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HP+ ended September 27, 2022

Better Policy for Better Health

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Viewpoints

How We Make the Case Matters

the map showed that most people live more than 4.6 kilometers from a covered village and many live  over 13 kilometers away.
By using geospatial analytics, HP+ Mali was not only able to help decisionmakers visualize disparities in healthcare coverage but also understand how to best reallocate efficiency gains to target underserved areas and provide options for scaling the country’s community health worker program

By Patrick Pascal Saint-Firmin

“Can you make this information less dense and easier on the eye?” “Can we have a shorter, simpler version of your analysis report?” I get these comments a lot from clients in my line of work and often agree that the most important policy pitch is buried under mounds of spreadsheets.

Data. We have piles of it. But what to make of it? How do we make the interpretation of data less complex and more accessible to our partners? My colleagues and I at the USAID-funded Health Policy Plus (HP+) project had been thinking a lot about these questions when we came across a quote from Carly Fiorina, former CEO of Hewlett-Packard and the first woman to lead a top 20 company as ranked by Fortune magazine. She said, “The goal of analytics is to turn data into information, and information into insight.” I would go a step further and say that analytics must also turn insight into practical decision-making. Recently, my colleagues and I put this theory into practice by using innovative visualization techniques to make financing data in support of Mali’s community health worker program more insightful, engaging, and easier for decisionmakers to act upon.

Data, Data, and More Data: The Need for Multiple Approaches

Improving program financial sustainability through evidence-based decision-making has been a driving force of HP+ support to community health workers in Mali for over four years. Ensuring that our technical work had a strong design was key as we conducted stepwise analyses in five of Mali’s eight regions. The body of evidence generated through situational and costing analyses provided a foundation to conduct further analyses, like those that examine efficiency through geospatial mapping and targeting. Efficiency analyses on community health workers, like any other health program, rely on robust financing data: assigning costs to services and recording how much is spent and on what. Again, more data.   

HP+’s Stepwise Analyses of Mali’s Community Health Worker (CHW) Program 
  1. CHW situational analysis: Collect and synthesize data on CHW workforce, funding sources, and program spending nationwide
  2. Costing of CHW-provided services
    • Understand the package of services provided by CHWs + Determine standard level of inputs required by CHWs
    • Estimate cost of health services provided by CHWs required by national norms
  3. District-level efficiency analysis and geospatial mapping and targeting
    • Compare spending and cost required by norms to estimate program efficiency at the district level + Create geospatial outputs and maps using geolocation, district-level spending, and costing and efficiency results
    • Visualize geospatial distribution of CHW program spending and its relationship with cost required by norms at the district-level
    • Visualize geospatial dynamics at district and village levels associated with efficiency results

Breaking the Mold: From Spreadsheets to Data Viz

While financing data are easier to report in rows and columns, this format makes it difficult for most people to draw out insights. Data displayed in spreadsheets are often seen as boring, confusing, and overwhelming. So, the question becomes, how can we make comprehensive financing data more insightful, engaging, and easier for decisionmakers to act upon? A little innovation, primarily in the way data are presented and visualized, can eliminate the limitations historically associated with their inherent complexity. HP+ Mali’s community health worker analyses provided an opportunity for us to think outside the box and consider new ways to present highly quantitative concepts of cost and efficiency in a more pragmatic and visually engaging way. Our goal was to highlight critical nationwide findings that inspire decisionmakers to act. We used location-based analyses (such as distance and proximity used in geospatial targeting) and data visualization (customized maps showing evidence or results in a particular geographical area), more commonly associated with geospatial analytics.

The geospatial analytics and supported interfaces facilitated analytical reasoning. Using a more intuitive and engaging platform, we were able to see patterns and dynamics from the data, which were previously buried in spreadsheets or tables. This allowed key evidence around financial planning for the community health worker program to be more targeted and thus easier for decisionmakers to act upon. A recently published article on community health system reform highlighted how HP+’s situational and costing analyses played a critical role in helping the government of Mali and community health experts understand the context, challenges, and inner dynamics affecting the sustainability of the community health worker program and identify the changes required to move key reforms forward. Further, providing a comprehensive picture of what is really at stake behind our findings will hopefully ensure that Mali’s experience is useful for countries facing similar challenges.

Empowering Decisionmakers to Act

Time is of the essence. The world faces unique health challenges that require information, insight, and effective decision-making, but unless decisionmakers can digest and act on the information we collect and present, we are falling short.

Take the case of community health worker programs. Nearly 60 percent of sub-Saharan Africa’s population lives in rural areas and relies extensively on community health workers to be a cost-effective alternative or extension to facility-based services, particularly in remote and underserved areas. However, the long-term financial sustainability of community health worker programs is in question as many low-income countries in the region have been reluctant to invest their own resources (often relying on foreign assistance). Demonstrating that community health worker programs can be run more efficiently without sacrificing quality provides powerful leverage in dialogues with resource-limited governments.

To make that case we, as data practitioners, need to find ways to present our analyses in more compelling ways. By doing so, we not only assist national and sub-national decisionmakers to act, but also contribute to the collective understanding of and solutions to some of our most pressing health challenges.   

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  • About
    • Project Overview
    • Partners
    • Leadership
    • Contact
    • Work with Us
    • Home
  • Our Work
    • Family Planning
    • HIV
    • COVID-19 Response
    • Health Financing
    • Maternal Health
    • Modeling
    • Capacity Development
    • Gender
    • Health Equity
  • Countries
    • Africa
    • Asia
    • Latin America & the Caribbean
  • Resources
    • Publications
    • Models
    • News
    • Viewpoints
    • Conferences & Events
    • Webinars
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Health Policy Plus (HP+) is a seven-year cooperative agreement funded by the U.S. Agency for International Development under Agreement No. AID-OAA-A-15-00051, beginning August 28, 2015. HP+ is implemented by Palladium, in collaboration with Avenir Health, Futures Group Global Outreach, Plan International USA, Population Reference Bureau, RTI International, ThinkWell, and the White Ribbon Alliance for Safe Motherhood.

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