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While development partners have played a roll in fragmentation by setting up program or disease specific information systems, there is increasing recognition of the problem internationally, and some notable development partners (e.g. Health Data Collaborative, WHO, the Global Fund, USAID, etc.) are taking pains to align with country systems.
The Health Data Collaborative (HDC) is a joint effort by countries, development
partners, civil society and academia to strengthen national health information
systems, improve the quality of health data and track progress towards the health related
Sustainable Development Goals. Arising from the call to action at the Measurement and Accountability for Health (MA4H) conference (2015), the HDC aims to (among other things),
“strengthen national and subnational systems for integrated monitoring of health programmes and performance. By helping countries collect, analyse and use timely and accurate data, the Health Data Collaborative will contribute to the goal of data-driven performance and accountability.”
(see the HDC factsheet here: https://drive.google.com/open?id=0B0kN6Fs9MipFdjN0OGZFN2Jzdkk)
From the Global Fund’s policy paper “Supporting Countries to Build Resilient and Sustainable
Systems for Health – The Role of the Global Fund” (2015), “Integrating multiple data collection systems into one single national health management information system can improve decision-making and accountability, from individual health care workers in the community to sub-national, national, regional and global policy makers.”
From our work in the USAID MEASURE Evaluation Project we know that USAID is also promoting integrated national RHIS and/or interoperability to achieve de facto integration. In MEASURE Evaluation Phase III – at the request of USAID – we published a white paper on RHIS Data Management Standards which speaks to best practices for RHIS along 4 domains;
1. Users’ Data and Decision Support Needs
2. Data Collection Processing, Analysis and Dissemination of Information
3. Data Integration and Interoperability
4. Governance of RHIS Data Management
Also in MEval Phase III we published a paper on standards and best practices for integration of HIV/AIDS information systems into RHIS (as a follow-up to the chapter on Integration and Interoperability in the RHIS Data Management Standards document).(http://www.cpc.unc.edu/measure/resources/publications/ms-15-103)
So, while international development partners have certainly played a role in the fragmentation of information systems in countries, they seem to have recognized their role and are now taking steps to bring these systems back into the fold.
Enjoying reading the contributions from all participants. Keep them coming!