HIS implementation in Ethiopia: case studies from AAHB Woinshet Abdella PhD Student Department of Informatcs University of Oslo
CONTENTS • Background • Ethiopia / Health Care System • HISP Ethiopia • DHIS Implementation in Addis & Oromia • Challenges
Ethiopia • Population - 72+ million • Area – 1.1 million km2 • Decentralized administrative structure • 9 regional states & two city administrations • 580 weredas (districts) • Regional sates are autonomous • Poor literacy, education, health status
Health Care System • MOH, Regional health bureaus, Zonal health departments, Wereda/Sub-city health offices, Health Facilities • Under developed • Health service coverage – 61% • MMR – 871/100,000, U5MR – 140/1000 • High Infectious & communicable diseases • HIS is primarily manual & under developed
HISP-Ethiopia • Project Initiation • Through a collaboration of the Department of Information Science, Addis Ababa University (AAU) and the University of Oslo in February 2003. • Partners • AAU; regional health bureaus of Ethiopia; global HISP
HISP-Ethiopia • Objective • Introducing computer based HMIS in Ethiopia in view of supportinglocal analysis and use of data
HISP-Ethiopia • HISP Members • 4 PhD students / 7 Masters students (one Norwegian) • 5 DHIS facilitators hired by HISP • Research Sites for HISP Ethiopia • Addis Ababa, Oromia, Tigray, Amhara, Benishangul-Gumuz • DHIS implementation is being carried out • Addis & Oromia – since Jan 04 • Others – since June 04 • Different stages of implementation
Case Studies from Addis • Research Objective • key research objective is to broadly understand the challenges and opportunities with respect to the integration of existing paper-based HIS with computer-based systems in Ethiopia. • Theoretical Perspective • ANT • Research Approach & context • PAR • AR intervention: • HIS implementation Intervention into health organizations (AAHB & OHB) • One DHIS facilitator for each region
Research Approach & context • Research Site • Addis Ababa health bureau (AAHB) , • 10 sub-cities (districts) • 500 public & private health facilities, • located in Addis Ababa city Administration (Province). • Addis Ababa is the capital city of Ethiopia (540 km2 ) • Population is 3 millions.
Research Approach & context • Researcher Role. • The role assumed was an involved researcher through action research. • Qualitative data collection method was employed including • photography, observations, interviews, discussions, meetings, workshops, training, action experiments, document analysis, telephone calls, visit related institutions, informal lunch/tea meetings.
Research Approach & context • Research subjects • managers and planners at different levels of the health structure, the health workers responsible in data collections and analysis.
DHIS Implementation in Addis • Negotiate research access (KK) • Situation analysis (Mar 03 – Aug 03) • Visits to Health bureaus & HFs • Initiating the Design / implementation process with AAHB/OHB (Dec 03) (Bureau) • EPR was just introduced then • Prototype system was developed and populated with 9 months own data
DHIS Implementation in Addis Ababa • Demonstration of the prototype DHIS Addis (Jan 04) • The experiences gained revealed the problems with the existing HMIS • Data duplication, fragmentation, … • Local requirement (Morbidity/Mortality data handling) identified that DHIS does not support efficiently • Developing minimum health data set & health indicators was proposed
DHIS Implementation in Addis Ababa • Major decisions • The proposal for standardizing data set/health indicators accepted • Adapting DHIS based on new dataset and reporting requirement • Adding module to accommodate M/M data handling • Implementing DHIS to ALL Sub-cities. • Team formed
The research team was composed of • Bureau level, • Bureau head; • health service head (leader of the project on the part of the bureau), team leader, and senior expert; • family health head, team leader and expert; • Disease Prevention and Control head; IDSR team leader, TB / Leprosy and HIV/Aids program team leader and senior expert; • IEC expert; • Network administrator; • Sub-city Level • two family health experts • Facility Level • two health facility managers; • And the researcher.
DHIS Implementation in Addis Ababa • Two Parallel activities performed • Standardized data set, health indicators, data collection & reporting instruments & procedures (data flow, …) development • Draft prepared by the group presented for workshops, comments incorporated, the draft was further developed in a series of long meetings, • Development of Morbidity & Mortality module • Iterative / incremental (involved one major revision)
DHIS Implementation in Addis Ababa • Use of DHIS as a prototyping tool • to better understand user requirements for producing an improved & useful system – which potentially increases data use • The standardized data set is implemented in all facilities • DHIS adapted, the new module incorporated • (Input Form, DHIS Data Flow, Data Entry (next slide), Pivot Table Report, Standard Report )
Monthly Routine Data Entry/Edit Form Monthly Morbidity and Mortality Data Entry/Edit Form
DHIS Implementation in Addis • DHIS is implemented • All districts (10 sub-cities) and AAHB initially • Scaled to health facility levels • 18/23-Health centers & 5/5-Hospitals (when resource / situation allowed) • Training (DHIS/computer basics) was given to sub-city/bureau/HF health staff / managers / data clerk / DHIS facilitators (with own data) • Technical support is being provided by the facilitator • Participatory design • July 2005, Workshop for evaluating one year experience of the use DHIS
Observations … • DHIS Software is well-tested & supports • Data aggregation; data sharing; health structure implementation; easily adaptable for new needs, which is inevitable; rapid set-up of DHIS application for a new setting • Complaints from different actors (use of MS Access in DHIS – DHIS 2 is a response)
DHIS Implementation in Oromia • Collection/reporting instruments and software prepared for Addis is shared by Oromia & other regions • Followed similar approach • Some of the differences • The process was slower when compared to Addis • The minimum data set prepared for Oromia not yet adopted by the region • DHIS implementation status • Some Weredas of East Shewa zone (based on computer availability) • Is being rolled out to the remaining zones (at the zone level only)
CHALLENGES • Improving data quality, data analysis and use • Reduce / Improve dataset • Achieving partnership with MOH • Scaling & Sustainability • Over burdened health worker • Limited resource • Negotiating with multiple actors • Parallel systems