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ICCM: Improving Data to Improve Programs

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Research Overview

In April 2011, an award was made to Johns Hopkins University to conduct embedded operations research in Malawi, Ethiopia, Mali, and Mozambique to improve iCCM monitoring systems and data availability and quality, using the iCCM Benchmarks indicators as the framework.  The “Implementation Research Embedded in Integrated Community Case Management Program: Improving Data to Improve Programs (CCM-IDIP)” project had the goal of improving routine and episodic monitoring of CCM programming in order to strengthen implementation and enhance the overall impact of CCM implementation on child survival in Malawi, Mozambique, Ethiopia, and globally.

Project Location

Malawi, Mali, Mozambique, Ethiopia

Research Objectives

The objective of this research was to improve monitoring of iCCM programming. The “Improving Data to Improve Systems” study was embedded within iCCM programs of four sub-Saharan African countries and focused on the monitoring and evaluation challenge to iCCM. The study team worked to assess iCCM indicators and data quality in each country’s monitoring system, identify priority gaps, and in Malawi, to identify and test potential solutions. TRAction and its research partners addressed the following objectives:

  • Assess iCCM monitoring and evaluation (M&E) systems
  • Identify priority gaps in iCCM M&E systems and potential innovative approaches to data collection
  • Examine feasibility, cost and quality of innovative approaches
  • Document benefits and use of improved iCCM M&E in programmatic decisions

Lessons Learned

Lack of iCCM integration into national M&E systems
  • Data are available for many iCCM indicators, but systems are not in place to be able to collect them. Data are frequently not available for costing indicators.
Good iCCM Data Quality
  • There is a well defined structure for iCCM reporting. Forms are submitted with reasonable levels of reporting, completeness, and consistency.
Low Levels of Data Use
  • Data use is limited, especially at lower levels of the health system.
Innovative Approaches have Potential for Impact
  • A data use improvement package helped increase data use at the community level and improved reporting consistency in some indicators.
  • Use of cell phone reporting is an inexpensive, feasible method to produce high-quality monitoring data.

Implications and Recommendations

These findings indicate that iCCM has yet to be well integrated into national M&E systems, and that the resulting lack of data may play a role in the limited scale-up of iCCM. Further integration is needed, and based on initial findings of high data quality, would likely provide reliable data on iCCM programs. Innovative approaches, including those tested by the study team, are needed, particularly to address data use issues. Partners in Malawi are already working on adapting these approaches for wider application.

Research into Action

TRAction and its partners used findings from this research to develop recommendations that will facilitate scale-up of iCCM programs. Findings were scaled up and shared with stakeholders through a variety of channels:

  • Data use package integrated into the iCCM strategy and training package in most districts of Malawi
  • Cell phone reporting method scaled-up
  • Integrated into lessons learned documents which were shared with representatives from 70 countries at the iCCM Evidence Review Symposium
  • Presented country-level results to the Ministries of Health and other key stakeholders in all countries in which case studies were completed
  • Shared with implementing partners through participation on the iCCM Task Force
  • Integrated into TRAction iCCM policy briefs which provide recommendations for policy makers and program managers on iCCM implementation and start-up

Findings and recommendations will continue to be disseminated at both the country and global level as TRAction and its partners develop technical documents, participate in working groups, and attend key events.

Research Partner

Johns Hopkins University
PI: Jennifer Bryce


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