14.8) 6.8


24.3 (18.6 - 31.2)

9.6 (5.6 - 15.9)

14.7

18

Percentage of children age 2-59 months who have been sick in the two weeks preceding the survey who received the first dose of treatment in the presence of an HSA among those who received prescription medicines for a CCM condition in the two weeks preceding the survey

Overall 50.6

(41.2 - 59.9) 45.5

(34.7 - 56.6) 5.1

Fever (ACT) 54.8

(42.2 - 66.8) 61.9

(35.3 - 82.9) -7.1


(11.6 - 43.5) 16.7

(3.6 - 51.9) 7.4


57.1 (44.3 - 69.1)

45.5 (28.8 - 63.3)

11.6

19


Overall 97.2

(92.0 - 99.0) 100 -2.8

Fever (ACT) 98.8

(91.0 - 99.9) 100 -1.2


(74.6 - 98.4) 100 -6.9


96.8 (87.2 - 99.3)

100 -3.2


20 Percentage of sick children age 2-59 who were referred in the two weeks preceding the survey whose caregiver adhered to referral advice

89.5 (80.5 - 94.6)

80.0 (64.8 - 89.7)

9.5

21


23.1 (17.3 - 30.1)

17.4 (11.9 - 24.7)

5.7



E.2 Key Indicator Summary Table Comparing Baseline and Endline Results for

33 Active Clusters


Indicator Baseline Endline % point

change p-value

% (CI %) % (CI %)

Caregiver knowledge

1


92.4 (85.4 - 96.2)

93.1 (87.4 - 96.3)

0.7 0.7392

2


38.4 (30.8 - 46.6)

35.0 (27.8 - 42.8)

-3.5 0.4923

3


98.0 (95.9 - 99.1)

96.2 (93.3 - 97.9)

-1.8 0.1724


4


84.5 (77.9 - 89.5)

77.8 (68.3 - 85.1)

-6.7 0.0638

5


67.7 (61.8 - 73.2)

62.0 (55.3 - 68.2)

-5.7 0.1378

6


87.0 (76.1 - 93.4)

84.1 (76.5 - 89.6)

-2.9 0.6081

7


64.0 (54.7 - 72.4)

60.1 (52.0 - 67.7)

-3.9 0.4257


8


Overall 68.5

(63.1 - 73.4) 73.9

(67.6 - 79.4) 5.4 0.1102

Fever 72.8

(65.5 - 79.1) 76.5

(69.9 - 82.0) 3.7 0.3820

Diarrhea 69.3

(62.7 - 75.2) 72.6

(64.3 - 79.7) 3.3 0.4725



change p-value

% (CI %) % (CI %)


(56.0 - 70.1) 71.8

(63.4 - 79.0) 8.5 0.0528

9


Overall 30.4

(22.9 - 39.0) 45.8

(37.4 - 54.5) 15.4 0.0007

Fever 30.7

(23.1 - 39.4) 47.0

(37.6 - 56.6) 16.4 0.0005

Diarrhea 37.1

(27.3 - 48.1) 48.1

(38.7 - 57.7) 11.0 0.0479


(17.2 - 33.9) 42.5

(33.8 - 51.6) 17.9 0.0007



32.2 (24.4 - 41.2)

60.8 (53.5 - 67.7)

28.6 0.0000

11


96.4 (89.0 - 98.9)

96.9 (93.4 - 98.6)

0.5 0.8233

12


29.4 (22.8 - 37.1)

44.4 (37.7 - 51.4)

15.0 0.0026


13


0 61.2

(50.6 - 70.8) 61.2 0.0000

14


0* 97.9

(91.2 - 99.5) 97.9 na

15

Percentage of children age 2-59 months with cough and difficult or rapid breathing (suspected pneumonia) in the two weeks preceding the survey who had their respiratory rate counted to assess fast breathing by an HSA at a village clinic (among those who sought care from an HSA)

29.9 (20.3 - 41.6)

57.5 (45.3 - 68.9)

27.7 0.0005


16


Overall 45.3

(39.4 - 51.4) 50.8

(45.5 - 56.1) 5.5 0.1133



change p-value

% (CI %) % (CI %)


(54.9 - 72.0) 61.3

(51.6 - 70.2) -2.5 0.6931


(13.5 - 28.2) 24.5

(18.3 - 32.1) 4.7 0.3283


amoxicillin)

56.5 (48.2 - 64.3)

66.8 (59.0 - 73.8)

10.3 0.0278

17


Overall 16.6

(11.8 - 22.8) 22.7

(17.1 - 29.4) 6.1 0.0753


(25.4 - 45.2) 33.6

(23.8 - 45.1) -1.0 0.8647


(4.9 - 15.7) 13.7

(8.7 - 20.9) 4.8 0.2168


amoxicillin)

13.3 (8.1 - 21.1)

24.3 (18.6 - 31.2)

11.0 0.0228

18


Overall 38.2

(25.9 - 52.4) 50.6

(41.2 - 59.9) 12.3 0.1000

Fever (ACT) 45.1

(34.3 - 56.4) 54.8

(42.2 - 66.8) 9.7 0.1809


(5.6 - 40.4) 24.1

(11.6 - 43.5) 7.5 0.5357


amoxicillin)

39.4 (17.2 - 67.1)

57.1 (44.3 - 69.1)

17.7 0.2615

19


Overall 100 97.2

(92.0 - 99.0) -2.8 0.1710

Fever (ACT) 100 98.8

(91.0 - 99.9) -1.2 0.4574

Diarrhea (ORS and zinc) 100 93.1

(74.6 - 98.4) -6.9 0.2401


amoxicillin) 100

96.8 (87.2 - 99.3)

-3.2 0.3274


20


87.0 (68.5 - 95.3)

89.5 (80.5 - 94.6)

2.5 0.7510



change p-value

% (CI %) % (CI %)

21


16.7 (10.1 - 26.4)

23.1 (17.3 - 30.1)

6.4 0.1435

na = not applicable *Appropriate fever treatment includes presumptive malaria treatment at baseline by HSAs, confirmed malaria treatment at endline by HSAs, confirmed malaria treatment by all other providers at baseline and endline. Presumptive treatment includes cases in which ACT was given but no there was no finger prick or heel stick. Confirmed malaria treatment includes cases in which ACT was given, there was a finger or heel stick, and the result of the test was positive. Appropriate treatment for fever cases was restricted to include only children aged 5–59 months.

E.3 Key Indicator Summary Table Comparing Baseline and Endline Results for

27 Inactive Clusters



change p-value

% (CI %) % (CI %)

Caregiver knowledge

1

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who are aware of the presence of the CCM-trained has in their community

86.9 (72.3 - 94.4)

72.1 (55.7 - 84.2)

-14.8 0.0239

2


30.4 (23.1 - 38.9)

32.6 (24.7 - 41.6)

2.2 0.7403

3


96.8 (94.2 - 98.3)

95.0 (90.9 - 97.4)

-1.8 0.3035


4


79.1 (71.6 - 85.1)

59.0 (47.2 - 69.9)

-20.1 0.0025

5


69.2 (61.2 - 76.3)

51.0 (42.7 - 59.1)

-18.3 0.0009

6


85.5 (75.8 - 91.8)

83.5 (73.8 - 90.1)

-2.0 0.7302

7


53.8 (42.6 - 64.6)

32.3 (22.2 - 44.5)

-21.5 0.0043



change p-value

% (CI %) % (CI %)


8


Overall 61.8

(52.7 - 70.1) 65.3

(58.3 - 71.7) 3.5 0.3604

Fever 67.0

(56.4 - 76.2) 70.6

(62.4 - 77.8) 3.6 0.4592

Diarrhea 57.4

(46.7 - 67.5) 66.3

(57.5 - 74.1) 8.9 0.1489


(48.3 - 70.9) 58.7

(50.4 - 66.5) -1.4 0.7822

9


Overall 19.7

(12.4 - 29.7) 18.4

(12.0 - 27.2) -1.3 0.8124

Fever 20.6

(11.5 - 34.3) 17.5

(11.1 - 26.4) -3.2 0.6192

Diarrhea 22.8

(14.9 - 33.4) 24.6

(15.8 - 36.1) 1.7 0.7698


(9.2 - 26.5) 14.8

(9.0 - 23.3) -1.3 0.8093



40.2 (32.9 - 48.0)

56.8 (48.3 - 64.8)

16.5 0.0029

11


97.4 (89.3 - 99.4)

97.9 (93.2 - 99.4)

0.5 0.7777

12


20.7 (13.5 - 30.5)

31.7 (24.9 - 39.5)

11.0 0.0685


13


0 63.6

(44.4 - 79.4) 63.6 0.0000

14


0* 100 0.0 na

15

Percentage of children age 2-59 months with cough and difficult or rapid breathing (suspected pneumonia) in the two weeks preceding the survey who

33.3 (17.1 - 54.8)

51.4 (36.7 - 65.9)

18.1 0.2194



change p-value

% (CI %) % (CI %)

had their respiratory rate counted to assess fast breathing by an HSA at a village clinic (among those who sought care from an HSA)


16


Overall 39.1

(32.2 - 46.5) 42.7

(37.3 - 48.2) 3.6 0.3365


(46.4 - 70.2) 56.4

(46.5 - 65.9) -2.4 0.7280


(10.4 - 25.7) 17.1

(11.6 - 24.6) 0.5 0.9166


amoxicillin)

49.2 (40.2 - 58.3)

56.1 (48.6 - 63.3)

6.9 0.2102

17


Overall 10.5

(5.6 - 18.8) 9.3

(5.0 - 16.7) -1.2 0.7774


(10.5 - 38.1) 12.9

(4.9 - 29.9) -8.3 0.3504


(1.8 - 12.7) 6.9

(3.0 - 14.8) 1.9 0.5854


amoxicillin)

10.4 (5.4 - 19.1)

9.6 (5.6 - 15.9)

-0.8 0.8379

18


Overall 35.3

(19.2 - 55.7) 45.5

(34.7 - 56.6) 10.2 0.3942

Fever (ACT) 26.1

(9.7 - 53.6) 61.9

(35.3 - 82.9) 35.8 0.0634


(16.9 - 63.8) 16.7

(3.6 - 51.9) -20.8 0.2063


amoxicillin)

45.0 (24.9 - 66.8)

45.5 (28.8 - 63.3)

0.5 0.9755

19


Overall 100 100 0 na

Fever (ACT) 100 100 0 na

Diarrhea (ORS and zinc) 100 100 0 na



change p-value

% (CI %) % (CI %)


amoxicillin) 100 100 0 na

Sick Child Referral and Follow-up

20


90.9 (74.6 - 97.2)

80.0 (64.8 - 89.7)

-10.9 0.2031

21


24.8 (15.8 - 36.6)

17.4 (11.9 - 24.7)

-7.4 0.1685

na = not applicable *Appropriate fever treatment includes presumptive malaria treatment at baseline by HSAs, confirmed malaria treatment at endline by HSAs, confirmed malaria treatment by all other providers at baseline and endline. Presumptive treatment includes cases in which ACT was given but no there was no finger prick or heel stick. Confirmed malaria treatment includes cases in which ACT was given, there was a finger or heel stick, and the result of the test was positive. Appropriate treatment for fever cases was restricted to include only children aged 5–59 months.


ANNEX F. ILLNESS MANAGEMENT AND DIAGNOSTICS BY SEX RESULTS TABLES

Table F1. Fever management

Sought any advice or treatment

Sought treatment from an

appropriate provider*

Sought treatment from

an HSA

Sought treatment from an HSA as first

choice

Had blood taken from

finger or heel

Malaria treatment Number of

children with fever

Any anti-malarial

ACT ACT within 24 hours

Overall 86.7

(83.1 - 89.6) 73.9

(68.9 - 78.4) 34.3

(27.4 - 42.0) 34.0

(27.2 - 41.5) 59.0

(53.7 - 64.2) 52.0

(47.5 - 56.5) 50.3

(45.6 - 54.9) 30.7

(26.6 - 35.0) 571

Male 84.6

(79.5 - 88.6) 70.5

(64.0 - 76.3) 36.5

(28.7 - 45.1) 36.1

(28.5 - 44.6) 55.8

(49.2 - 62.2) 50.2

(44.4 - 56.0) 49.1

(43.5 - 54.8) 31.2

(26.1 - 36.8) 285

Female 88.8

(85.0 - 91.8) 77.3

(71.7 - 82.1) 32.2

(24.8 - 40.5) 31.8

(24.5 - 40.1) 62.2

(55.7 - 68.4) 53.9

(48.0 - 59.6) 51.4

(45.4 - 57.4) 30.1

(24.9 - 35.8) 286

* Refers to those who sought care from a hospital, health center, health post, village clinic (HSA), mobile/outreach clinic, or private hospital, clinic, or physician.

Table F2. Confirmed malaria treatment

Confirmed malaria treatment Number of children with a positive blood

test

Any Anti-malarial

ACT ACT within 24 hours

% (CI %) % (CI %) % (CI %)

Overall 95.1

(91.5 - 97.2) 92.2

(87.7 - 95.2) 59.0

(52.1 - 65.6) 244

Male 96.5

(90.6 - 98.7) 94.7

(88.4 - 97.7) 64.9

(55.6 - 73.2) 114

Female 93.9

(88.5 - 96.8) 90.0

(83.7 - 94.1) 53.9

(45.1 - 62.3) 130


Table F3. Fever diagnostics

Had blood taken from

finger or heel

Among those who had blood taken

Number of children

with fever Were given

results Test result

positive

Overall 59.0

(53.7 - 64.2) 97.3

(95.0 - 98.6) 74.4

(69.1 - 79.1) 571

Male 55.8

(49.2 - 62.2) 96.9

(92.8 - 98.7) 74.0

(66.9 - 80.1) 285

Female 62.2

(55.7 - 68.4) 97.8

(94.0 - 99.2) 74.7

(67.0 - 81.1) 286

Table F4. Diarrhea management



appropriate provider*

Sought treatment

from an HSA


HSA as first choice

Given same or

more than usual to

drink

Given same or

more than usual to

eat

Treatment Treated

with ORS AND Zinc

Number of

children with

diarrhea

ORS Home- made fluid

Zinc

Overall 77.3

(72.4 - 81.5) 69.8

(63.9 - 75.0) 37.7

(30.7 - 45.3) 37.5

(30.5 - 45.1) 50.4

(44.9 - 55.9) 32.6

(27.5 - 38.1) 68.5

(63.2 - 73.3) N/A

24.0 (19.1 - 29.8)

21.2 (16.9 - 26.3)

387

Male 73.7

(66.8 - 79.6) 68.8

(61.8 - 75.0) 39.5

(30.7 - 49.1) 39.5

(30.7 - 49.1) 51.7

(45.1 - 58.3) 29.8

(23.5 - 36.9) 67.8

(61.2 - 73.8) N/A

22.0 (16.8 - 28.2)

19.5 (14.5 - 25.8)

205

Female 81.3

(74.2 - 86.8) 70.9

(62.6 - 78.0) 35.7

(27.1 - 45.3) 35.2

(26.7 - 44.7) 48.9

(40.8 - 57.1) 35.7

(28.6 - 43.6) 69.2

(60.5 - 76.8) N/A

26.4 (19.6 - 34.5)

23.1 (17.1 - 30.4)

182

N/A=not available * Refers to those who sought care from a hospital, health center, health post, village clinic (HSA), mobile/outreach clinic, or private hospital, clinic, or physician.


Table F5. Cough with difficult or fast breathing management


Sought treatment from an appropriate

provider*

Sought treatment from

an HSA

Sought treatment from an HSA as first

choice

Assessed for rapid breathing

Treatment Number of children with cough and difficult or

fast breathing

Any antibiotic Amoxicillin

Overall 81.8

(78.1 - 85.0) 65.6

(59.8 - 71.1) 30.1

(23.7 - 37.3) 29.5

(23.2 - 36.6) 38.5

(33.5 - 43.7) 65.0

(59.6 - 70.1) 61.8

(56.4 - 66.9) 489

Male 79.8

(73.8 - 84.7) 64.6

(56.3 - 72.0) 29.1

(22.0 - 37.4) 27.9

(20.9 - 36.0) 35.4

(28.4 - 43.2) 61.6

(53.7 - 69.0) 59.1

(51.3 - 66.4) 237

Female 83.7

(78.6 - 87.8) 66.7

(60.4 - 72.4) 31.0

(24.0 - 38.9) 31.0

(24.0 - 38.9) 41.3

(34.9 - 48.0) 68.3

(61.8 - 74.1) 64.3

(57.4 - 70.6) 252

* Refers to those who sought care from a hospital, health center, health post, village clinic (HSA), mobile/outreach clinic, or private hospital, clinic, or physician.


ANNEX G. SUPPLEMENTARY 60 CLUSTER RESULTS TABLES

Table G1. Caregiver knowledge of child illness or danger signs

Child Illness or danger sign Baseline % (CI %)

Endline % (CI %)

Child under two months old 0.3

(0.1 - 1.1) 0.0

(0.0 - 0.0)

Fever 94.0

(91.7 - 95.7) 65.5

(59.9 - 70.8)

Fever for seven days or more 1.5

(0.7 - 3.2) 22.9

(18.9 - 27.4)

Diarrhea with blood in stool 6.0

(4.3 - 8.3) 17.0

(13.7 - 20.9)

Diarrhea with dehydration 45.6

(40.8 - 50.4) 47.0

(42.1 - 52.0)

Diarrhea for 14 days or more 9.9

(7.6 - 12.8) 8.2

(5.9 - 11.3)

Fast or difficult breathing/chest in-drawing 28.9

(24.6 - 33.6) 36.0

(31.6 - 40.7)

Cough for 21 days or more 24.4

(21.0 - 28.2) 17.2

(14.0 - 21.1)

Refusal to breastfeed 11.4

(8.7 - 14.7) 9.1

(7.0 - 11.6)

Not able to drink or feed 16.4

(12.7 - 20.9) 13.4

(10.5 - 17.0)

Vomits everything 42.4

(37.9 - 46.9) 42.4

(38.3 - 46.7) Yellow or red MUAC result/skinny upper arm and swelling of both feet

2.2 (1.3 - 3.7)

5.5 (3.8 - 7.8)

Convulsions 12.6

(9.6 - 16.5) 17.9

(15.0 - 21.2)

Loss of consciousness 11.5

(8.7 - 15.1) 19.3

(15.6 - 23.6)

Lethargic/tired/slow to respond/does not want to play 17.6

(13.0 - 23.5) 16.7

(13.5 - 20.6)

Stiff next 1.8

(1.0 - 3.2) 0.6

(0.2 - 2.1)

Don't know 0.1

(0.0 - 1.0) 0.0


MUAC=mid-upper arm circumference


Table G2. Caregiver knowledge of HSA activities

HSA activity Baseline % (CI %)

Endline % (CI %)

Community mobilization 26.2

(20.8 - 32.5) 23.6

(18.2 - 30.0)

Organization of health campaigns 18.2

(13.9 - 23.5) 26.8

(20.8 - 33.8)

Dissemination of health messages 19.4

(14.9 - 24.9) 36.0

(30.3 - 42.1)

Provide health information in households 64.8

(57.7 - 71.3) 44.9

(39.2 - 50.7)

Provide health information at community events 17.0

(14.2 - 20.2) 13.2

(10.2 - 16.9)

Collect information on health 6.5

(4.5 - 9.2) 6.6

(4.4 - 9.8)

Other preventative activity 8.3

(5.7 - 12.1) 11.6

(7.9 - 16.8)

Refer to health facility 18.5

(14.6 - 23.2) 13.5

(10.4 - 17.3)

Test for malaria 2.8

(1.7 - 4.6) 13.0

(9.7 - 17.2)

Assess for suspected pneumonia 4.5

(2.7 - 7.4) 6.6

(4.6 - 9.3)

Provide treatment for malaria 38.7

(33.4 - 44.3) 32.0

(25.6 - 39.2)

Provide treatment for pneumonia 5.9

(4.1 - 8.3) 10.6

(7.5 - 14.7)

Provide ORS for diarrhea 32.1

(26.8 - 37.9) 17.6

(13.9 - 22.1)

Provide zinc for diarrhea 3.7

(2.4 - 5.8) 4.9

(3.5 - 6.7)

Assess for malnutrition 5.6

(3.3 - 9.1) 13.6

(10.4 - 17.7)

Follow up sick children at home 7.9

(4.9 - 12.4) 9.8

(7.4 - 12.9)

Other curative activity 5.4

(3.4 - 8.6) 11.2

(7.8 - 15.9)

Don't know 0.5

(0.1 - 2.0) 0.8



Table G3. Reasons caregivers did not seek care from any source (endline only)

Reason Overall

% (CI %) Fever

% (CI %) Diarrhea % (CI %)

Cough* % (CI %)

Did not think the condition was serious 30.4

(24.6 - 37.0) 26.3

(18.9 - 35.4) 39.8

(28.5 - 52.3) 24.7

(17.5 - 33.7)

Condition passed 12.7

(8.9 - 17.7) 15.8

(8.6 - 27.2) 14.8

(8.8 - 23.7) 7.9

(3.6 - 16.2)

Place of care was too far 14.6

(9.5 - 21.9) 11.8

(5.9 - 22.4) 12.5

(7.2 - 20.9) 19.1

(11.0 - 31.2)

Did not have time 7.1

(4.0 - 12.5) 4.0

(1.2 - 11.9) 6.8

(2.7 - 16.4) 10.1

(5.1 - 19.1)

Did not have permission 0.4

(0.1 - 2.9) 0.0 0.0

1.1 (0.2 - 7.9)

Did not have money 21.0

(13.9 - 30.4) 25.0

(14.4 - 39.8) 18.2

(9.4 - 32.3) 20.2

(12.2 - 31.6) Could treat the condition at home or with medicines already on hand

22.1 (16.4 - 29.2)

23.7 (14.8 - 35.6)

11.4 (5.5 - 22.1)

31.5 (21.9 - 43.0)

Other 7.1

(4.1 - 12.0) 5.3

(2.0 - 13.3) 9.1

(4.1 - 19.0) 6.7

(3.1 - 14.0) Number of caregivers who didn't seek care

253 76 88 89

*Cough with difficult or fast breathing

Table G4. Reasons caregivers did not seek care from an HSA, among those who sought care

(endline only)

Reason Overall

% (CI %) Fever

% (CI %) Diarrhea % (CI %)

Cough* % (CI %)

HSA was not available 18.2

(11.6 - 27.2) 17.7

(11.3 - 26.7) 17.7

(10.3 - 28.7) 19.0

(11.4 - 30.0)

HSA did not have medicines or supplies 1.1

(0.4 - 3.5) 2.0

(0.7 - 5.4) 0.7

(0.1 - 4.8) 0.4

(0.1 - 2.9)

Did not trust HSA to provide care 1.0

(0.4 - 2.2) 2.0

(0.9 - 4.3) 0.0

0.4 (0.1 - 2.9)

Thought condition was too serious 2.6

(1.3 - 4.9) 3.3

(1.6 - 6.7) 2.0

(0.5 - 8.0) 2.0

(0.7 - 5.6)

Preferred to go to another provider 80.4

(73.1 - 86.2) 78.3

(70.6 - 84.4) 84.3

(72.3 - 91.7) 80.6

(72.3 - 86.9)

HSA was too far away 5.3

(3.3 - 8.2) 5.7

(3.4 - 9.4) 2.0

(0.5 - 8.1) 6.7

(3.8 - 11.7)

Other 1.6

(0.9 - 2.7) 1.3

(0.5 - 3.4) 1.3

(0.3 - 5.0) 2.0

(0.9 - 4.5) Number of caregivers who sought care—but not from HSA 705 299 153 253

*Cough with difficult or fast breathing


Table G5. Location of sick child assessment

Location* Malaria Fast breathing

Baseline Endline Baseline Endline % (CI %) % (CI %) % (CI %) % (CI %)

Village clinic** 2.5

(0.7 - 8.2) 36.5

(27.8 - 46.2) 27.4

(18.3 - 39.0) 45.2

(34.8 - 56.1)

Government hospital 81.5

(70.6 - 89.0) 51.3

(42.6 - 60.0) 62.0

(50.7 - 72.1) 45.2

(36.1 - 54.6)

Mission hospital (CHAM) 10.5

(4.5 - 22.5) 5.9

(3.3 - 10.4) 6.2

(2.7 - 13.6) 5.3

(3.0 - 9.2)

Private health facility 5.6

(2.9 - 10.3) 8.0

(4.8 - 13.2) 6.2

(2.9 - 12.6) 9.6

(5.3 - 16.7)

Other 0.0 0.3

(0.0 - 2.2) 0.0 0.0

Total number of illness cases assessed

162 337 113 188

* The dataset only contained one response per caregiver in the baseline survey but allowed for multiple responses in the endline survey. ** Three caregivers reported that their children had blood taken by an HSA at a village clinic in the baseline survey, but Save the Children Malawi confirmed that this was not possible because malaria blood tests were not available at that time; one caregiver reported that his or her child had blood drawn by a nurse at a village clinic.

Table G6. Provider of sick child assessment

Provider Malaria Fast breathing

Baseline Endline Baseline Endline % (CI %) % (CI %) % (CI %) % (CI %)

HSA* 9.3

(5.3 - 15.7) 43.0

(34.5 - 52.0) 30.1

(21.2 - 40.8) 47.9

(37.7 - 58.2)

Medical assistant 54.3

(44.0 - 64.3) 28.5

(22.5 - 35.4) 35.4

(26.2 - 45.8) 28.7

(21.3 - 37.5)

Clinical officer 13.0

(6.8 - 23.3) 2.1

(0.9 - 4.8) 15.9

(9.3 - 26.0) 2.7

(0.9 - 7.3)

Nurse 17.9

(10.9 - 27.9) 18.4

(13.4 - 24.8) 15.9

(9.8 - 24.9) 20.2

(13.7 - 28.9)

Doctor 4.3

(1.9 - 9.7) 3.6

(1.8 - 7.0) 5.3

(2.5 - 11.0) 3.7

(1.8 - 7.6)

Other 0.6

(0.1 - 4.4) 6.5

(3.8 - 11.1) 0.0

1.6 (0.4 - 6.9)

Don't know 0.6

(0.1 - 4.5) 0.6

(0.2 - 2.3) 0.0

0.5 (0.1 - 3.9)

Total number of illness cases assessed

162 337 113 188

* HSAs may have taken blood from a child at a health center; mRDTs were not available at village clinics at the time of the baseline survey.

Table G7. Sick child care for children with diarrhea

Treatment Baseline Endline


Continued fluids 52.5

(47.2 - 57.7) 50.4

(44.9 - 55.9) 0.6193

Continued feeding 35.2

(30.5 - 40.2) 32.6

(27.5 - 38.1) 0.4735

Total number of children with diarrhea

364 387


Table G8. Fever treatment coverage*

Received Treatment From HSA Among Those Who Sought

Care From HSA

Received Treatment Among all Fever Cases

Baseline Endline p-

value Baseline

N Endline

N

Baseline Endline p-value

Baseline N

Endline N % (CI %) % (CI %) % (CI %) % (CI %)

Received ACT 59.7

(51.2 - 67.7) 54.4

(45.2 - 63.2) 0.4456 124 184 52.1

(46.5 - 57.6) 51.5

(46.6 - 56.3) 0.8723 438 542

Received ACT within 24 hours

52.4 (43.9 - 60.8)

38.6 (30.6 - 47.3)

0.0263 124 184 40.2 (34.1 - 46.6)

31.7 (27.6 - 36.2)

0.0140 438 542

Received ACT within 24 hours, positive blood test*

na 64.8

(53.8 - 74.5) na 0 91 57.4

(47.5 - 66.7) 59.2

(52.5 - 65.7) 0.7467 122 238

Received ACT

Blood test positive na 89.0

(79.1 - 94.6) na 0 91 84.4

(77.0 - 89.8) 92.4

(87.9 - 95.4) 0.0318 122 238

Blood test negative na 4.4

(0.5 - 30.1) na 0 23 20.6

(9.5 - 39.0) 7.7

(3.5 - 16.1) 0.0592 34 78

No blood test** 59.7

(51.1 - 67.7) 26.1

(16.7 - 38.3) 0.0002 124 69 48.9

(41.5 - 56.4) 35.2

(27.5 - 43.6) 0.0096 235 145

Did not receive ACT

Blood test positive na 11.0

(5.4 - 20.9) na 0 91 15.6

(10.2 - 23.0) 7.6

(4.6 - 12.1) 0.0318 122 238

Blood test negative na 95.7

(70.0 - 99.5) na 0 23 79.4

(61.0 - 90.5) 92.3

(83.9 - 96.5) 0.0592 34 78

No blood test** 40.3

(32.3 - 48.9) 73.9

(61.7 - 83.3) 0.0002 124 69

51.1 (43.6 - 58.5)

64.8 (56.4 - 72.5)

0.0096 235 145

na = not applicable

* 3 caregivers reported that their child got a finger prick or heel stick by an HSA at a village clinic at baseline even though mRDTs were not available at village clinics at the time of the baseline survey. All indicators in this table were restricted to include only children 5 - 59 months.

** Included only cases in which any care was sought among all fever cases


Table G9. Diarrhea treatment taken

Treatment Baseline % (CI %)

Endline % (CI %)

ORS 70.1

(64.4 - 75.1) 68.5

(63.2 - 73.3)

Zinc 21.4

(16.8 - 26.9) 24.0

(19.1 - 29.8) Homemade fluid N/A N/A Number of children with diarrhea 364 387

Other treatment Baseline % (CI %)

Endline % (CI %)

Antibiotic pill/syrup 32.6

(22.6 - 44.4) 18.3

(11.9 - 27.0)

Anti-motility pill/syrup 2.3

(0.5 - 8.8) 11.8

(5.3 - 24.2)

Other pill/syrup 2.3

(0.5 - 8.9) 2.2

(0.5 - 8.5)

Unknown pill/syrup 13.5

(8.0 - 22.0) 15.1

(9.0 - 24.1)

Antibiotic injection 3.4

(1.1 - 9.9) 5.4

(2.2 - 12.4)

Non-antibiotic injection 1.1

(0.2 - 7.9) 1.1

(0.1 - 7.8)

Unknown injection 1.1

(0.2 - 7.3) 1.1

(0.2 - 7.5)

Intravenous treatment 1.1

(0.2 - 7.9) 0.0

(0.0 - 0.0)

Home remedy/herbal medicine 11.2

(6.1 - 19.8) 12.9

(6.6 - 23.6)

Other 39.3

(29.9 - 49.7) 41.9

(31.9 - 52.7) Number of children with diarrhea who took other medication

89 93

N/A=not available

Table G10. Fever treatment taken


Endline % (CI %)

ACT (LA) 59.4

(54.1 - 64.5) 61.9

(57.1 - 66.4)

Quinine 2.9

(1.5 - 5.5) 3.9

(2.4 - 6.2)

SP/Fansidar 1.3

(0.6 - 3.1) 1.3

(0.4 - 4.0) Antibiotic pill/syrup (not corimoxazole or amoxicillin)

5.2 (3.2 - 8.3)

1.7 (0.8 - 3.7)


(0.5 - 3.1) 2.6

(1.4 - 4.8)

Cotrimoxazole/amoxicillin 19.8

(15.3 - 25.2) 19.4

(16.3 - 22.9)

Aspirin 12.5

(9.3 - 16.5) 5.4

(3.4 - 8.6)

Paracetamol 63.3

(58.0 - 68.2) 84.5

(81.3 - 87.2)

Other 6.3

(3.9 - 10.0) 4.5

(2.9 - 7.1)

Don't know 0.3

(0.0 - 1.9) 0.2

(0.0 - 1.6) Number of children with fever who took any medication

384 464


Table G11. Cough with difficult or fast breathing treatment taken


Endline % (CI %)

ACT (LA) 4.7

(2.9 - 7.5) 4.7

(2.8 - 8.0)

Quinine 0.6

(0.1 - 2.2) 1.1

(0.3 - 3.5)

SP/Fansidar 0.0

(0.0 - 0.0) 0.8

(0.3 - 2.4)

Antibiotic cough syrup 22.5

(17.3 - 28.6) 9.7

(6.6 - 14.2)


(1.1 - 4.2) 1.3

(0.5 - 3.7)

Cotrimoxazole/amoxicillin 64.4

(59.0 - 69.4) 79.5

(73.7 - 84.3)

Aspirin 5.8

(3.5 - 9.2) 2.9

(1.7 - 5.0)

Paracetamol 35.3

(29.7 - 41.4) 41.8

(36.7 - 47.1)

Other 12.6

(8.9 - 17.6) 8.2

(5.4 - 12.1)

Don't know 0.3

(0.0 - 2.0) 1.6

(0.7 - 3.4) Number of children with difficult or fast breathing who took any medication

365 380

Table G12. Source of ACT

Location Source of treatment

Baseline Endline % (CI %) % (CI %)

Public facility 53.1

(44.1 - 61.8) 44.6

(36.1 - 53.4)

Private facility 9.7

(5.5 - 16.5) 12.5

(7.9 - 19.3)

HSA 32.5

(24.0 - 42.2) 36.6

(27.8 - 46.3)

Shop or pharmacy 4.4

(2.0 - 9.6) 5.9

(3.5 - 9.8) Traditional practitioner 0.0 0.0

Other 0.4

(0.1 - 3.1) 0.4

(0.1 - 2.5) Total number of fever cases receiving ACT 228 287


Table G13. Source of ORS




(29.7 - 46.4) 33.2

(25.5 - 42.0)


(2.1 - 8.7) 8.3

(4.8 - 14.0)

HSA 39.6

(30.8 - 49.2) 44.2

(35.3 - 53.4)


(11.5 - 22.0) 11.3


Other 2.4

(1.1 - 5.1) 3.0

(1.4 - 6.3) Total number of diarrhea cases receiving ORS

255 265

Table G14. Source of zinc




(31.9 - 58.6) 43.0

(30.4 - 56.6)


(3.3 - 22.3) 7.5

(3.2 - 16.9)

HSA 38.5

(25.5 - 53.3) 46.2

(33.7 - 59.2)


(1.8 - 13.5) 3.2


Other 2.6

(0.6 - 10.1) 0.0

Total number of diarrhea cases receiving zinc 78 93

Table G15. Source of cotrimoxazole/amoxicillin

Location Source of treatment*



(39.9 - 55.9) 44.0

(37.0 - 51.3)


(2.3 - 9.4) 9.9

(6.2 - 15.6)

HSA 22.8

(16.0 - 31.5) 28.2

(22.2 - 35.0)


(18.0 - 30.6) 15.9


Other 0.9

(0.2 - 3.5) 2.0

(0.9 - 4.4) Total number of cough with fast breathing cases receiving cotrimoxazole/amoxicillin

232 302

* Source of treatment was missing for three respondents who indicated that they received cotrimoxazole or amoxicillin.


G16. Reason did not comply with HSA referral

Reason Baseline Endline

% (CI %) % (CI %)

Too far 11.1

(1.2 - 55.7) 0.0

Did not have money 11.1

(1.2 - 55.7) 30.8

(11.9 - 59.3)

No transport 0.0 15.4

(3.3 - 49.2)

Did not think illness was serious 0.0 7.7

(0.9 - 44.1)

Child improved 77.8

(37.2 - 95.4) 46.2

(22.2 - 72.0)

No time 0.0 7.7

(0.9 - 44.1)

Went somewhere else 0.0 0.0

Did not have husband's permission 0.0 0.0

Other 0.0 7.7

(0.9 - 44.1)

Total number of caregivers who did not comply with referral

9 13

G17. Time of follow-up visit to HSA (days after initial consultation)

When did follow-up take place? Baseline Endline

% (CI %) % (CI %)

One day

21.4 (8.7 - 43.9)

9.5 (2.7 - 28.9)

Two days

14.3 (5.0 - 34.4)

28.6 (12.5 - 52.8)

Three days

32.1 (12.1 - 62.1)

42.9 (23.1 - 65.1)

Four days

3.6 (0.5 - 22.5)

9.5 (2.0 - 34.9)

Five days

3.6 (0.4 - 27.2)

0.0 (0.0 - 0.0)

More than five days

25.0 (6.6 - 61.3)

9.5 (1.9 - 36.8)

Total number of sick children who were followed up by an HSA

28 21


ANNEX H. RESULTS OF ENDLINE HSA SURVEY

INTRODUCTION

As part of the endline evaluation, the National Statistics Office, ICF, and Save the Children conducted a

survey of health surveillance assistants (HSAs) to assess the implementation strength and quality of

integrated community case management (iCCM) services delivered by them. The HSA survey was

conducted alongside the endline household survey in four districts (Dedza, Mzimba North, Ntcheu, and

Ntchisi) to assess care-seeking practices and treatment coverage for iCCM conditions. The objective of

the HSA survey was to gain a better understanding of the HSAs’ background characteristics, activity

levels, and support and supervision received to help interpret the results of the coverage survey.

The HSAs serving the 60 clusters selected for the endline household survey formed the sample

population for the HSA survey. The clusters do not align perfectly with HSA catchment areas, and in

some cases there could be more than one HSA associated with a given cluster, or the cluster might not

have any community case management (CCM)-trained or active HSAs providing services. If a selected

cluster had more than one HSA who was trained in CCM, one was randomly selected for interview.

Data collection was carried out during August 2016.

RESULTS

A summary indicator table is provided in Table 1 and the main findings are summarized below. An HSA

could not be located in 13 (22 percent) of the 60 clusters (5 in Dedza, 6 in Ntcheu, and 2 in Ntchisi).

Thus, interviews were completed with a total of 47 HSAs:

District Number of clusters Number of HSAs

interviewed

Percentage of clusters with HSA

interviewed

Dedza 21 16 76%

Mzimba North 9 9 100%

Ntcheu 20 14 70%

Ntchisi 10 8 80%

Total 60 47 78%

HSA profile: Seventy percent of sampled HSAs were male (33/47) and most had completed Form 4

(62 percent) or Form 2 (32 percent) education. Two-thirds (68 percent) were between 29 and 40 years

of age.

HSA catchment areas: Most HSAs (83 percent) resided in their catchment areas. The main modes of

transportation were push bike (74 percent) or walking (19 percent). About one-third of HSAs

(36 percent) reported that it took less than 1 hour to reach the nearest health facility, 43 percent

reported that it took between 1–2 hours, and 21 percent reported that it took 2 hours or more. For

those not living in their catchment areas, most (5/8) reported that they could reach their village clinic

within 30 minutes.

Supervision: Two-thirds of HSAs (31/47) reported receiving at least 1 supervisory visit in the last

3 months, and 30 percent had received 2 or more visits. Senior HSAs (72 percent) and district staff

(22 percent) were the most frequently mentioned providers of supervision during the most recent visit.

Among those who reported supervision, all reported that the supervisors used a supervision checklist,

and most indicated that records and supply availability were reviewed and that they received feedback

on their iCCM activities. A smaller percentage of HSAs mentioned that the supervisor had administered

a case scenario (84 percent), observed sick child care (72 percent), observed a malaria rapid diagnostic


test (mRDT) (72 percent), or talked with village leaders (56 percent). About half of HSAs (55 percent)

reported one or more mentorship sessions in which sick child care was observed in the last three

months.

Availability of iCCM medicines and diagnostics: The majority of HSAs (87 percent, 41/47) had at

least one age formulation of first-line antimalarial medicine (Coartem; LA 1x6 or 2x6) in stock on the

day of observation, and 79 percent (37/47) had both. Most HSAs were observed to have paracetamol

(89 percent), zinc (83 percent), amoxicillin (79 percent), and oral rehydration solution (ORS)

(79 percent). Regarding diagnostics, 89 percent of HSAs had rapid diagnostic tests (RDTs), and 87

percent had a functional timer. Overall, about 40 percent of HSAs had all iCCM medicines and supplies

available on the day of the survey, and 60 percent had all essential iCCM medicines and supplies.13

Stockouts of iCCM items were relatively common, with only 64 percent of HSAs reporting no

stockouts of any essential iCCM medicine or RDTs in the last one month.14 The most frequently

reported stockouts were amoxicillin and LA 2x6. About 13 percent of HSAs reporting referring one or

more sick children due to stockouts of medicine in the last month.

HSA functionality: About 89 percent of HSAs had provided iCCM services in the past month and

reported provided iCCM services at least 2 days per week. However, only 26 percent met a stricter

definition of functionality, in which they resided in their catchment areas, provided iCCM services in the

last month, and reported providing iCCM at least 5 days per week.

Activity levels and record-keeping: Most HSAs (94 percent) reported providing iCCM services at least

2 days per week, but only one-quarter (26 percent) reported providing iCCM 5 or more days per week.

HSAs reported operating their village clinics for an average of 3.3 days per week and 12.8 days per

month (median 10). Register reviews indicated that HSAs treated an average of 43.5 sick child cases

(median 37; range 0–220) in the last month. About 6 percent of HSAs had not treated any sick child

cases in the past one month. Interestingly, HSAs meeting the stricter definition of functionality treated

slightly fewer sick child cases per month on average (41.8 percent) than those who did not meet that

definition (44.1 percent). More than one-third (36 percent) of HSAs had referred one or more sick

children for danger signs in the last month (mean of 0.5; range 0–3). Completeness of recording of cases

in the registers was high for RDT results (91 percent) for the 5 most recent fever cases, but slightly

lower for results of respiratory rate counts (85 percent) for the 5 most recent cough cases.

HSA data use: About 72 percent of HSAs (34/47) reported being trained in the data use package. Of

those trained, 71 percent (24/34) had received the data use templates, 33 percent had wall charts

displayed (13/34), and 29 percent (10/34) had completed charts with data filled out for the past three

months.

IMPLICATIONS

These findings have several implications for iCCM in Malawi:

Only 78 percent of the 60 endline survey clusters had a CCM-trained HSA available for interview.

Although most of the available HSAs met the Ministry of Health (MOH) definition for functionality

(providing iCCM services in last month and providing iCCM at least two days per week), only one in

four were providing regular iCCM services (living in their catchment areas, and providing iCCM at

13 LA (at least 1x6 or 2x6), amoxicillin, ORS, zinc, RDTs, and functional timer 14 LA (stock-outs of both 1x6 and 2x6), amoxicillin, ORS, zinc, and RDTs


least five days per week). Thus, when considering the full sample of 60 clusters, only 20 percent of

sampled areas had access to an HSA providing iCCM at least 5 days per week, and 70 percent had

access to an HSA providing iCCM at least 2 days per week. However, all HSAs, even those who did

not meet the stricter definition of functionality, still treated relatively high numbers of sick child

cases on a monthly basis, reflecting the high demand for iCCM services in the community.

Despite program support through RAcE and supply chain support tools such as c-stock, HSAs are

still experiencing shortages of iCCM medicines and supplies that limit their ability to provide quality

care. Only about 60 percent of HSAs had all essential medicines and diagnostics to deliver quality

iCCM, and reports of stockouts in the previous month were common. Amoxicillin was introduced

as first-line treatment for suspected pneumonia in RAcE districts, and monitoring data suggest that

overtreatment with antibiotics is still common and could be contributing to shortages, because

procurement is based on expected cases. Concurrent efforts are needed to identify and address the

underlying causes of overtreatment and to strengthen the supply chain management system for case

management at facility and HSA levels.

Supervision and mentoring levels reported by HSAs were substantially lower than targeted in the

RAcE program. After senior HSAs, RAcE district supervisors were among the primary providers of

onsite supervision. This raises concerns regarding the level of supervision and clinical mentoring that

will be maintained when support from the RAcE program ends and MOH takes on full responsibility.

Distance to HSAs, transportation gaps, competing time demands, and other factors are known

barriers to supervision. Numerous attempts have been made to address these issues with limited

sustained success. New approaches to providing clinical support and mentoring of HSAs that are

less demanding of over-stretched facility staff will likely need to be identified as part of the transition

plan.

Data use by HSAs is an area for further strengthening—many HSAs were trained in the package but

not all had received the templates and few were filling them on a regular basis.

Table H1. Summary of indicators for iCCM service delivery by HSAs

Domain Indicator Result

Residency Percentage of CCM-trained HSAs residing in their catchment area 83% (39/47) (95% CI: 69%-91%)

Functionality Percentage of CCM-trained HSAs who are functional (MOH definition): i) have provided iCCM services in past month ii) report operating village clinic for at least two days per week

89% (42/47) (95% CI: 76%-96%)

Percentage of CCM-trained HSAs who are functional (stricter version): i) reside in their catchment area ii) have provided iCCM services in past month iii) report operating village clinic for at least five days per week

26% (12/47) (95% CI: 15%-40%)

Medicine and diagnostics availability

Percentage of HSAs with all key iCCM medicines and diagnostics in stock on day of assessment (LA, amoxicillin, ORS, zinc, RDTs, timer)

60% (28/47) (95% CI: 45%-73%)

LA (1x6) 87%

LA (2x6) 79%

RDTs 89%

Amoxicillin 79%

ORS 79%

Zinc 83%

Timer 87%

Paracetemol 89%

Eye antibiotic ointment 68%



Percentage of HSAs with all medicines and diagnostics in stock on the day of assessment (all above medicines and supplies)

40% (19/47) (95% CI: 27%-55%)

Percentage of HSAs reporting no stockouts of essential iCCM supplies lasting seven days or more in the month before the survey (LA 1x6 and 2x6, RDTs, amoxicillin, ORS, zinc)

64% (30/47) (95% CI: 49%-77%)

LA (1x6) 83%

LA (2x6) 79%

RDTs 87%

Amoxicillin 75%

ORS 79%

Zinc 81%

Percentage of HSAs reporting no stockouts of all iCCM medicines and supplies lasting seven days or more in the month before the survey

47% (22/47) (95% CI: 33%-61%)

Percentage of HSAs who referred sick child cases due to medicine stockouts in the last one month (based on register review)

13% (95% CI: 6%-26%) Mean: 1.5 cases Range: 0-30 cases

Supervision Percentage of HSAs who received at least one supervision session during the prior three months during which registers were reviewed

66% (31/47) (95% CI: 51%-78%)

A. Review your treatment register? 97%

B. Check your supplies and equipment levels? 97%

C. Use a supervision checklist? 100%

D. Administer a case scenario? 84%

E. Observe you manage a sick child? 72%

F. Observe an mRDT being performed? 72%

G. Meet with village leaders? 56%

H. Give you feedback on your CCM activities? 97%

Percentage of HSAs who received at least one mentorship session during the prior three months with observation of case management (clinical supervision)

55% (26/47) (95% CI: 41%-69%)

Service availability and activity levels

Percentage of HSAs who report typically operating their village clinic:

i) Less than two days per week 6%

ii) Two or more days per week 94%

iii) Five or more days per week 26%

Number of days HSAs report operating village clinic per week Mean: 3.3 Median: 2.0

Percentage of HSAs who report typically operating their village clinic:

i) Less than eight days in the past month 34%

ii) Eight or more days in the past month 66%

iii) 16 or more days in the past month 32%

Number of days HSAs report operating village clinic per month Mean: 12.8 Median: 10.0

Number of days HSAs report working from health facility in last month Mean: 5.5 Median: 4.0

Number of sick child cases treated in the last one month Mean: 43.5 Median: 37.0 Range: 0-220

Percentage of HSAs who referred one or more sick child cases for danger signs in the last one month

36% (17/47) (95% CI: 23%-51%) Mean: 0.5 cases Range: 0-3 cases

Recording completeness

Percentage of HSAs with complete recording for use of mRDTs for five most recent cases presenting with fever

91% (43/47) (95% CI: 79%-97%)

Percentage of HSAs with complete recording of respiratory rate for five most recent cases presenting with cough/difficult breathing

85% (40/47) (95% CI: 71%-93%)

Data display and use

Percentage of HSAs who were trained on the data use display package and received data use templates 51% (24/47)



Percentage of HSAs trained in the package who report using the templates and can show completed templates for the last three completed months 33% (13/34)

Percentage of HSAs trained in the package who have the data use templates displayed where can be easily seen (e.g., on wall or other visible location) 29% (10/34)

Percentage of HSAs trained in the package who give one or more examples of how they use the data N/A

N/A = not available

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