Health Information System: Interoperability and Integration to Maximize Effective Decision Making
- 1. Health Information System Interoperability and Integration to Maximize Effective Decision Making Manish Kumar, MPH, MS Sam Wambugu, MPH, PMP MEASURE Evaluation October 6, 2015 Brown Bag Presentation USAID
- 2. Outline • Describe ecology of HIS • Discuss issues around interoperability and integration • Present country and global experiences • Key messages • Tools and resources
- 3. Adapted by MEASURE Evaluation from Common Road Map Steering Committee. Roadmap for Health Measurement and Accountability. June 2015. Washington, DC: World Bank Group, USAID, and the World Health Organization. Available from http://ma4health.org.
- 4. HIS situation in LMICs • Weak health systems, leadership, and governance • Inadequate capacity • Limited user engagement • Lack of standards • Redundant data • Data quality issues • Fragmented HIS
- 6. What can we do? • Collaborate and conduct HIS landscape assessment • Agree on health information needs • Develop standard measurement indicators • Develop data and interoperability standards • Build technical, institutional, and organizational capacity Develop country HIS architecture.
- 7. What is interoperability? Ability of health information systems to work together within and across organizational boundaries in order to advance the effective delivery of healthcare for individuals and communities. Ability of different information technology systems and software applications to communicate, exchange data, and use the information that has been exchanged. Source: HMISS Interoperability and Standards Toolkit
- 8. What are data standards? Broadly grouped under two categories: • Data representation standards Data structure-XML Data semantics-ICD10, SNOWMED, LOINC • Data interchange standards HL7 Context of standards is the information architecture
- 10. Country and global experiences • Liberia • Swaziland • DATIM
- 11. HIS situation in Liberia • Progress in generating service delivery data through the HMIS and using them for decision making • Limited development of resource information systems • Fragmented HIS components and data sources Example: weak link between HMIS and DHIS 2 • Lack of ‘co-operability’ among multiple partners • Outdated HIS strategic plan (2009) • Lack of adequate ICT infrastructure and capacity
- 12. HIS strengthening in Liberia • Conducted overall HMIS and ICT infrastructure assessment • Facilitated development of HIS Strategy 2015−2021 Supported MOH to create a stakeholder coordination mechanism Facilitated stakeholder consultation to achieve consensus on the strategy and operational plan • Supporting development of HIS data architecture • Provide technical assistance to accelerate the process of integrating HIS systems and their sub-systems • Facilitating collaboration between MOH and OpenHIE community • Enhance MOH capacity to use data for decision making
- 13. HIS situation in Swaziland Results of HIMS assessments in Swaziland: • Parallel/ disease specific systems • Too many data collection tools • Lack of procedures for data collection • Lack of a modern, patient-based information system to capture, store, and retrieve a clean dataset
- 14. 1. Developed an enterprise architecture plan 2. Established a Strategic Information Department for MOH 3. Developed a consolidated patient file and a Unique Patient Identifier 4. Developed a modular client management information system (CMIS) / EMR 5. Developed clinical data servers (distributed data servers) 6. Ongoing development of clinical data warehouse Swaziland HMIS strengthening steps
- 17. Key messages • Promote country ownership and build local capacity • Establish stakeholder collaboration and coordination • Agree on information needs and architecture for health systems • Develop/adapt standards-based health information architecture • Promote institutional mechanism for data use
- 18. Tools and resources Common Road Map Steering Committee. Roadmap for Health Measurement and Accountability. June 2015. Washington, DC: World Bank Group, USAID, and the World Health Organization. Available from http://ma4health.org. Gobee Group. Regional, Real-Time Data Infrastructure for Ebola Response: An Assessment of On-The-Ground Data Systems and Realistic Opportunities for Transformation in Guinea, Liberia & Sierra Leone. Gobeegroup.com. July 2015. HIMSS. HIMSS Interoperability and Standards Toolkit. Available from http://www.himss.org/library/interoperability-standards/toolkit HMN WHO. Framework and Standards for Country Health Information Systems. Second Edition ed. Geneva: World Health Organization: Geneva, 2008 Principles for Digital Development. Available from http://digitalprinciples.org/wp- content/uploads/2015/05/Principles-Overview.pdf Ritz D, Althauser C, Wilson K. Connecting Health Information Systems for Better Health: Leveraging interoperability standards to link patient, provider, payor, and policymaker data. Seattle, WA: PATH and Joint Learning Network for Universal Health Coverage, 2014
- 19. MEASURE Evaluation is funded by the U.S. Agency for International Development (USAID) under terms of Cooperative Agreement AID-OAA-L-14-00004 and implemented by the Carolina Population Center, University of North Carolina at Chapel Hill in partnership with ICF International, John Snow, Inc., Management Sciences for Health, Palladium Group, and Tulane University. The views expressed in this presentation do not necessarily reflect the views of USAID or the United States government. www.measureevaluation.org