Evidence map›Paper›PMID 38335447›Full record

ArticleJournal of women's health (2002)2024

Assessing Patient Acceptance of an Automated Algorithm to Identify Ciswomen for HIV Pre-Exposure Prophylaxis.

Shivanjali Shankaran, Eleanor E Friedman, Samantha Devlin, Ekta Kishen, Joseph A Mason, Beverly E Sha, Darjai Payne, Katherine Sinchek, Natali Smiley, Sloane York and 1 more

Open access · greenAbstract read
In one paragraph

Article in Journal of women's health (2002), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 98% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Shivanjali ShankaranDivision of Infectious Diseases, Rush University Medical Center, Chicago, Illinois, USA.
Eleanor E FriedmanSection of Infectious Diseases and Global Health, Department of Medicine, University of Chicago, Chicago, Illinois, USA.
Samantha DevlinSection of Infectious Diseases and Global Health, Department of Medicine, University of Chicago, Chicago, Illinois, USA.
Ekta KishenRush Research Informatics Core, Rush University Medical Center, Chicago, Illinois, USA.
Joseph A MasonSection of Infectious Diseases and Global Health, Department of Medicine, University of Chicago, Chicago, Illinois, USA.
Beverly E ShaDivision of Infectious Diseases, Rush University Medical Center, Chicago, Illinois, USA.
Darjai PayneDivision of Infectious Diseases, Rush University Medical Center, Chicago, Illinois, USA.
Katherine SinchekDivision of Infectious Diseases, Rush University Medical Center, Chicago, Illinois, USA.ORCID 0000-0002-7049-8241
Natali SmileyDivision of Infectious Diseases, Rush University Medical Center, Chicago, Illinois, USA.
Sloane YorkDepartment of Obstetrics and Gynecology, Rush University Medical Center, Chicago, Illinois, USA.
Jessica P RidgwaySection of Infectious Diseases and Global Health, Department of Medicine, University of Chicago, Chicago, Illinois, USA.
Rush University Medical Center · USUniversity of Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AlgorithmsHIV InfectionsPatient Acceptance of Health CarePre-Exposure ProphylaxisAdultAnti-HIV AgentsChicagoElectronic Health RecordsFemaleHumansMiddle AgedSurveys and QuestionnairesYoung AdultAnti-HIV Agentselectronic algorithmelectronic medical recordsHIVpre-exposure prophylaxis (PrEP)women

Identifiers

PMID38335447
PMCPMC11238832
OpenAlexW4391676665

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.