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Antoine Mafwilla, MD, MPH, Chief of Monitoring and Evaluation, SANRU shares the challenges of performing evidence-based monitoring and evaluation on health programs in SANRU's program in the Democratic Republic of the Congo.

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  1. 1. Antoine L. MAFWILA, MD MPH Chief Monitoring and Evaluation SANRU 1CCIH 31stAnnual Conference, July 15th 2017
  2. 2.  In the context of evidence based management, basic knowledges becomes more important for Managers, mainly on how to measure progress and change after corrective strategies has been implemented.  Evidence based Management and evidence based policy making put policy makers or program managers in a role of evidence users and researcher, monitoring and evaluation people in a role of evidence provider.  Providing evidence becomes the main challenge of Monitoring and evaluation everywhere and particularly in developing countries where limitation of resources is a common characteristic of the global economy including health economy 2
  3. 3.  SANRU asbl, a DR Congo a faith-based and non-governmental organization is working in supporting health sector in DR Congo for more than 30 years and,  particularly now, we are involved in implementing health support in 422 health zones among them 314 for Malaria, 145 for HIV (141 with Global Fund and 4 for PEPFAR), 144 for immunization (With GAVI), 28 for integrated health package, and 20 for family planning (AQUAL,Tulane University project). 3
  4. 4.  In this context a big amount of data is produced and proceeded by the different projects.  For example in 2015 and only for Malaria program, even aggregated, 35 features were informed by 325 records by the sub recipients each month and sent to SANRU team for analysis.  In this presentation, we will see how SANRU is facing this challenging context aiming to provide high quality data for evidence-based management  enhancing a unique national health management information system  dealing with data quality using data comparison or triangulation between different data sources  Using information for improving health program performance considering differently the clusters 4
  5. 5. 5
  6. 6.  Defined as an organized set of structures, institutions, staff, methods, tools and equipment allowing providing necessary information for decision making, for action and for health system management at all levels, the DRC HMIS is the key national element for evidence based health management in the country  The National HMIS exists since colonial period, it evolved as a project in 1990s and gets its first regulation in 18th March 2005 through a ministry order.  The last assessment conducted on the HMIS in 2015 revealed some issues:  The weakness in diffusing high quality information due to the weak accuracy, completeness and timeline of the data 6 Building a unique health Management Information System with the MOH
  7. 7.  This situation does not allow providing quality data in real time and brought MOH specialized program and implementing partners for many funds to implement parallels information systems and electronic platform for satisfying their need of data.  SANRU began in 2015 with MOH a project called “Renforcement du Système National d’information Sanitaire” funded by global funds (~14 M$) and theWord Bank (~2M$) aiming to reinforce the National HMIS and improving the quality of data produced.  A real opportunity for the country to get a strong health information system, its activities cover topics (1) support to the National office of HIS with equipment, training of staff and implementation of electronic DHIS2 (2) support technical assistance of the National office of HIS by consultants (3) Support the National population register on population registration and statistic report production (4) support use of health information and, (5) begin implementation of electronic health record (EHR) in facility level. 7 Building a unique health Management Information System with the MOH
  8. 8.  Today, after a disbursement of 8M $ and 800K $ on the provision respectively from GF andWB, DHIS 2 is fully implemented in the country.  The completeness and the timeline are increasing over time and have reached a mean of 71% for the completeness and 33.5% for timeliness. 8 Building a unique health Management Information System with the MOH
  9. 9. 9 Building a unique health Management Information System with the MOH
  10. 10.  Insuring data quality when receiving a huge number of data, request some quality control practices involving data check, triangulation when data are reaching the different levels of data aggregation.  At the highest level of aggregation in SANRU offices, different source are examined in purpose to get an idea of the quality of the data collected and aggregated.  The most common method is the comparison of programmatic data with supply chain management data. 10 Getting higher data quality by comparing data from different sources
  11. 11.  For instance, controlling the quality of data on People tested with Rapid DiagnosisTest, data are compared with the RDT distribution report from SCM 11 Getting higher data quality by comparing data from different sources Table1:persons testedVs RDT used during 6 month
  12. 12.  Managing a project with multiple actors as sub recipient and with a strong commitment of success to donors requests a regular analysis of sub recipients performances and assistance to those who do not meet the requirement in achieving the program targets.This print show an overview of a print taken from Malaria GF Program 12 Rationalizing follow-up using periodic performance rating
  13. 13. 13 Rationalizing follow-up using periodic performance rating