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

被引:2
|
作者
Volk, Jonathan E. [1 ,8 ]
Leyden, Wendy A. [2 ]
Lea, Alexandra N. [2 ]
Lee, Catherine [2 ]
Donnelly, Michelle C. [3 ]
Krakower, Douglas S. [4 ,5 ,6 ]
Lee, Kristine [7 ]
Liu, Vincent X. [2 ]
Marcus, Julia L. [4 ,5 ]
Silverberg, Michael J. [2 ]
机构
[1] Kaiser Permanente San Francisco, Dept Gastroenterol, San Francisco, CA USA
[2] Div Res, Kaiser Permanente Northern Calif, Oakland, CA USA
[3] Kaiser Permanente Informat Technol, Pleasanton, CA USA
[4] Harvard Med Sch, Dept Populat Med, Boston, MA USA
[5] Harvard Pilgrim Hlth Care Inst, Boston, MA USA
[6] Beth Israel Deaconess Med Ctr, Div Infect Dis, Boston, MA USA
[7] Dept Adult & Family Med, Kaiser Permanente San Francisco, San Francisco, CA USA
[8] 2238 Geary Blvd, San Francisco, CA 94115 USA
关键词
HIV preexposure prophylaxis; machine learning; artificial intelligence; primary care; ETHNIC DISPARITIES; SERVICES; MEN; SEX;
D O I
10.1097/QAI.0000000000003376
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
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.
引用
收藏
页码:362 / 369
页数:8
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