AJPM Focus (Dec 2023)

Using Electronic Health Record Data to Measure the Latent Tuberculosis Infection Care Cascade in Safety-Net Primary Care Clinics

  • Laura A. Vonnahme, MPH,
  • Julia Raykin, PhD,
  • Matthew Jones, MS,
  • Jee Oakley, MPH,
  • Jon Puro, MPA,
  • Adam Langer, DVM,
  • Kaylynn Aiona, MPH,
  • Robert Belknap, MD,
  • Tracy Ayers, PhD,
  • Jonathan Todd, PhD,
  • Kathryn Winglee, PhD

Journal volume & issue
Vol. 2, no. 4
p. 100148

Abstract

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Introduction: Prevention of tuberculosis disease through diagnosis and treatment of latent tuberculosis infection is critical for achieving tuberculosis elimination in the U.S. Diagnosis and treatment of latent tuberculosis infection in safety-net primary care settings that serve patients at risk for tuberculosis may increase uptake of this prevention effort and accelerate progress toward elimination. Optimizing tuberculosis prevention in these settings requires measuring the latent tuberculosis infection care cascade (testing, diagnosis, and treatment) and identifying gaps to develop solutions to overcome barriers. We used electronic health record data to describe the latent tuberculosis infection care cascade and identify gaps among a network of safety-net primary care clinics. Methods: Electronic health record data for patients seen in the OCHIN Clinical Network, the largest network of safety-net clinics in the U.S., between 2012 and 2019 were extracted. electronic health record data were used to measure the latent tuberculosis infection care cascade: patients who met tuberculosis screening criteria on the basis of current recommendations were tested for tuberculosis infection, diagnosed with latent tuberculosis infection, and prescribed treatment for latent tuberculosis infection. Outcomes were stratified by diagnostic test and treatment regimen. Results: Among 1.9 million patients in the analytic cohort, 43.5% met tuberculosis screening criteria, but only 21.4% were tested for latent tuberculosis infection; less than half (40.4%) were tested using an interferon-gamma release assay. Among those with a valid result, 10.5% were diagnosed with latent tuberculosis infection, 29.1% of those were prescribed latent tuberculosis infection treatment, and only 33.6% were prescribed a recommended rifamycin-based regimen. Conclusions: Electronic health record data can be used to measure the latent tuberculosis infection care cascade. A large proportion of patients in this safety-net clinical network are at high risk for tuberculosis infection. Addressing identified gaps in latent tuberculosis infection testing and treatment may have a direct impact on improving tuberculosis prevention in primary care clinics and accelerate progress toward elimination.

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