Assessing Patient Acceptance of an Automated Algorithm to Identify Ciswomen for HIV Pre-Exposure Prophylaxis.
J Womens Health (Larchmt)
; 33(4): 505-514, 2024 Apr.
Article
em En
| MEDLINE
| ID: mdl-38335447
ABSTRACT
The use of HIV pre-exposure prophylaxis (PrEP) in cisgender women (ciswomen) lags far behind their need. Data elements from the electronic medical record (EMR), including diagnosis of a sexually transmitted infection (STI), can be incorporated into automated algorithms for identifying clients who are most vulnerable to HIV and would benefit from PrEP. However, it is unknown how women feel about the use of such technology. In this study, we assessed women's attitudes and opinions about an automated EMR-based HIV risk algorithm and determined if their perspectives varied by level of HIV risk. Respondents were identified using best practice alerts or referral to a clinic for STI symptoms from January to December 2021 in Chicago, IL. Participants were asked about HIV risk factors, their self-perceived HIV risk, and their thoughts regarding an algorithm to identify ciswomen who could benefit from PrEP. Most of the 112 women who completed the survey (85%) thought they were at low risk for HIV, despite high rates of STI diagnoses. The majority were comfortable with the use of this algorithm, but their comfort level dropped when asked about the algorithm identifying them specifically. Ciswomen had mixed feelings about the use of an automated HIV risk algorithm, citing it as a potentially helpful and empowering tool for women, yet raising concerns about invasion of privacy and potential racial bias. Clinics must balance the benefits of using an EMR-based algorithm for ciswomen with their concerns about privacy and bias to improve PrEP uptake among particularly vulnerable women.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
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Aceitação pelo Paciente de Cuidados de Saúde
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Infecções por HIV
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Profilaxia Pré-Exposição
Tipo de estudo:
Guideline
/
Prognostic_studies
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Risk_factors_studies
Limite:
Adult
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Female
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Humans
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Middle aged
País como assunto:
America do norte
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article