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
DHIS2 country systems & PEPFAR
Early phase / pilots
Early implementation / many states in
India
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
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
• 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 / DHIS timeline (2):
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:
•
Where?
•
What?
•
When?
Analysis
& decisions:
•
Why?
•
How to?
Data Element
Period
Location (Organisation Unit)
Data Value
1
1
1
N
N
N
When
Where
What
National
State /
Province
District
Sub-District
Health
facility
Organised in an
Organisational hierarchy
Disaggregated by
Dimensions, e.g. sex, age
Organised in
Data sets
Dates, time period,
e.g. August 2011,
Quarter 3 2011
‘When, What, Where’:
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:
•
Inequity
between blacks & whites, rural & urban, urban &
“peri-urban”, 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
– ‘
Motivation for ‘Standardisation’:
Hospital
PAWC
Clinic
RSC
Clinic
RSC
Clinic
PAWC
Private
Private
NGO
Cape Town
RSC
Cape Town
PAWC
Malmesbury
PAWC
DNHPD
Western Cape
Family PlanningMOU
PAWC
School
Health
Hospital
Clinic
Private
NGO
A) Post-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
Example South Africa, Atlantis District 1994:
First Architecture approach: From fragmentation to integration;
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
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
Patient – individual client Level
Health Facility Level
Sub-National Level
National Level
Regional Level
Standard
Indicators,
& datasets:
Patient
Facility
Sub National
National
Regional
-ECOWAS
South Africa
Nigeria
Vietnam
Sri Lanka
Uganda
India
Norway
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
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 India & Vietnam
& HISP Sri Lanka
!
HISP
Kenya
Tanzania
Uganda
Rwanda
HISP South Africa
HISP
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
WHY SUCH EXPANSION ?
And how to continue to
Mobile subscribers per 100 persons, Africa
Internet: Total bandwidth of communication
cables to Africa South of Sahara
DHIS2 implementations /initial projects
correlated with increase in bandwidth
Source: AFRINIC
DHIS 2
implementations
2014
2015
D
H
IS
=
1
/1
0
0
Online system – one server
Easier to integrate / interoperability with other systems
which are also online: web API
& central server
DHIS2
Online
Data capture
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
Improved Internet and mobile network: Rapid scaling
Data
warehouse
DHIS 2
LMIS
HR
EMR
Ext
rac
t
Tra
nsf
orm
Loa
d
Data from
Mobile devises
Data cap
ture
from pap
er
forms
-Data mart
-Meta data
-Visualising
tools
Dashboard
Graphs
Maps
Getting data in - Data warehousing
Getting data out - Decision support
systems – ‘Business intelligence (BI)
Web Portal
Mobile
Data
Warehouse
Paper based systems:
OPD, EPI, RCH,
other programs
Users of primary data
& data providers
Electronic
Medical
Records
HR
Management
Logistics
& drugs
Mobile
reporting
Finance
Users of
primary data
& data providers
Users of processed & integrated data
Int
ero
pe
rab
ilit
y
Inter
oper
abilit
y
Integration of
technologies, systems,
data & health programs
Integrated Health Information Architecture (“Horizontal integration”)
- integrating sub-systems, technologies, health services & programs
Performance
Based financing
reporting
SDMX -HD
Paper
reports
Integration and interoperability
DHIS
: Data
warehouse
Statistical
data
OpenMRS :
Medical records
iHRIS: Human
Resource records
Data transfer
from OpenMRS
To DHIS, e.g.:
#deliveries
@health centre X
for month of May
Data transfer
from iHRIS to
DHIS, e.g.:
#midwifes
@health centre X
for month of May
DHIS is calculating
the indicator:
Deliveries per midwife
Per facility per month
Integration
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
Java
All devises integrated in
Lightweight
Browser
SMS
Android
app or
browser
Tablet
PC/laptop
Mo
re
f
ex
Level 1:
Information
Needs, Users, Usage
Across Organisations
“Business level”
Level 2:
Software applications
& Information
Systems
“Application level”
Level 3:
“Data
exchange level”
“Technical level”
Interoperability &
standards, technical
infrastructure
Open
MRS
DHIS
Patient
records
iHRIS
Data warehouse
Aggregate data
Institutional use of information
Applications supporting use
of information
Data Standards and infrastructure supporting the applications
Enterprise architecture: 3 Levels
(each serving the level above)
Data & indicator dictionary /standards
Facility register
Provider register
ADX
OpenHIE
Indonesia Data Warehouse &
Dashboard
DHIS2
Data warehouse
DHIS2
Data warehouse
SITT (TB)
SITT (TB)
SIHA
(HIV)
SIHA
(HIV)
(Malaria)
E-Sismal
E-Sismal
(Malaria)
NCD
NCD
Logistics
Logistics
TB + rate 2014
By Province
By Province
By District
By District
TB +Ve cases by
facilities
TB
MC
H
Vaccin
e
IDS
R
Malari
a
AID
S
Other
s
TB
Vaccin
e
AID
S
Other
s
MC
H
Malari
a
IDS
R
PUSKESMAS:
Each Program
Reports to Program in
District
DISTRICT:
Each program
manage own data
-Limited
coordination
across programs
Puskesmas – Health facility
District
Data flow
NATIONAL
PROVINCE: All programs
receive reports aggregated by
district –from district programs
KOMDATA
Pilotitis in Uganda: mHealth mapping
DHIS
: Data
warehouse
Statistical
data
Human Resource
records
Dashboard
Diffe
rent
code
s
TB
Malaria
HIV/
AIDS
Komdat
/HMIS
Facility
Codes
Register
M
A
P
P
IN
G
Mapping
Facility codes
MCH
Same
code
Shared Facility
codes
Integrating data
sources
TB
MC
H
Vaccin
e
IDS
R
Malari
a
AID
S
Other
s
TB
Vaccin
e
AID
S
Other
s
MC
H
Malari
a
IDS
R
PUSKESMAS:
Programs use DHIS2,
both data use and
reporting
DISTRICT:
Integrated data
warehouse &
dashboard
Puskesmas – Health facility
PROVINCE/NATIONAL:
Integrated data warehouse
& dashboard used by all
DHIS2
DHIS2
Integration
TB
MC
H
Vaccin
e
IDS
R
Malari
a
AID
S
Other
s
TB
Vaccin
e
AID
S
Other
s
MC
H
Malari
a
IDS
R
PUSKESMAS:
Programs use DHIS2,
both data use and
reporting
DISTRICT:
Integrated data
warehouse &
dashboard
Puskesmas – Health facility
PROVINCE/NATIONAL:
Integrated data warehouse
& dashboard used by all
DHIS2
Data access
& use
DHIS2
Integration
OpenHIE / DHIS Architecture
- Evolving through use
DHIS
2
Facility Registry
Data Dictionary
HMIS
Commun
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
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
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
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
Challenge:
E-SISMAL to Komdat 2 –
Integrated Data Warehouse
(dhis2 at Pusdatin)
DHIS2
: Data
warehouse
Statistical
data
Komdat 2
DHIS2
E-SISMAL 2
E-SISMAL Excel
file at District
Level by
Puskesmas
Data check and
Approval at National /
Province Level
Malaria based
dashboard
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 !
– ‘
•
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
– ‘
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
– ‘
‘Organisational solution’:
Progress:
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
in analysis and use
From vertical reporting systems
… towards a common data
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
Click here
t 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 fo 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 fo r u sin g t h e se t e m p la t e s a n d t o o ls.
St a n d a r d t o o ls a n d t e m p la t e s
I n d ica to rs
R e fe re n c e fa cility
in d ica to rs
W H O r e co m m e n d e d in d i ca t o r s fo r r o u t in e fa cili t y d a t a .
L e a r n m o r e …
I m p o r t
D a ta d ictio n a ry a p p
A p p fo r b r o w sin 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 ll a s to a list o f W H O r e fe r e n cei n d ica t o r s.L e a r n m o r e …
I n st a l l
D a ta co lle ctio n
H o s p ita l m o rta lity
m o d u le
M o d u le fo r co lle ct io n o f h o sp it a l m o r t a lit y d a t a u sin g t h e IC D -1 0 st a r t-u p m o r t a lit y list.
In clu d e s d a t a e n t r y t e m p la t e a n d b a sic o u t p u t s.
L e a r n m o r e …
I m p o r t
H I V d a ta co lle ctio n
f o rm s
T h e d a t a co lle ct io n fo r m fo r H IV , in clu d in g d a t a e le m e n t s (w it h d isa g g r e g a t io n s) a n d
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L e a r n m o r e …
I m p o r t
M a la ria d a ta co lle ctio n
f o rm s
T h e d a t a co lle ct io n fo r m fo r M a la r ia , in cl u d in g d a t a e le m e n t s (w it h d isa g g r e g a t io n s) a nd
d a t a v a lid a t io n r u le s.
L e a r n m o r e …
I m p o r t
O th e r d a ta co lle ctio n
f o rm s
T h e d a t a co lle ct io 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, in clu d i n g d a t a e le m e n t s (w it h
d isa g g r e g a t io n s) a n d d a t a v a lid a t io n r u le s, e .g . T B , E P I, M C H e tc.
L e a r n m o r e …
I m p o r t
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W H O d a ta q u a lity to o l
A p p fo r p e r fo r m in g r o u t i n e a n d a n n u a l d a t a q u a li t y ch e ck s o n a g g r e g a t e h e a l t h fa cilit yd a t a , a cco r d in g t o t h e W H O D a t a q u a lit y r e v ie w t o o l k it.L e a r n m o r e …
I n st a l l
D a s h b o a rd s
Status WHO DHIS 2
standards/tools
2016Q1
2016Q2
2016Q3
2016Q4
Data Quality Tool
Data Dictionary
Standards Repository
Done/nearly done
In progress
Not started/early
phase
HIV module
TB module
EPI module
Malaria module
Cause of death (ICD-SMoL)
TB patient tracker
TB-MDR patient tracker
RMNCAH
module