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Ceylon Auguste-Nelson, BACarolyn Fisher, PhD, Ranjani Paradise, PhD, Hanna Haptu, MD, Andrew Tibbs and Jennifer Cochran. “‘Like we are family’: Using qualitative methods to understand strategies for engaging patients in community-based latent TB infection treatment.” Presented at the 2021 APHA Annual Meeting and Expo. Virtual.


Quantitative epidemiological data are essential for evaluating progress towards goals for many public health programs but cannot always provide a detailed picture of how and why outcomes occur. By marrying quantitative data with complementary approaches, evaluators can build a more robust understanding of interventions and increase utility of findings. In this presentation, we will describe how qualitative methods were used to explore patient engagement strategies at a community-based latent TB infection treatment program in Lynn, Massachusetts.

In collaboration with Lynn Community Health Center (LCHC), the Massachusetts Department of Public Health (MDPH) scaled up testing and treatment for latent TB infection among patients who were born outside the US. To complement quantitative electronic health record data analysis led by MDPH of 8,827 patients tested October 2016-March 2019, external evaluators conducted semi-structured interviews with 13 patients and 2 physicians and structured interviews with 2 clinicians and 3 community health workers over two years. Using a framework analysis approach, evaluators extracted themes about factors that helped LCHC engage and retain safety-net patients in care. These themes were supplemented with additional qualitative data collected from the TB care team during site visits. Results highlighted the importance of “high-touch” communication, flexibility, and relationship-building for patient engagement.

Overall, the qualitative components of the evaluation facilitated understanding of patient engagement strategies that others can learn from and use in developing their own programs. Evaluations of other public health initiatives can employ similar methods to complement quantitative epidemiological analysis and deepen understanding of programs and outcomes.