PRP168: Targeted tuberculosis testing through the development and implementation of clinical decision support tools

Rose Gunn, MA; Matthew Jones, MS; Jon Puro, MPA; Marshall Hammond, MSN, RN; Michael Lieberman, MD, MS; Oyinkansola Ogunrinde, MHA; Jee Oakley; Jonathan Todd, PhD


Context: Tuberculosis (TB) is a leading cause of death worldwide and remains a public health concern. Most new TB cases in the US result from progression of latent tuberculosis infections (LTBI) acquired years earlier. Timely identification and treatment of LTBI in primary care is a critical component of the national TB elimination campaign. Primary care electronic health records (EHRs) would benefit from robust LTBI clinical decision tools. Objective: To pilot a suite of EHR tools designed to facilitate targeted LTBI testing. Study design: Mixed-methods study. Setting: Community health centers in the OCHIN network, a large US-based EHR network with clinics in 20 states. Population studied: Community health center patients at high risk for LTBI and care teams serving those patients. Itervention: Development and implementation of an EHR clinical decision support tool augmented by the creation of new workflows, an improvement guide, comprehensive training, and practice facilitation. Results: Anticipated results will explore the feasibility and acceptability of increasing LTBI testing of high-risk patients using EHR tools and associated implementation support. By developing definitions of high-risk LTBI priority populations with the expertise of clinical provider partners, the EHR-based solution will maximize efficiency to clinical workflows while increasing adherence to clinical guidelines for LTBI. Results will include provider preference in EHR based intervention options, potentially increased identification of patient populations at-risk, and improvements in testing and treatment of LTBI. Expected outcomes: Outcomes to be reported include the establishment of improved EHR tools designed to enhance LTBI testing and associated implementation at the local level by focusing on populations most at-risk for LTBI. Identifying new approaches, in collaboration with end-users, may support LTBI testing and, in turn, result in better targeted and more informed population health interventions.

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