October 2–5, 2007  Lusaka, Zambia

1. STRATEGIES FOR BUILDING NATIONAL-SCALE LONGITUDINAL ELECTRONIC PATIENT MONITORING SYSTEMS FOR HIV TREATMENT AND CARE IN PEPFAR COUNTRIES October 2–5, 2007 Lusaka, Zambia

2. Botswana – Integration at the Top Suzanne Cloutier, MSPH Informatics Consultant – BOTUSA 2

3. Overview • Current HMIS Environment • IT Infrastructure • GoB Organizational Structure • HIV Data Warehouse • Challenges and Opportunities • Next Steps

4. Current HMIS Environment • Botswana has several information systems for capturing data on health services provided to HIV+ patients • EMR – Integrated Patient Management System (IPMS) • ART – Patient Information Management System (PIMS) • TB – Electronic TB Register (ETR), Isoniazid Preventative Therapy (IPT) System • VCT – VCT Management Information System • General – District Health Information System (DHIS)

5. Current HMIS Environment • Integrated Patient Management System (IPMS) • Proprietary, centralized, client/server application implemented by Meditech in 2003 • Focused on overall patient care and treatment in community, clinic, and hospital settings • Provide user-friendly, modular, scalable application • Focus on core functions • Phase 1: 4 hospitals + 16 satellite clinics • Accounts for 48% of ARV patients 5

6. IPMS - continued • Still in phase 1 pending evaluation • Preliminary results from evaluation • Inadequate user training • Inadequate user support • Inadequate bandwidth on the network • No interfaces to other GoB systems • Very expensive • More functionality  Higher cost 6

7. Current HMIS Environment • Patient Information Management System (PIMS) • Decentralized facility-based application • MS Access backend supported by VB and SQL code • Clinic data are entered by data entry clerks • Standardized reports available for local and national use • Installed at 28 ART sites not connected to IPMS • Accounts for 52% of ART patients • Upgrade necessary to support future needs 7

8. Current HMIS Environment • TB treatment and prophylaxis • Electronic TB Register (ETR) and Isoniazid Preventative Therapy (IPT) System • Both developed on VB.Net platform with a MS Access backend • Distributed systems with health facility data entered at district level and dispatched to a central database at the national program • The TB systems are not integrated • Ideally they would share district, facility, and patient tables

9. Current HMIS Environment • Tebelopele – VCT Management Information System (MIS) • Decentralized application • Developed in MS Access • Installed at 16 sites across Botswana • Counselors use handheld PCs to capture confidential client data • Data collected at the VCT centers are converted to an Epi6 dataset, then merged into 1 dataset at the national level

10. Current HMIS Environment • District Health Information System (DHIS) • Developed in MS Access • Uses Excel for analysis – pivot tables, graphs • Supports XML • Installed as a stand-alone system in the districts • Aggregated health facility data are entered at district level by Community Health Nurses • Data entered support minimal indicator set defined by stakeholders • Piloted in 4 districts – roll-out to all districts will start before end of year 10

11. IT Infrastructure • Government Data Network (GDN) • TCP/IP connectivity via LANs • Email • Internet • Web hosting • Applications 11

12. IT Infrastructure • Health Districts • Comprehensive IT assessment of all health districts last year • Conducted site visits to 24 districts and 3 sub-districts • Assessed the ICT infrastructure, as well as the capacity of key district personnel to use IT resources effectively and efficiently for managing strategic information • Assessment teams consisted of 1 IT specialist and 1 Informatics specialist 12

13. Health District Informatics Assessment • ICT Infrastructure • 135 computers were assessed • Operating system • Processor speed • Hard disk size • RAM • Network connectivity • Software • Other ICT equipment 13

14. Health District Informatics Assessment • Use of ICT Resources • 122 district health officers were interviewed • Date management activities • File management skills • Software use and skill level 14

15. GoB Organizational Structure 15

16. GoB Organizational Structure 16

17. GoB Organizational Structure 17

18. GoB Organizational Structure 18

19. HIV Data Warehouse • Rationale for this Solution • Masa ARV program decided to develop a data warehouse to integrate ARV data from IPMS and PIMS • Agreed later to expand the scope to include all patient level data from the various health programs

20. HIV Data Warehouse • Rationale for this Solution • Fragmented approach to patient management and outcome monitoring • Each program captures data independently and is unable to share data with other programs • Level of detail for data varies across programs • ARV, TB, and VCT programs capture patient level data • Other health data are aggregated by facility • Applications are built on different platforms • No standard way to exchange data • Not easy to link patient records within programs, let alone across programs

21. HIV Data Warehouse • Rationale for this Solution • Not possible to get a comprehensive picture of the services PLWHA access, nor the overall effectiveness of the healthcare provided to them • Goal of the HIV Data Warehouse • Integrate all electronic health data on services provided to PLWHA so that analysis and reporting may be done to improve patient care and outcomes

22. HIV Data Warehouse • Objectives • Integrate ARV data into a national data repository • Integrate other health services data for HIV+ patients • Allow access to anonymous, linked health data • Ensure appropriate privacy/confidentiality and security measures are implemented

23. Phase 1 – Integrate ARV Data HIV Data Warehouse

24. Phase 2 – Integrate TB Data HIV Data Warehouse

25. Phase 3 – Integrate Other Data

26. HIV Data Warehouse • Progress to date • Purchased server hardware and software • Quad dual-core processors • MS SQL Server 2005 • Defined the scope • Data extraction, cleaning, integration, transformation, loading, reporting, business intelligence component • Defined the development methodology • Kimball methodology for MS SQL Server 2005 - “The Microsoft Data Warehouse Toolkit” by Mundy et al.

27. HIV Data Warehouse • Progress to date • Gathered user requirements from ARV program • Developed the initial data model • Received TA from WHO data warehouse expert • Extracted and loaded IPMS data onto the server • Able to produce monthly M&E reports • Provide limited research support • Started development of prototype based on pharmacy module as proof of concept

28. Preliminary Data Model Fact Tables Care Summary Conformed Dimensions Dimensions Person Observations Observation Facility Lab Results Lab Test Encounter Drug Orders Drug Drug Stops Transfers

29. Privacy Protection Principles Collection Limitation Data Quality Purpose Specification Use Limitation Security Safeguards Openness Individual Participation Accountability Protection of Patient Information Ownership of Data Informed Consent Data Retention Privacy Protection • Support for privacy and confidentiality is built into the data model • Demographic data will be stored separately from the data warehouse • Pseudonymous patient identifiers will be used within the data warehouse • Overall design allows for the implementation of basic privacy principles through engineering and policy

30. Security • Foundation for privacy protection • Security will be layered into the data warehouse system using industry standard approaches • Data model includes components to ensure logging and auditing capabilities

31. Preliminary Data Structure Fact Tables Personal Data Care Summary Identifiers Conformed Dimensions Dimensions Private Details Person Observations Observation Facility Lab Results Lab Test Private Contacts Encounter Drug Orders Drug Drug Stops Audit and Tracking HIV Data Warehouse Transfers

32. ARV Enrollment Projections 125,000 110,000 95,000 75,000

33. Estimated Volume of ARV Data 33

34. Challenges • Non-technical • Low level of communication and collaboration across government organizations • The GoB makes all decisions • Nothing is implemented without their approval • They operate on their own timetable with their own protocol • No CIO to provide strategic vision, sponsorship, or guidance to the project team • No national health informatics strategy 34

35. Challenges • Technical • Shortage of skilled IT resources • Much of the patient data are in paper-based systems • Modeling atomic drugs vs. combination drugs vs. drug regimens • Network Infrastructure • Very few healthcare facilities are connected to LANs • GDN is not robust or stable enough to support centralized systems 35

36. Challenges • Technical • Remote sites • Minimal connectivity via internet or cellular network • Synchronization issues • Data transfer challenges • Linking patient records from disparate systems • Patients’ records are fragmented • Data integrity problems • Misuse of national ID (Omang #) • Patient names 36

37. Opportunities • National HMIS Strategic Plan Development • Funds requested in COP 08 • Provide guidance for IS development • Include international ICT standards and guidelines • Active participation by 5 key GoB stakeholders • Revitalization of a System Integration Working Group in DHAPC 37

38. Opportunities • DIT E-Governance Initiative • by December 2010 • All healthcare facilities in the country will be networked • Healthcare information and applications will be made available online • Pilot Implementation of Security Guidelines • MS SQL Server Security Consultant • Set up security measures per international guidelines 38

39. Next Steps • Complete Prototype of Pharmacy Module • Evaluate modeling of • Combination drugs (e.g. Combivir) vs.atomic drugs (e.g. AZT, 3TC) • Drugs vs.drug regimens (e.g. DDI+D4T+EFV) • Evaluate MS SQL Server analysis tools • Acquire and install business intelligence (BI) tools 39

40. Next Steps • Set up security for MS SQL Server 2005 • Provide on-the-job training to local IT staff • Use probabilistic matching software to link patient records • Evaluate COTS product • Further refine data extracts from IPMS to include hospitalizations • Extract and load PIMS data 40

41. Thank You! Thank You! Thank You! Thank You! Thank You! 41

42. Background • HIV/AIDS • Prevalence is declining, but still high • 17% in general population (2004) • 25% in adults 15-49 years • 32% in pregnant women 15-49 years (2006) • PMTCT program began in 1999 • Full coverage since 2003 with uptake of about 96% • 96% of babies born to mothers in PMTCT are HIV- • ARV program began in 2002 • Out of 1.7 million population, approx 270,000 are PLWHA • >82,000 of the eligible 91,000 PLWHA are on ART 42

43. Background • TB • Case Reporting • 10,000-12,000 /year • 60-86% of TB patients are HIV+ • Isoniazid Prevention Therapy (IPT) program began in 2002 • 56,000 PLWHA screened and >42,000 enrolled as of 2006 43

44. Progress with ARV Data • Extract monthly IPMS data to produce tables 2–7 of the Site Manager’s Report • Extract 1.5 million pharmacy records of ARV drugs dispensed • Extract 8 million lab records of lab tests done for patients on ARV • Currently integrating “MASA” data from the main hospital sites

45. BRHIMS OVERVIEW Data aggregated by DAC sent to MOH / MLG MLG MOH NATIONAL LEVEL 24 health districts with DHIS(2 yrs operational) DAC DHT 27 LG districts DISTRICT LEVEL Forms-based data collection OVC, District admin Clinics LEGEND:Data flow MLG Ministry of Local GovtMOH Ministry of HealthDHT District Health TeamDHIS District Health ISDAC District AIDS Coordinator