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.

1. Antoine L. MAFWILA, MD MPH
Chief Monitoring and Evaluation
SANRU
1CCIH 31stAnnual Conference, July 15th 2017

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.  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.  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

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.  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.  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
Building a unique health Management Information
System with the MOH

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.  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.  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
Rationalizing follow-up using periodic performance rating

14. THANKS YOU
FOR YOUR ATTENTION!
14