Remembering Who the Data Are For

By Liz Millar, MPH, MEASURE Evaluation

MEXICO CITY, Mexico—This week at the International AIDS Conference on HIV Science (July 21–24, 2019), MEASURE Evaluation conducted a session titled “Measuring what counts: Maximizing the use of health information to speed country progress toward the 95-95-95 targets.”

During the session, we invited the audience to share perspectives on the most important advancements in HIV data collection and what priorities should be to improve health information. The audience identified several advancements, including improvements in completeness and accuracy of data and the introduction of electronic systems and mobile technology to make data collection easier.

When it came to what the priorities should be, the conversation focused on the end users: Making data more accessible to health workers in clinics and communities; making sure health workers aren’t overburdened by immense data collection tasks; and the importance of remembering that every client identification number and all the data rolled into aggregated data sets belongs to a person. MEASURE Evaluation, funded by the United States Agency for International Development and the U.S. President’s Emergency Plan for AIDS Relief, focuses on systems, data elements, and exciting new technologies. But we try never to forget the individuals for whom the systems are built and who are meant to benefit from the technology.

For example, a health clinic in rural Malawi might make a registry entry for a 25-year-old mother of two who is HIV positive but adheres to her antiretroviral therapy (ART) and is virally suppressed. She visits the clinic regularly when she needs medication, but she’s recently moved to work in a new district. So far, data have been used successfully to help support this person. But in her new setting, she doesn’t know where to go for ART treatment counseling or if there are providers she can trust not to disclose her HIV status. She’ll be counted in Malawi’s aggregate statistics on achieving the goals of 90-90-90[i], but what that data won’t capture is that she’s now at risk for falling out of ART adherence. Her two children are HIV negative, but she’s pregnant with a third child, who will be at increased risk of HIV acquisition if she is not on treatment. This woman falls into a gap that existing HIV programs in her region may not be addressing.

Improved health information can help identify and address this gap, while also allowing HIV programs to more closely follow individual clients in the larger health system. With data that are complete and accurate and data systems that are increasingly interoperable, improved opportunities exist to use that data to identify when people move from one region to another across health systems and to alert any program to what kind of care and support that person may need.