When it comes to health data in developing nations, many of us are facing big, gaping holes – and I’m not referring to pit latrines.  I’m talking about the lack of data reported on traditional healthcare services, which constitute a significant portion of healthcare provision around the world.  According to the WHO, in some nations as much as 80% of the population primarily uses traditional health care.  But we have very little data on these practices and few nations have national polices regarding traditional medicine.  This makes it very difficult to monitor and evaluate traditional services.  And without this data, there are certainly gaps in our health statistics.

As health researchers, we can all agree that we are missing something.  But we may not agree on the solution.  Governments and researchers have utilized a handful of methods to attempt to gather better data on traditional healthcare provision.  The most notable methods include (1) training and/or regulating traditional healthcare providers, (2) the use of knowledge brokers, such as community health workers, to bridge data divides, and (3) the use of secondary source indicators to estimate data.  As far as I can tell, no one has been hugely successful or inspired mass replication.  So where does that leave us?

It leaves me wondering whether we should take a cue from Esther Duflo and Abhijit Banerjee, authors of Poor Economics.  Duflo and Banerjee argue that individuals respond to incentives.  Based on this theory, we need to assess the incentives of the “gatekeepers” of the missing data – a.k.a. the traditional healers.  What incentives – or disincentives – might they have to cooperate with governments and researchers in their efforts to gather traditional health data?

The disincentives are obvious.  There is long-standing dissonance between modern science and traditional healthcare.  Over the years, scientists have accused traditional providers of harming patients with false information and ineffective treatments, among other things. Naturally, traditional healers have responded with anger and fear of de-legitimization.  As the modern world grows more interested in traditional, alternative, and herbal-based healthcare methods, traditional providers have developed new fears of intellectual property theft.  This is all to say that traditional healthcare providers have strong impediments to cooperation.  

Certainly the incentives for cooperation are less obvious.  But they do exist.  And you get a glimpse of them when you visit the websites of various councils and organizations of traditional healers.  These organized groups of practitioners state their objectives in no uncertain terms.  They seek professional legitimacy and political support that cement their positions in society.  This includes legal protections, professionalization, and national policies on traditional medicine.  Assuming that the views expressed on these websites represent the general views of legitimate traditional healers (perhaps a big assumption), we can begin to understand the traditional healers’ individual and group incentives.  This knowledge can help us imagine a framework that includes traditional health workers in data collection efforts.

Perhaps the key to gathering traditional health data is the creation of data collection processes that recognize traditional healers’ desires for legitimacy.  In providing healers with paths to legitimacy, public health officials and researchers might achieve real collaboration – and finally fill those elusive data gaps.  I’m not entirely sure what these new processes and “paths” should look like.  What about you? Do you have a vision of this future or an alternative idea for addressing the data gap? 

Rebecca Hornbach is a dual masters' candidate in Global Policy Studies and Public Health at The University of Texas at Austin.

Originally posted on AidData's First Tranche here.

Wednesday, July 3, 2013

Open data has generated a lot of buzz recently, prompting governments to make increasing amounts of data publicly accessible and catalyzing new partnerships with private sector and civil society actors around the use and reuse of this information. How much of the open data movement is flash versus substance? As an AidData Summer Fellow with the Center of Environmental and Agricultural Policy Research, Extension and Development (CEAPRED) in Nepal, I have witnessed firsthand that ensuring that open aid reporting programs are responsive to the real needs of citizens is key to maximizing their impact. My recent participation in Open Nepal’s Data Literacy Bootcamp underscores this point.

On June 3rd and 4th, I participated in Open Nepal Week’s Data Literacy Bootcamp in Kathmandu, supported by the Open Aid Partnership. A coalition of organizations, including Freedom Forum, Young Innovations, NGO Federation of Nepal, Development Initiatives, and Development Gateway, trained with over 80 Nepali journalists, developers, coders, and civil society representatives to find, extract, and analyze public data. Participants learned how to consolidate data and create visualizations using Geographic Information Systems (GIS) platforms and Java applications. A 48-hour competition enabled participants to put their new knowledge to practical use as they conceptualized business plans for digital or web applications leveraging open data. Sponsors Google, the World Bank Institute, and African Media Initiative, envisioned the competition as empowering citizens to utilize open data.

Varsha Upraity, a Research Officer at CEAPRED, proposed an idea for an app that would report on whether the user is meeting their daily nutritional requirements, and make recommendations for local market, clinics, and support groups. Engaging remote and severely disadvantaged communities proved to be an obstacle in planning Varsha’s app, which would be primarily web or SMS-based and thus inaccessible to many high-need areas. Inevitably, some users would be left out. This raised a critical question: how could we prevent this from happening?

Designing a data-driven application responsive to the needs of even the most disadvantaged communities is a challenge that is not unique to Varsha’s experience. Transparent data reporting and visualizations offer a powerful way to inform the public about development progress. Yet, there are broader questions for policy makers and open data advocates regarding how the Open Data movement defines its goals and what success should look like. The answers are critical to informing the degree to which inclusivity and consideration of citizens factor into the creation of new apps.

Experiences such as the Nepal Open Data Literacy Bootcamp remind us that open data and the applications it spawns can help build the capacity of citizens to track and evaluate information on their country’s development. It is equally apparent that merely releasing data or developing new data driven apps does not necessarily address issues of inclusivity, representation and participation across society.  However, these issues remain largely unaddressed in spite of the rapid growth of the Open Data movement. I would submit that, as the Open Data movement evolves in Nepal and elsewhere, these issues should be front and center and inform the design of solutions that leverage both data and human capabilities.


Madeline Clark is an IPD Graduate Research Affiliate and AidData Summer Fellow with the Center of Environmental and Agricultural Policy Research, Extension, and Development (CEAPRED) in Nepal.