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

Author:

Volk Jonathan E.1,Leyden Wendy A.2,Lea Alexandra N.2,Lee Catherine2,Donnelly Michelle C.3,Krakower Douglas S.45,Lee Kristine6,Liu Vincent X.2,Marcus Julia L.4,Silverberg Michael J.2

Affiliation:

1. Department of Infectious Diseases, Kaiser Permanente San Francisco, San Francisco, CA;

2. Division of Research, Kaiser Permanente Northern California, Oakland, CA;

3. Kaiser Permanente Information Technology, Pleasanton, CA;

4. Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA;

5. Division of Infectious Diseases, Beth Israel Deaconess Medical Center, Boston, MA; and

6. Department of Adult and Family Medicine, Kaiser Permanente San Francisco, San Francisco, CA.

Abstract

Background: Preexposure prophylaxis (PrEP) use remains limited and inequitable, and strategies are needed to improve PrEP provision in primary care. Methods: We conducted a cluster randomized trial at Kaiser Permanente, San Francisco, to evaluate the effectiveness of a clinical decision support intervention guided by an electronic health record (EHR)–based HIV risk prediction model to improve PrEP provision. Primary care providers (PCPs) were randomized to usual care or intervention, with PCPs who provide care to people with HIV balanced between arms. PCPs in the intervention arm received an EHR-based staff message with prompts to discuss HIV prevention and PrEP before upcoming in-person or video visits with patients whose predicted 3-year HIV risk was above a prespecified threshold. The main study outcome was initiation of PrEP care within 90 days, defined as PrEP discussions, referrals, or prescription fills. Results: One hundred twenty-one PCPs had 5051 appointments with eligible patients (2580 usual care; 2471 intervention). There was a nonsignificant increase in initiation of PrEP care in the intervention arm (6.0% vs 4.5%, HR 1.32, 95% CI: 0.84 to 2.1). There was a significant interaction by HIV provider status, with an intervention HR of 2.59 (95% CI: 1.30 to 5.16) for HIV providers and 0.89 (95% CI: 0.59 to 1.35) for non-HIV providers (P-interaction <0.001). Conclusion: An EHR-based intervention guided by an HIV risk prediction model substantially increased initiation of PrEP care among patients of PCPs who also care for people with HIV. Higher-intensity interventions may be needed to improve PrEP provision among PCPs less familiar with PrEP and HIV care.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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