2016 Infokes Guest Lecture Jogja jorn UGM based on Colombo HISP Network
•
Health Information Systems
Program HISP & DHIS 2: Past,
Current,
Future
HISP : global network
for HIS
development, Open Source Software,
education and research
• DHIS 2 open source software : reporting,
analysis and dissemination of health data
& tracking individuals
• Started in South Africa in the 1990’s
- Now 40+ countries using DHIS 2
• DHIS 2: core funding from Norad and
PEPFAR.
• Global Fund: Country implementations
• Partners: WHO, Global Fund, GAVI,
UNICEF
DHIS2 country systems & PEPFAR
Early phase / pilots
Early implementation / many states in
India
Nation-wide
PEPFAR
DHIS – District Health information Software
HISP – Health Information Systems Program
Background:
• HISP started 1994 in “New” post apartheid South Africa
• Development DHIS started 1997 & 2002 National Standard
• DHIS v1 & HISP to India from 2000
• DHIS v1 spread to many countries in Africa from 2000
• 2000-2013 - Develop Masters Programs in Mozambique,
South Africa, Malawi, Tanzania, Ethiopia & Sri Lanka
• PhD program, 40 students from Asia and Africa
…… who are later running the Masters programs
Background in ‘NEW’ post apartheid South Africa
1994-2000
HISP approach – from South Africa:
•Local use of information;
•Maximise end-user control;
•Local empowerment &
•bottom-up design and system development
Focus: Integration and use of data
1) standardisation of primary health care data &
2) ‘flexible’ – easy to change and adapt new data sets
•1998/99: implementation in two provinces
•1999/2000 - onwards: National implementation
HISP / DHIS timeline (2):
From ‘Stand alone’ MS Access – to DHIS2
Web & global footprint
• 2004 – 2010: New technological paradigm:
o Web based open source – Java frameworks
o 2006 Kerala; 2009 Sierra Leone
• 2011 – 2013: ‘Cloud’ and online
o ‘Cables around Africa’:
o Kenya, Ghana, Uganda, Rwanda, …
• 2014 – 2016: 40+ countries in Asia and Africa use
DHIS2 as national HIS
HISP Approach to information systems –
Background
• Information for decision making
• Data use – culture of information
• ‘Power to the users’ – Empower health workers, local levels,
communities
• Training & education
• Participatory design
• Focus on important data & indicators:
• Data standardisation, harmonisation of data sets
• ‘Less is better’
Data Use, for what
Data:
• Where?
• What?
• When?
Analysis
& decisions:
• Why?
• How to?
‘When, What, Where’:
Basis for DHIS2 data model
When
Dates, time period,
e.g. August 2011,
Quarter 3 2011
Period
1
N
1
Data Value
N
1
Data Element
What
N
National
State /
Province
Where
Location (Organisation Unit)
Organised in an
Organisational hierarchy
Disaggregated by
Dimensions, e.g. sex, age
Organised in
Data sets
District
SubDistrict
Health
facility
Data collection, analysis, action
TALI Tool: Tool for Measuring levels of Information
USAGE & The DHIS2
Level 0: The DHIS2 may be in various stages of development,
but not yet fully functional
Level 1: System is functioning technically : data reporting
completeness as a key indicator
Level 2: Data is analysed, disseminated and used. Data quality
(accuracy, timeliness, completeness) and feedback reports and
graphs on the wall are key indicators
Level 3: Data used for planning and decision making:
Indicators: evidence of use of data to measure achievements
in reaching targets in e.g. annual planning process
Motivation for ‘Standardisation’:
South Africa 1994 /95 – Problems & challenges:
• Inequity between blacks & whites, rural & urban, urban & “periurban”, former “homelands”, etc.
• “Equity” main target
– Need data 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
• HISP key actor in developing the new unified Health Information
System in South Africa
–‘
Example South Africa, Atlantis District 1994:
First Architecture approach: From fragmentation to integration;
Higher
levels
Health
programs
DNHPD
Western Cape
Cape Town
RSC
Cape Town
PAWC
Family Planning
Clinic
RSC
Clinic
RSC
Malmesbury
PAWC
Clinic
PAWC
Hospital
PAWC
Private
School
Health
A
Clinic
Mother
Child
NGO
Private
MOU
PAWC
A) Post-apartheid centralised, vertical and
fragmented structure in Atlantis (simplified).
Clinic
Database
Info. office
School
Health
Clinic
Hospital
B
NGO
Private
B) Decentralised integrated district model
As according to the ANC Health Plan
Intergation: Still the same challenge !!
Different levels of the health system
– different needs for information
Level of health
system
Quantity of data
Data granularity
Information needs
Global/Region
Less data
Summary indicators
General, e.g. MDG
Countries/
Health Programs
Indicators
National /program
District
Indicators district
management
Facility
Facility
management
Patient
Patient records,
tracking & care
More data
Hierarchy of data standards:
• Balancing national need for standards with local need for
flexibility to include additional indicators
• All levels – province, district, facility – can define their own
standards as long as they adhere to the standards of the level above
Hierarchy of Indicator
& Data Standards
Regional Level
National Level
Standard
Indicators,
& datasets:
Patient
Facility
Sub-National Level
Health Facility Level
Patient – individual client Level
Sub National
National
Regional ECOWAS
3 components of the HISP ‘Network of Action’
Health Information Systems
Integration, standards, architecture
Use of information for action
Health management
Free & Open Source Software
Distributed DHIS2 development
– Sharing across the world
knowledge & support
Mozambique
South Africa
Vietnam
Norway
Uganda
Nigeria
Kenya
Ghana
others
Rwanda
Sri Lanka
India
Bangladesh
Phillipines
Laos
Indonesia
Building Capacity,
Academies, Education, Research
Training of health workers
Graduate courses, Masters, PhD
Sharing teaching /courses
Regional approach:
Implementing DHIS2 through HISP nodes
Early phase / pilots / preparation
Under implementation / many states in
India
Nation-wide
PEPFAR
HISP
West Africa
Nigeria,
Ghana, ..
HISP
Kenya
Tanzania
Uganda
Rwanda HISP India & Vietnam
& HISP Sri Lanka!
HISP South Africa
HISP – DHIS2 Community:
principles
• Free and Open Source Software &
training / educational materials, etc.
• Development and implementation of
sustainable & integrated Health
Information Systems
• Empower communities, healthcare
workers and decision makers to
improve the coverage, quality and
efficiency of health services
• Developmental approach to capacity
building & research
– Research based development
– Engage HISP groups and health
workers in action research!
WHY SUCH EXPANSION ?
And how to continue to
build the network and open source
platform
Mobile subscribers per 100 persons, Africa
Source: World Bank
Internet: Total bandwidth of communication
cables to Africa South of Sahara
Source: AFRINIC
DHIS = 1/1000
DHIS2 implementations /initial projects
correlated with increase in bandwidth
DHIS 2
implementations
2014
Source: AFRINIC
2015
Improved Internet & mobile network – ‘cloud’ infrastructure
Rapid scaling – from ‘hundreds’ of installations to 1
Online system – one server
Easier to integrate / interoperability with other systems
which are also online: web API
& central server
Interoperability
with Other systems
Improved Internet and mobile network: Rapid scaling
Implementation Using central server & “cloud” infrastructure
Online data use; web pivot
reports, charts, maps
Online
Data capture
DHIS2
Mobile Data Use
Mobile
Data
Capture
BCG:
12
PENTA1:10
PENTA2: 7
PENTA3:11
Online / / Offline
Offline data use
Browser
application
Offline
Data Capture
Datamart
- pivot tables
Archive
-reports,
- Charts, maps
HMN architecture (2007) – Integrated National data
warehouse:
DHIS2 Country platform: Integrating health programs
& data sources
Web Portal
Data
from capture
form paper
s
Data from
Mobile devises
LMIS
HR
EMR
act rm
r
t
Ex nsfo
Tra d
a
Lo
Data
warehouse
DHIS 2
Getting data in - Data warehousing
-Data mart
-Meta data
-Visualising
tools
Dashboard
Graphs
Mobile
Maps
Getting data out - Decision support
systems – ‘Business intelligence (BI)
Integrated Health Information Architecture (“Horizontal integration”)
- integrating sub-systems, technologies, health services & programs
Users of processed & integrated data
Data
Aggregate &
indicator data Warehouse
er
p
o
er
t
In
y
Electronic
Medical
Records
Int
y erop
era
ilit
b
a
SDMX -HD
Paper
reports
Performance
Based financing
reporting
HR
Management
Users of
primary data
& data providers
Logistics
& drugs
Finance
bil
it
Mobile
reporting
Paper based systems:
OPD, EPI, RCH,
other programs
Users of primary data
& data providers
Integration of
technologies, systems,
data & health programs
Integration and interoperability
Data transfer
from OpenMRS
To DHIS, e.g.:
#deliveries
@health centre X
for month of May
Interoperability
OpenMRS :
Medical records
DHIS : Data
warehouse
Statistical
data
DHIS is calculating
the indicator:
Deliveries per midwife
Per facility per month
Integration
Data transfer
from iHRIS to
DHIS, e.g.:
#midwifes
@health centre X
for month of May
Interoperability
iHRIS: Human
Resource records
Extending the reach through
mobiles
• User friendly & ’close’ data entry individual level/aggregate
data
• Tracking clients in programs
– sending reminders, e.g. for ANC visits & vaccination
• Feedback – simple reports, text & calls
• Communication – ‘social media’ for both health staff and
community (support, chat,
• Integration with DHIS data warehouse & backbone
infrastructure
• Support wide range of technologies
SMS
Java
Browser
Android
PC/laptop/tablet
All devises integrated in
SMS
e
or
M
bl
i
x
e
f
e
Lightweight
Browser
PC/laptop
Android
app or
browser
Tablet
erprise architecture: 3 Levels (each serving the level abo
Level 1:
Information
Needs, Users, Usage
Across Organisations
“Business level”
Institutional use of information
Level 2:
Software applications
& Information
Systems
“Application level”
Patient
records
Open
MRS
DHIS
Data warehouse
Aggregate data
iHRIS
Applications supporting use
of information
Level 3: “Data
Data & indicator dictionary /standards
Facility register
exchange level”
OpenHIE
Provider register
“Technical level” Health Information Exchange
Interoperability &
ADX
standards, technical
Data Standards and infrastructure supporting the applicatio
infrastructure
Indonesia Data Warehouse &
Dashboard
National level:
Electronic data
sources
BKKBN
(Family
Planning
Board)
BPJS
(Social
Security
Provider)
SITT (TB)
Dashboard
DHIS2
Data warehouse
SIHA
(HIV)
E-Sismal
(Malaria)
NCD
NIHR&D
Logistics
Integrated National HTM
Dashboard
National TB Dashboard
National Malaria Dashboard
TB + rate 2014
By Province
By District
TB +Ve cases by
facilities
Location of Hospital and
Puskesmas
Yogyakarta Hospital and
Puskesmas
Yogyakarta Dashboard
NATIONAL
PROVINCE: All programs
receive reports aggregated by
district –from district programs
KOMDATA
District
AID
MC
IDS
S
H
R
Vaccin
Other
Malari
e
s
a
TB
Data flow
AID
MC
TB
S
H
Vaccin
Other
e
s
IDS
R
Malari
a
Puskesmas – Health facility
DISTRICT:
Each program
manage own data
-Limited
coordination
across programs
PUSKESMAS:
Each Program
Reports to Program in
District
Datafow – Districts with few patient records (Malang)
Pilotitis in Uganda: mHealth mapping
Map of mHealth pilots in Uganda (Sean Blaschke , Unicef Uganda)
Shared Facility
codes
Integrating data
sources
Mapping
Facility codes
Sam
e
code
EPI
Diff
cod eren
es t
Indonesia
Komdat
/HMIS
Nutrition
TB
Facility
Codes
Register
Dashboard
MCH
Malaria
MAPPING
DHIS : Data
warehouse
Statistical
data
Family
Planning
BPJS
Human Resource
records
HIV/
AIDS
LMIS
Integration
- District system
DHIS2
AID
TB
Vaccin S
e MC
IDS
R
H
Malari
a
Other
s
DHIS2
AID
MC
TB
S
H
Vaccin
Other
e
s
PROVINCE/NATIONAL:
Integrated data warehouse
& dashboard used by all
DISTRICT:
Integrated data
warehouse &
dashboard
IDS
R
Malari
a
Puskesmas – Health facility
PUSKESMAS:
Programs use DHIS2,
both data use and
reporting
Integration
- District system
AID
TB
Vaccin S
e MC
IDS
R
H
Malari
a
Other
s
DHIS2
Data access
& use
DHIS2
AID
MC
TB
S
H
Vaccin
Other
e
s
PROVINCE/NATIONAL:
Integrated data warehouse
& dashboard used by all
DISTRICT:
Integrated data
warehouse &
dashboard
IDS
R
Malari
a
Puskesmas – Health facility
PUSKESMAS:
Programs use DHIS2,
both data use and
reporting
OpenHIE Architecture Design
OpenHIE / DHIS Architecture
- Evolving through use
Facility Registry
Data Dictionary
DHIS
2
HMIS
Commun
ity
Dashboard projects in Indonesia
Pusdatin – University of Oslo – UGM
•National data warehouse & dashboard project
• Integration national programs: data by Puskesmas
• Creation of health program-based dashboards (TB,
HIV/AIDS, Malaria, ..)
• Creation of integrated dashboards: indicators
across programs TB-HIV/AIDS, ..
•Yogyakarta province data warehouse
• Province & district based dashboards
• Applying & aligning national data warehouse with
province data warehouse
Initial plans: HSS – Pusdatin – Oslo –UGM
Selection on 5 provinces for DHIS2 implementation
•Provinces where HSS district located
•Identification of data sources and reporting flows in
districts and province
•Applying & aligning national data warehouse with
province and district data
• Including selected district & province specific data
• Electronic data: (semi) automate data transfer
• Manual data capture
•Design and develop of district and province dashboards
Initial plans (2) : HSS – Pusdatin – Oslo –UGM
Capacity building
•Train & develop national expert DHIS2 team –Pusdatin
&UGM
•Train all HSS staff
•Training of Trainers (TOT): Key people from provinces
& districts
•Training & data review and data use in districts
•Continuous hands-on training and support
Challenge:
Capture data from Puskesmas in Districts
Data only by districts at national leve –need to be
captured in the dstricts
•Malaria: Only Excel
•Morbidity data; districts and Puskesmas have different
systems – sending to districts
• Different methods and systems between districts
•MCH data: e.g. excel sent to district
•Vaccination: Jogja has system, different in other
provinces
E-SISMAL to Komdat 2 –
Integrated Data Warehouse
(dhis2 at Pusdatin)
Komdat 2
Approved data by
E-SISMAL Malaria
2
department
DHIS2
E-SISMAL Excel
file at District
Level by
Puskesmas
Data check and
Approval at National /
Province Level
Malaria based
dashboard
DHIS2 : Data
warehouse
Statistical
data
BACK TO THE GLOBAL: Way Forward
Challenge:
•‘Success’ = large number of countries,
organisations, systems & use cases
•Disease surveillance, malaria, TB,
HIV/AIDS, registers, tracker, etc.
•Large number of new requirements
•Central development team becoming
bottleneck !
‘Technical Solution’: DHIS2 - app platform
• How to respond to large amounts of new
requirements?
Enable users & local groups to make
their own apps!
• Web api
• SDK for Android (Software Development
Kit)
• App store for distribution of apps
‘Organisational solution’:
Build strong HISP – DHIS2 community!!
Build network of DHIS2 projects,
countries &universities
• Organise country HISP nodes (Sri Lanka!)
&
• Regional hubs – centres of excellence
• Focus on research and education
•Masters & PhD program critical
From vertical reporting systems
… towards a common data
platformProgress:
More and more
programmes & countries
moving towards single
country platform (e.g. DHIS
2)
Partners working on joint
investment & core functional
requirements
But .. much more
required:
−to establish sound
governance at country level
−To integrate public health
surveillance into routine
systems
−To build adequate capacity
W H O / I n t e r n a t io n a l s t a n d a r d s fo r D H I S 2
Clickheret o g o t o t h e W H O st a n d a r d s w e b p o r t a l, w it h d e t a ile d
in f o r m a t io n a n d in st a lla t io n in st r u c t io n s f o r u sin g t h e se t e m p la t e s a n d t o o ls.
S t a n d a r d t o o ls a n d t e m p la t e s
I n d ic a to rs
R e f e re n c e f a c ility
in d ic a to rs
Learn m o re…
Im p o rt
A p p fo r b r o w s i n g o f D H IS 2 a g g r e g a t e m e t a d a t a , a s w e l l a s to a l i s t o f W H O r e fe r e n ce
i n d i ca t o r s .
Learn m o re…
I n st a l l
H o s p it a l m o rta lity
m o d u le
M o d u l e fo r co l l e ct i o n o f h o s p i t a l m o r t a l i t y d a t a u s i n g t h e IC D -1 0 s t a r t-u p m o r t a l i t y l i s t.
I n cl u d e s d a t a e n t r y t e m p l a t e a n d b a s i c o u t p u t s .
Learn m o re…
Im p o rt
H I V d a ta c o lle c tio n
f o rm s
T h e d a t a co l l e ct i o n fo r m fo r H IV , i n cl u d i n g d a t a e l e m e n t s (w i t h d i s a g g r e g a t i o n s ) a n d
d a t a v a l i d a t i o n r u l e s..
Learn m o re…
Im p o rt
M a la ria d a ta c o lle c tio n
f o rm s
T h e d a t a co l l e ct i o n fo r m fo r M a l a r i a , i n cl u d i n g d a t a e l e m e n t s (w i t h d i s a g g r e g a t io n s ) a nd
d a t a v a l i d a t i o n r u l e s.
Learn m o re…
Im p o rt
O t h e r d a t a c o lle c tio n
f o rm s
T h e d a t a co l l e ct i o n fo r m fo r o t h e r p r o g r a m m e s / a r e a s , i n cl u d i n g d a t a e l e m e n t s (w i t h
d i s a g g r e g a t i o n s) a n d d a t a v a l i d a t i o n r u l e s , e .g . T B , E P I, M C H e tc.
Learn m o re…
Im p o rt
W H O d a ta q u a lity to o l
A p p fo r p e r fo r m i n g r o u t i n e a n d a n n u a l d a t a q u a l i t y ch e ck s o n a g g r e g a t e h e a l t h fa ci l i t y
d a t a , a cco r d i n g t o t h e W H O D a t a q u a l i t y r e v ie w t o o l k i t.
Learn m o re…
I n st a l l
H I V d a s h b o a rd s
D a s h b o a r d s fo r u se o f r o u t i n e fa ci l i t y -b a s e d H IV d a t a . In cl u d e s d a s h b o a r d s , a n a l y t i ca l
o u t p u t s a n d i n d i ca t o r s .
Learn m o re…
Im p o rt
M a la ria d a s h b o a rd s
D a s h b o a r d s fo r u se o f r o u t i n e fa ci l i t y -b a s e d m a la r i a d a t a . In cl u d e s d a s h b o a r d s ,
a n a l y t i ca l o u t p u t s a n d i n d i ca t o r s .
Learn m o re…
Im p o rt
O t h e r d a s h b o a rd s
D a s h b o a r d s a n d d a t a co l l e ct i o n t e m p l a t e s fo r a d d i t i o n a l p r o g r a m m e s / a r e a s , e .g . T B ,
E P I, M C H e t c
Learn m o re…
Im p o rt
Learn m o re…
Im p o rt
D a t a d ic tio n a ry a p p
D a ta c o lle c tio n
D a ta q u a lity
D a s h b o a rd s
S y ste m
W H O r e co m m e n d e d i n d i ca t o r s fo r r o u t i n e fa ci l i t y d a t a .
M a s t e r F a c ilit y L is t
G u i d a n ce o n e st a b l i sh i n g a n a t i o n a l m a s t e r fa ci l i t y l i s t .
2016Q1
Status WHO DHIS 2
standards/tools
2016Q2
2016Q3
2016Q4
Data Quality Tool
Data Dictionary
Standards Repository
HIV module
EPI module
RMNCAH
module
TB module
NTD module(s)
Malaria module
Cause of death (ICD-SMoL)
TB patient tracker
TB-MDR patient tracker
Not started/early
In progress
Done/nearly done
Health Information Systems
Program HISP & DHIS 2: Past,
Current,
Future
HISP : global network
for HIS
development, Open Source Software,
education and research
• DHIS 2 open source software : reporting,
analysis and dissemination of health data
& tracking individuals
• Started in South Africa in the 1990’s
- Now 40+ countries using DHIS 2
• DHIS 2: core funding from Norad and
PEPFAR.
• Global Fund: Country implementations
• Partners: WHO, Global Fund, GAVI,
UNICEF
DHIS2 country systems & PEPFAR
Early phase / pilots
Early implementation / many states in
India
Nation-wide
PEPFAR
DHIS – District Health information Software
HISP – Health Information Systems Program
Background:
• HISP started 1994 in “New” post apartheid South Africa
• Development DHIS started 1997 & 2002 National Standard
• DHIS v1 & HISP to India from 2000
• DHIS v1 spread to many countries in Africa from 2000
• 2000-2013 - Develop Masters Programs in Mozambique,
South Africa, Malawi, Tanzania, Ethiopia & Sri Lanka
• PhD program, 40 students from Asia and Africa
…… who are later running the Masters programs
Background in ‘NEW’ post apartheid South Africa
1994-2000
HISP approach – from South Africa:
•Local use of information;
•Maximise end-user control;
•Local empowerment &
•bottom-up design and system development
Focus: Integration and use of data
1) standardisation of primary health care data &
2) ‘flexible’ – easy to change and adapt new data sets
•1998/99: implementation in two provinces
•1999/2000 - onwards: National implementation
HISP / DHIS timeline (2):
From ‘Stand alone’ MS Access – to DHIS2
Web & global footprint
• 2004 – 2010: New technological paradigm:
o Web based open source – Java frameworks
o 2006 Kerala; 2009 Sierra Leone
• 2011 – 2013: ‘Cloud’ and online
o ‘Cables around Africa’:
o Kenya, Ghana, Uganda, Rwanda, …
• 2014 – 2016: 40+ countries in Asia and Africa use
DHIS2 as national HIS
HISP Approach to information systems –
Background
• Information for decision making
• Data use – culture of information
• ‘Power to the users’ – Empower health workers, local levels,
communities
• Training & education
• Participatory design
• Focus on important data & indicators:
• Data standardisation, harmonisation of data sets
• ‘Less is better’
Data Use, for what
Data:
• Where?
• What?
• When?
Analysis
& decisions:
• Why?
• How to?
‘When, What, Where’:
Basis for DHIS2 data model
When
Dates, time period,
e.g. August 2011,
Quarter 3 2011
Period
1
N
1
Data Value
N
1
Data Element
What
N
National
State /
Province
Where
Location (Organisation Unit)
Organised in an
Organisational hierarchy
Disaggregated by
Dimensions, e.g. sex, age
Organised in
Data sets
District
SubDistrict
Health
facility
Data collection, analysis, action
TALI Tool: Tool for Measuring levels of Information
USAGE & The DHIS2
Level 0: The DHIS2 may be in various stages of development,
but not yet fully functional
Level 1: System is functioning technically : data reporting
completeness as a key indicator
Level 2: Data is analysed, disseminated and used. Data quality
(accuracy, timeliness, completeness) and feedback reports and
graphs on the wall are key indicators
Level 3: Data used for planning and decision making:
Indicators: evidence of use of data to measure achievements
in reaching targets in e.g. annual planning process
Motivation for ‘Standardisation’:
South Africa 1994 /95 – Problems & challenges:
• Inequity between blacks & whites, rural & urban, urban & “periurban”, former “homelands”, etc.
• “Equity” main target
– Need data 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
• HISP key actor in developing the new unified Health Information
System in South Africa
–‘
Example South Africa, Atlantis District 1994:
First Architecture approach: From fragmentation to integration;
Higher
levels
Health
programs
DNHPD
Western Cape
Cape Town
RSC
Cape Town
PAWC
Family Planning
Clinic
RSC
Clinic
RSC
Malmesbury
PAWC
Clinic
PAWC
Hospital
PAWC
Private
School
Health
A
Clinic
Mother
Child
NGO
Private
MOU
PAWC
A) Post-apartheid centralised, vertical and
fragmented structure in Atlantis (simplified).
Clinic
Database
Info. office
School
Health
Clinic
Hospital
B
NGO
Private
B) Decentralised integrated district model
As according to the ANC Health Plan
Intergation: Still the same challenge !!
Different levels of the health system
– different needs for information
Level of health
system
Quantity of data
Data granularity
Information needs
Global/Region
Less data
Summary indicators
General, e.g. MDG
Countries/
Health Programs
Indicators
National /program
District
Indicators district
management
Facility
Facility
management
Patient
Patient records,
tracking & care
More data
Hierarchy of data standards:
• Balancing national need for standards with local need for
flexibility to include additional indicators
• All levels – province, district, facility – can define their own
standards as long as they adhere to the standards of the level above
Hierarchy of Indicator
& Data Standards
Regional Level
National Level
Standard
Indicators,
& datasets:
Patient
Facility
Sub-National Level
Health Facility Level
Patient – individual client Level
Sub National
National
Regional ECOWAS
3 components of the HISP ‘Network of Action’
Health Information Systems
Integration, standards, architecture
Use of information for action
Health management
Free & Open Source Software
Distributed DHIS2 development
– Sharing across the world
knowledge & support
Mozambique
South Africa
Vietnam
Norway
Uganda
Nigeria
Kenya
Ghana
others
Rwanda
Sri Lanka
India
Bangladesh
Phillipines
Laos
Indonesia
Building Capacity,
Academies, Education, Research
Training of health workers
Graduate courses, Masters, PhD
Sharing teaching /courses
Regional approach:
Implementing DHIS2 through HISP nodes
Early phase / pilots / preparation
Under implementation / many states in
India
Nation-wide
PEPFAR
HISP
West Africa
Nigeria,
Ghana, ..
HISP
Kenya
Tanzania
Uganda
Rwanda HISP India & Vietnam
& HISP Sri Lanka!
HISP South Africa
HISP – DHIS2 Community:
principles
• Free and Open Source Software &
training / educational materials, etc.
• Development and implementation of
sustainable & integrated Health
Information Systems
• Empower communities, healthcare
workers and decision makers to
improve the coverage, quality and
efficiency of health services
• Developmental approach to capacity
building & research
– Research based development
– Engage HISP groups and health
workers in action research!
WHY SUCH EXPANSION ?
And how to continue to
build the network and open source
platform
Mobile subscribers per 100 persons, Africa
Source: World Bank
Internet: Total bandwidth of communication
cables to Africa South of Sahara
Source: AFRINIC
DHIS = 1/1000
DHIS2 implementations /initial projects
correlated with increase in bandwidth
DHIS 2
implementations
2014
Source: AFRINIC
2015
Improved Internet & mobile network – ‘cloud’ infrastructure
Rapid scaling – from ‘hundreds’ of installations to 1
Online system – one server
Easier to integrate / interoperability with other systems
which are also online: web API
& central server
Interoperability
with Other systems
Improved Internet and mobile network: Rapid scaling
Implementation Using central server & “cloud” infrastructure
Online data use; web pivot
reports, charts, maps
Online
Data capture
DHIS2
Mobile Data Use
Mobile
Data
Capture
BCG:
12
PENTA1:10
PENTA2: 7
PENTA3:11
Online / / Offline
Offline data use
Browser
application
Offline
Data Capture
Datamart
- pivot tables
Archive
-reports,
- Charts, maps
HMN architecture (2007) – Integrated National data
warehouse:
DHIS2 Country platform: Integrating health programs
& data sources
Web Portal
Data
from capture
form paper
s
Data from
Mobile devises
LMIS
HR
EMR
act rm
r
t
Ex nsfo
Tra d
a
Lo
Data
warehouse
DHIS 2
Getting data in - Data warehousing
-Data mart
-Meta data
-Visualising
tools
Dashboard
Graphs
Mobile
Maps
Getting data out - Decision support
systems – ‘Business intelligence (BI)
Integrated Health Information Architecture (“Horizontal integration”)
- integrating sub-systems, technologies, health services & programs
Users of processed & integrated data
Data
Aggregate &
indicator data Warehouse
er
p
o
er
t
In
y
Electronic
Medical
Records
Int
y erop
era
ilit
b
a
SDMX -HD
Paper
reports
Performance
Based financing
reporting
HR
Management
Users of
primary data
& data providers
Logistics
& drugs
Finance
bil
it
Mobile
reporting
Paper based systems:
OPD, EPI, RCH,
other programs
Users of primary data
& data providers
Integration of
technologies, systems,
data & health programs
Integration and interoperability
Data transfer
from OpenMRS
To DHIS, e.g.:
#deliveries
@health centre X
for month of May
Interoperability
OpenMRS :
Medical records
DHIS : Data
warehouse
Statistical
data
DHIS is calculating
the indicator:
Deliveries per midwife
Per facility per month
Integration
Data transfer
from iHRIS to
DHIS, e.g.:
#midwifes
@health centre X
for month of May
Interoperability
iHRIS: Human
Resource records
Extending the reach through
mobiles
• User friendly & ’close’ data entry individual level/aggregate
data
• Tracking clients in programs
– sending reminders, e.g. for ANC visits & vaccination
• Feedback – simple reports, text & calls
• Communication – ‘social media’ for both health staff and
community (support, chat,
• Integration with DHIS data warehouse & backbone
infrastructure
• Support wide range of technologies
SMS
Java
Browser
Android
PC/laptop/tablet
All devises integrated in
SMS
e
or
M
bl
i
x
e
f
e
Lightweight
Browser
PC/laptop
Android
app or
browser
Tablet
erprise architecture: 3 Levels (each serving the level abo
Level 1:
Information
Needs, Users, Usage
Across Organisations
“Business level”
Institutional use of information
Level 2:
Software applications
& Information
Systems
“Application level”
Patient
records
Open
MRS
DHIS
Data warehouse
Aggregate data
iHRIS
Applications supporting use
of information
Level 3: “Data
Data & indicator dictionary /standards
Facility register
exchange level”
OpenHIE
Provider register
“Technical level” Health Information Exchange
Interoperability &
ADX
standards, technical
Data Standards and infrastructure supporting the applicatio
infrastructure
Indonesia Data Warehouse &
Dashboard
National level:
Electronic data
sources
BKKBN
(Family
Planning
Board)
BPJS
(Social
Security
Provider)
SITT (TB)
Dashboard
DHIS2
Data warehouse
SIHA
(HIV)
E-Sismal
(Malaria)
NCD
NIHR&D
Logistics
Integrated National HTM
Dashboard
National TB Dashboard
National Malaria Dashboard
TB + rate 2014
By Province
By District
TB +Ve cases by
facilities
Location of Hospital and
Puskesmas
Yogyakarta Hospital and
Puskesmas
Yogyakarta Dashboard
NATIONAL
PROVINCE: All programs
receive reports aggregated by
district –from district programs
KOMDATA
District
AID
MC
IDS
S
H
R
Vaccin
Other
Malari
e
s
a
TB
Data flow
AID
MC
TB
S
H
Vaccin
Other
e
s
IDS
R
Malari
a
Puskesmas – Health facility
DISTRICT:
Each program
manage own data
-Limited
coordination
across programs
PUSKESMAS:
Each Program
Reports to Program in
District
Datafow – Districts with few patient records (Malang)
Pilotitis in Uganda: mHealth mapping
Map of mHealth pilots in Uganda (Sean Blaschke , Unicef Uganda)
Shared Facility
codes
Integrating data
sources
Mapping
Facility codes
Sam
e
code
EPI
Diff
cod eren
es t
Indonesia
Komdat
/HMIS
Nutrition
TB
Facility
Codes
Register
Dashboard
MCH
Malaria
MAPPING
DHIS : Data
warehouse
Statistical
data
Family
Planning
BPJS
Human Resource
records
HIV/
AIDS
LMIS
Integration
- District system
DHIS2
AID
TB
Vaccin S
e MC
IDS
R
H
Malari
a
Other
s
DHIS2
AID
MC
TB
S
H
Vaccin
Other
e
s
PROVINCE/NATIONAL:
Integrated data warehouse
& dashboard used by all
DISTRICT:
Integrated data
warehouse &
dashboard
IDS
R
Malari
a
Puskesmas – Health facility
PUSKESMAS:
Programs use DHIS2,
both data use and
reporting
Integration
- District system
AID
TB
Vaccin S
e MC
IDS
R
H
Malari
a
Other
s
DHIS2
Data access
& use
DHIS2
AID
MC
TB
S
H
Vaccin
Other
e
s
PROVINCE/NATIONAL:
Integrated data warehouse
& dashboard used by all
DISTRICT:
Integrated data
warehouse &
dashboard
IDS
R
Malari
a
Puskesmas – Health facility
PUSKESMAS:
Programs use DHIS2,
both data use and
reporting
OpenHIE Architecture Design
OpenHIE / DHIS Architecture
- Evolving through use
Facility Registry
Data Dictionary
DHIS
2
HMIS
Commun
ity
Dashboard projects in Indonesia
Pusdatin – University of Oslo – UGM
•National data warehouse & dashboard project
• Integration national programs: data by Puskesmas
• Creation of health program-based dashboards (TB,
HIV/AIDS, Malaria, ..)
• Creation of integrated dashboards: indicators
across programs TB-HIV/AIDS, ..
•Yogyakarta province data warehouse
• Province & district based dashboards
• Applying & aligning national data warehouse with
province data warehouse
Initial plans: HSS – Pusdatin – Oslo –UGM
Selection on 5 provinces for DHIS2 implementation
•Provinces where HSS district located
•Identification of data sources and reporting flows in
districts and province
•Applying & aligning national data warehouse with
province and district data
• Including selected district & province specific data
• Electronic data: (semi) automate data transfer
• Manual data capture
•Design and develop of district and province dashboards
Initial plans (2) : HSS – Pusdatin – Oslo –UGM
Capacity building
•Train & develop national expert DHIS2 team –Pusdatin
&UGM
•Train all HSS staff
•Training of Trainers (TOT): Key people from provinces
& districts
•Training & data review and data use in districts
•Continuous hands-on training and support
Challenge:
Capture data from Puskesmas in Districts
Data only by districts at national leve –need to be
captured in the dstricts
•Malaria: Only Excel
•Morbidity data; districts and Puskesmas have different
systems – sending to districts
• Different methods and systems between districts
•MCH data: e.g. excel sent to district
•Vaccination: Jogja has system, different in other
provinces
E-SISMAL to Komdat 2 –
Integrated Data Warehouse
(dhis2 at Pusdatin)
Komdat 2
Approved data by
E-SISMAL Malaria
2
department
DHIS2
E-SISMAL Excel
file at District
Level by
Puskesmas
Data check and
Approval at National /
Province Level
Malaria based
dashboard
DHIS2 : Data
warehouse
Statistical
data
BACK TO THE GLOBAL: Way Forward
Challenge:
•‘Success’ = large number of countries,
organisations, systems & use cases
•Disease surveillance, malaria, TB,
HIV/AIDS, registers, tracker, etc.
•Large number of new requirements
•Central development team becoming
bottleneck !
‘Technical Solution’: DHIS2 - app platform
• How to respond to large amounts of new
requirements?
Enable users & local groups to make
their own apps!
• Web api
• SDK for Android (Software Development
Kit)
• App store for distribution of apps
‘Organisational solution’:
Build strong HISP – DHIS2 community!!
Build network of DHIS2 projects,
countries &universities
• Organise country HISP nodes (Sri Lanka!)
&
• Regional hubs – centres of excellence
• Focus on research and education
•Masters & PhD program critical
From vertical reporting systems
… towards a common data
platformProgress:
More and more
programmes & countries
moving towards single
country platform (e.g. DHIS
2)
Partners working on joint
investment & core functional
requirements
But .. much more
required:
−to establish sound
governance at country level
−To integrate public health
surveillance into routine
systems
−To build adequate capacity
W H O / I n t e r n a t io n a l s t a n d a r d s fo r D H I S 2
Clickheret o g o t o t h e W H O st a n d a r d s w e b p o r t a l, w it h d e t a ile d
in f o r m a t io n a n d in st a lla t io n in st r u c t io n s f o r u sin g t h e se t e m p la t e s a n d t o o ls.
S t a n d a r d t o o ls a n d t e m p la t e s
I n d ic a to rs
R e f e re n c e f a c ility
in d ic a to rs
Learn m o re…
Im p o rt
A p p fo r b r o w s i n g o f D H IS 2 a g g r e g a t e m e t a d a t a , a s w e l l a s to a l i s t o f W H O r e fe r e n ce
i n d i ca t o r s .
Learn m o re…
I n st a l l
H o s p it a l m o rta lity
m o d u le
M o d u l e fo r co l l e ct i o n o f h o s p i t a l m o r t a l i t y d a t a u s i n g t h e IC D -1 0 s t a r t-u p m o r t a l i t y l i s t.
I n cl u d e s d a t a e n t r y t e m p l a t e a n d b a s i c o u t p u t s .
Learn m o re…
Im p o rt
H I V d a ta c o lle c tio n
f o rm s
T h e d a t a co l l e ct i o n fo r m fo r H IV , i n cl u d i n g d a t a e l e m e n t s (w i t h d i s a g g r e g a t i o n s ) a n d
d a t a v a l i d a t i o n r u l e s..
Learn m o re…
Im p o rt
M a la ria d a ta c o lle c tio n
f o rm s
T h e d a t a co l l e ct i o n fo r m fo r M a l a r i a , i n cl u d i n g d a t a e l e m e n t s (w i t h d i s a g g r e g a t io n s ) a nd
d a t a v a l i d a t i o n r u l e s.
Learn m o re…
Im p o rt
O t h e r d a t a c o lle c tio n
f o rm s
T h e d a t a co l l e ct i o n fo r m fo r o t h e r p r o g r a m m e s / a r e a s , i n cl u d i n g d a t a e l e m e n t s (w i t h
d i s a g g r e g a t i o n s) a n d d a t a v a l i d a t i o n r u l e s , e .g . T B , E P I, M C H e tc.
Learn m o re…
Im p o rt
W H O d a ta q u a lity to o l
A p p fo r p e r fo r m i n g r o u t i n e a n d a n n u a l d a t a q u a l i t y ch e ck s o n a g g r e g a t e h e a l t h fa ci l i t y
d a t a , a cco r d i n g t o t h e W H O D a t a q u a l i t y r e v ie w t o o l k i t.
Learn m o re…
I n st a l l
H I V d a s h b o a rd s
D a s h b o a r d s fo r u se o f r o u t i n e fa ci l i t y -b a s e d H IV d a t a . In cl u d e s d a s h b o a r d s , a n a l y t i ca l
o u t p u t s a n d i n d i ca t o r s .
Learn m o re…
Im p o rt
M a la ria d a s h b o a rd s
D a s h b o a r d s fo r u se o f r o u t i n e fa ci l i t y -b a s e d m a la r i a d a t a . In cl u d e s d a s h b o a r d s ,
a n a l y t i ca l o u t p u t s a n d i n d i ca t o r s .
Learn m o re…
Im p o rt
O t h e r d a s h b o a rd s
D a s h b o a r d s a n d d a t a co l l e ct i o n t e m p l a t e s fo r a d d i t i o n a l p r o g r a m m e s / a r e a s , e .g . T B ,
E P I, M C H e t c
Learn m o re…
Im p o rt
Learn m o re…
Im p o rt
D a t a d ic tio n a ry a p p
D a ta c o lle c tio n
D a ta q u a lity
D a s h b o a rd s
S y ste m
W H O r e co m m e n d e d i n d i ca t o r s fo r r o u t i n e fa ci l i t y d a t a .
M a s t e r F a c ilit y L is t
G u i d a n ce o n e st a b l i sh i n g a n a t i o n a l m a s t e r fa ci l i t y l i s t .
2016Q1
Status WHO DHIS 2
standards/tools
2016Q2
2016Q3
2016Q4
Data Quality Tool
Data Dictionary
Standards Repository
HIV module
EPI module
RMNCAH
module
TB module
NTD module(s)
Malaria module
Cause of death (ICD-SMoL)
TB patient tracker
TB-MDR patient tracker
Not started/early
In progress
Done/nearly done