Effectiveness of an electronic health record model for HIV pre-exposure prophylaxis

Abstract

Pre-exposure prophylaxis (PrEP) to prevent human immunodeficiency virus (HIV) is extremely effective when taken correctly, though grossly under-prescribed for at-risk patients. We initiated a best practice advisory (BPA) in the Epic electronic medical record (EMR) to identify patients who met criteria for PrEP use. We evaluated this model to determine its effectiveness in identifying patients and its use by providers for increasing prescription of PrEP. The BPA fired 145 times with five total new PrEP prescriptions. Over half of the patients identified were cisgender women, a group that is both under prescribed PrEP and missed by prior EMR PrEP algorithms. Half of the patients were African American, a group at high risk of HIV infection. Though the model was effective at identifying patients, provider initiation of PrEP or acknowledgment of the BPA was low. Further education of providers regarding PrEP usage and expansion of BPA messages are needed to increase rates of PrEP initiation.

Using Electronic Health Records to Improve HIV Preexposure Prophylaxis Care: A Randomized Trial

“…23 In contrast, a recent study implemented EHR alerts about PrEP for adult patients who were MSM, had an STI in the past 2 years, or had frequent STI testing in the prior year, finding that alert acknowledgments and initiation of PrEP were low. 24…”

“…23 In contrast, a recent study implemented EHR alerts about PrEP for adult patients who were MSM, had an STI in the past 2 years, or had frequent STI testing in the prior year, finding that alert acknowledgments and initiation of PrEP were low. 24 Use of prediction models that integrate larger numbers of variables, including proxies for social and structural factors associated with HIV risk, may increase the predictive performance, efficiency, and equity of decision support tools for PrEP. Relying on traditional HIV risk factors, such as MSM status and STI positivity, will miss many individuals at increased risk of HIV acquisition, particularly those from underserved groups, such as Black and Latino people.…”

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

“…Federman et al [53], 2017; Goehler et al [54], 2019; Horton et al [55], 2018; Howell et al [56], 2014; Klang et al [57], 2021; Li et al [58], 2020; Lindholm et al [59], 2010; Melnick et al [60], 2022; Milne Adult et al [61], 2020; Mitchell et al [62], 2022; Mulhem et al [63], 2020; Park et al [64], 2021; Ritchey et al [65], 2016; Rose et al [66], 2018; Ryan et al [67], 2021; Shelley et al [68], 2017; Sroujieh et al [69], 2016; Toscos et al [70], 2020; Toscos et al [71], 2020; Willis et al [72], 2022 Del Fiol et al [73], 2020; DeLozier [74], 2021; Jones et al [75], 2022; Jose et al [76], 2020; Keizur et al [77], 2022; Kolb et al [78], 2016; Lilih et al [79], 2017; Nikolic et al [80], 2017; Ray et al [81], 2018; Adult and pediatric Shelden et al [82], 2021; Siff and Emerman [83], 2016; Sonstein et al [84], 2014; Straub et al [85], 2013; Stutz et al [86], 2018; Tham et al [87], 2016; Wendel et al [88], 2023; Zorn et al [89], 2022 Tsai et al [90], 2015 Not specified Goldberg et al [91], 2016; Hojat et al [92], 2020; Simon et al [93], 2023; Tham et al…”