HISP – Health Information Systems Program - Forsiden · HISP – Health Information Systems...
Transcript of HISP – Health Information Systems Program - Forsiden · HISP – Health Information Systems...
Background and Overview DHIS – District Health information System HISP – Health Information Systems Program Global Open Source Software development & application ICT for better health ICT for development
Health Information Systems Program and DHIS 2
• HISP is a global network headed and initiated at the Department of Informatics, University of Oslo since 1994
• DHIS 2 open source software developed, customized and used for reporting, analysis and dissemination of health data
• Core funding from Norad • Partners: WAHO, UNICEF, WHO
(PAHO/CAREC, WPRO, AFRO) • Used by projects funded by e.g. USAID,
CDC, GIZ • http://dhis2.org
South Africa
Malawi
Tanzania
Burkina Faso
Kenya
India
Norway
HISP collaborative Network of Action
Health Information Systems Research, Implementation Development
Use of information for action Integration & Interoperability
Open Source Software Sharing across the world DHIS2; National HIS &
Individual tracking
Capacity Building Training, Education, Research
Training of health workers Graduate courses,
Masters, PhD
Botswana
Vietnam Togo
others Nigeria Liberia
Ghana
Sierra Leone
Gambia
Côte d’Ivoir Sri Lanka Mali
Bangladesh
Uganda
Network of Action eksempel West Africa: HIS Centre of excellence
= National HIS deployment = National start-up / pilot = early national initiative or program-specific deployment
ECOWAS Regional Deployment
DHIS – Current status
EAC Regional
Deployment
DHIS – District Health information System HISP – Health Information Systems Program University of Oslo; education, research & development
Background: • HISP started 1994 in “New” pos apartheid South Africa • Development DHIS 1 started 1997 & 2002 National Standard • DHIS 1 & HISP to India from 2000 • DHIS 1 spread to many countries in Africa from 2000 • (2000-2010) Develop Masters Programs in South Africa,
Mozambique, Malawi, Tanzania, Ethiopia, Sri Lanka • PhD program inn Oslo, 30 students from Africa!
DHIS 2: Web & Fully Open Source • Development of DHIS2 in Java started 2004 • First implementation Kerala –India 2006 • With HMN & Sierra Leone from 2007
• develop DHIS to HMN + “African requirements” • The Gambia from 2009; + more West African countries • In India: implemented in many states
• + Bangladesh & Sri Lanka • GIS developed with WHO + More functionality • 2010: Full Health Information Architecture: - SDMX-HD Interoperability Standard launched in Accra 2011+ : Kenya, Ghana, + & Cloud based infrastructure
• Inequity between blacks & whites, rural & urban, urban & “peri-urban”, former “homelands”, etc.
• “Equity” main target – But how to know whether targets are achieved?
• Need standard data from across the country on – Health status & Health services provision
• Problem: No coordinated data system – no standards • Fragmented information systems
• HISP key actor in developing the new unified Health Information System in South Africa
HOW it started: South Africa 1994 /95 – Problems & challenges:
Dental unit 1 PAWC
City Health Clinic 1
54 private medical pract.
Geriatric Services
MOU (Midwife&
obstetric unit) PAWC
23 private dental pract.
12 private pharmacies
Private hospital: 31 medical specialists
Day Hospital DNHPD
UWC Oral Health Centre
City Health Clinic 2
City Health Clinic 3
City Health Clinic 4
City Health Clinic 5
Dental unit 2 PAWC
Dental unit 3 PAWC
12-15 NGOs
School Health
DNHDP Pretoria
Groote Schuur Hospital
PAWC
DNHDP Western Cape City Health
MITCHELL’S PLAIN
Environmental office
Mandalay Mobile clinic
RSC Youth Health Services
Psyciatric hospital PAWC
RSC
Outside hospitals
Births Deaths Notifiable diseases
New /emerging flow of information
Apartheid legacy: a fragmented and top down health structure as reflected and ‘reproduced’ every day by the information systems Information infrastructure - Installed base
South Africa 1994 /95 – Problems & challenges :
Hospital PAWC
Clinic RSC
Clinic RSC
Clinic PAWC
Private
Private
NGO
Cape Town RSC
Cape Town PAWC
Malmesbury PAWC
DNHPD Western Cape
Family Planning
MOU PAWC
School Health Hospital
Clinic
Private NGO
A) Pre-apartheid centralised, vertical and fragmented structure in Atlantis (simplified).
School Health
Clinic
Clinic
A B
B) Decentralised integrated district model As according to the ANC Health Plan
Database Info. office
Higher levels
Health programs
Mother Child
Strategy: Information management at district level - From fragmentation to integration; Decentralisation: From central control to local empowerment
Record of patients seen Summary of key information
Data entry into database
Data analysis and use
NGOs (Non-gov.
Organisations)
Clinics
DISTRICT
INFORMATION SYSTEM
& DATABASE
DISTRICT HEALTH
MNG. TEAM
Traditional healers
Private Sector
Health Committees
Maternity/ Midwife
units
Day hospitals
Psychiatric services
Nutrition
TB
STD/ AIDS
Local Government
Special Interest Groups
Health & Welfare
Forum
Dental Services Circumcision
Surgeons
Family planning
GOVERNMENT NON-GOVERNMENT
COMMUNITY STRUCTURES
C O M M U N I T Y
HEALTH PROGRAMS
Higher levels
Unions
Referrals
HEALTH SERVICES
V E R T I C A L
School Health
Environmental Health
Information from other sources, e.g. Birth / death registers; TB register, census data, socio-economic data
Example: HMN architecture - National data warehouse
Data warehouse
DHIS 2 LMIS
HR EMR
Measles under 1 year coverage by district 2006(Measles doses given to children < 1 year / total population < 1 year)
74.781.3 79.0 80.7
89.594.4
80.0 79.9
93.6 93.8
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
ChakeChakeDistrict
Michew eniDistrict
MkoaniDistrict
WeteDistrict
CentralDistrict
North ADistrict
North BDistrict
SouthDistrict
UrbanDistrict
WestDistrict
Pemba Zone Unguja Zone
District
Annu
al m
easle
s cov
erag
e %
Data from Mobile devises
-Data mart -Meta data -Visualising tools
Dashboard
Graphs
Maps
Getting data in - Data warehousing Getting data out - Decision support systems
Web Portal
Mobile
Output tailored to the range of devices and infrastructures
Lightweight Browser
SMS
Android app or browser Tablet
PC/laptop
Level of health system
Global/Region
Countries/ Health Programs
Facility
Patient
District
Quantity of data Data granularity Information needs
Summary indicators General, e.g. MDG
Indicators district management
Indicators National /program
Facility management
Patient records, tracking & care More data
Less data
Different levels of the health system – different needs for information
Hierarchy of data standards: • Balancing national need for standards with local need for flexibility to include additional indicators • All levels have freedom to define their own standards as long as they adhere to the standards of the level above (core data set)
Patient – individual client Level
Health Facility Level
Sub-National Level
National Level
Regional Level
Standard Indicators, & datasets:
Patient
Facility
Sub National
National
Regional - ECOWAS
Hierarchy of Indicator & Data Standards
Main components of a HIS (also the DHIS metadata model)
The organisational hierarchy service-delivery and administrative organisational units organised in a
hierarchy of typically 4-6 levels and following administrative areas (country, province, district/municipality, sub-district)
Ministry of Public Health
(MINSAP)
Provincial health office
Provincial health office…….………..
Municipal health office
Nationalhealth units
Municipal health office
Municipal health office…….…….
Health area
Health area
Working group
Working group
Working group
Family doctor office
Family doctor office
Family doctor office
Family doctor office
…..…
……
Provincial health units
Municipalhealth units
PHC services
……..…
DHIS metadata model cont. Collection forms, data elements, indicators and reports
Data is collected/imported in data sets; typically in data
entry forms that are typically grid-based
“Atomic variables” => Flexibility. Each value captured in the form is linked to a data element which describes the
phenomena captured, e.g. “Number of BCG vaccines given”, and referencing the organisation unit (e.g. a clinic) and the
period (Sep 2008) the specific form is valid for. + Any other relevant data, e.g. Population census, data on
number of beds, doctors, nurses etc.
Data captured from paper forms – in health facility or at district level
BEFORE: data exported to higher levels on memory sticks NOW: direct on national server
DHIS metadata model cont.
Data elements and indicators
Combining & analysing any data in formulas. For better comparative analysis indicators can be defined as
formulas combining data elements, e.g. BCG Coverage < 1 year =
100 % x BCG vaccines given < 1 year / Population < 1 year
Data elements and indicators can be grouped across many dimensions
and the values are visualised in various output formats (tables, charts, maps).
DHIS Branching . Risk of forking Example India
Synchronisation
Continuous DHIS 2 development; common core, different local applications
Global distributed participatory development of DHIS 2 – SW end-user application which is used differently in each participating context Is it possible?
India Use Context:
30 states, each a country
e.g. Vietnam
Use Context
e.g. Tanzania
Use Context
Sierra Leone 2008-09: No National Internet - aggregate data from all programs & services (horizontal integration)
HF1 HF2 HF3 HFn …..
Harmonised paper forms
Health facilities and hospitals reporting aggregate paper forms to HIS office at district
Nat
iona
l Lev
el
Dist
rict L
evel
Fa
cilit
y Le
vel
HIS office Integrated data management
HIS office Integrated data entry
Information use
Information use
Information use
Feedback
Feedback
DHIS: District data repository
Other districts reporting to national
DHIS:National data repository
Data and tools available to all staff
Session 3e, 29 May 2013 IST-Africa 2013 2013 University of Oslo
Mobile subscribers per 100 persons
Source: World Bank
Session 3e, 29 May 2013 IST-Africa 2013 2013 University of Oslo
Total bandwidth of communication cables to Africa
Source: AFRINIC
DHIS2
Online Data capture Measles under 1 year coverage by district 2006
(Measles doses given to children < 1 year / total population < 1 year)
74.781.3 79.0 80.7
89.594.4
80.0 79.9
93.6 93.8
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
ChakeChakeDistrict
Michew eniDistrict
MkoaniDistrict
WeteDistrict
CentralDistrict
North ADistrict
North BDistrict
SouthDistrict
UrbanDistrict
WestDistrict
Pemba Zone Unguja Zone
District
An
nu
al m
ea
sle
s c
ov
era
ge
%
Online data use; web pivot reports, charts, maps
Datamart - pivot tables Archive -reports, - Charts, maps
Browser
Offline Data Capture
Offline data use application
Online / / Offline
BCG: 12 PENTA1:10 PENTA2: 7 PENTA3:11
Mobile Data Use
Mobile Data Capture
Cloud infrastructure - Africa since 2011, e.g. Kenya, Ghana
Session 3e, 29 May 2013 IST-Africa 2013 2013 University of Oslo
Online central server vs Offline stand-alone HIS
DHIS
: Services de prévention: Vaccination, Mère & enfants, etc.,
Utilisateurs de données primaires & fournisseur de données
Dossier patients iHRIS
gestion RH Logistique
& medicament
Rapportage Mobile
Utilisateurs de Données primaires & fournisseur De données
Utilisateurs de données traitées et intégrées
Integration de technologies, données & grammes de santé
Integrated health information architecture: Data warehouse - integrating sub-systems, services, programs
SIG
Analyse de données
Maladie specifiques: TB, VIH/SIDA, Decl. Obligat, etc.
Rapport papier:
Transfert electronique
SDMX-HD: Statistical Data & Metadata Exchange for the Health Domain
DHIS : Data warehouse Statistical data
OpenMRS : Medical records
iHRIS: Human Resource records
SDMX-HD: Metadata “order” from DHIS to OpenMRS, e.g.: #deliveries @health centre X for month of May
SDMX-HD: Metadata “order” from DHIS to iHRIS, e.g.: #midwifes @health centre X for month of May DHIS is calculating
the indicator: Deliveries per midwife
SDMX-HD: Piloted in Sierra Leone and launched in Accra
Number of clients per clinical worker per day, by district, 2008 and 2009
0
5
10
15
20
25
Western Area Moyamba Kono Kailahun Bonthe Port Loko Bo Kenema Kambia Koinadugu Bombali Tonkolili Pujehun
Total
PHU (All) Chiefdom (All)
Average of Clients/Clinician/Day
District
Integrated Human Resource and Health service data - made possible by systems integration & interoperability
India: Integrated architecture (design) of interoperable systems An integrative “umbrella” across programs, sub-systems & infrastructures (paper, computers, Internet, mobile telephones)
Data warehouse
Reports, GIS, Pivot, graphs, etc,
Import Electronic data
Data capture from paper reports
Medical Records
Register pregnant women & children for immunization
Human Resource records
Export electronic summary data
Monthly summary reports
Replicated at each Administrative Level: National State/Province District
Data from / to Mobile telephones
Household Tracking
iHRIS
DHIS2
OpenMRS / DHIS2 tracker
DHIS2/ NBIT