Implementing Indicator Condition–Guided HIV Screening Alerts in the Emergency Department: Lessons Learned from a Case Study.
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| Title: | Implementing Indicator Condition–Guided HIV Screening Alerts in the Emergency Department: Lessons Learned from a Case Study. |
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| Authors: | Fanjul, Francisco1,2,3 (AUTHOR) franciscoj.fanjul@ssib.es, Macià Romero, Maria Dolores2,3,4 (AUTHOR), Fraile, Pablo2,4 (AUTHOR), Guiu, Alexandra3,5 (AUTHOR), Campins, Antoni1,2 (AUTHOR), Ferré, Adrià1,2 (AUTHOR), Pinecki, Sophia2 (AUTHOR), Riera, Melchor1,2,3 (AUTHOR) |
| Source: | Inquiry (00469580). 7/24/2026, Vol. 63, p1-7. 7p. |
| Subject Terms: | *Longitudinal method, *Case studies, Diagnosis of HIV infections, Patient compliance, Effect sizes (Statistics), Research funding, Clinical decision support systems, Hospital emergency services, HIV infections, Descriptive statistics, Chi-squared test, Odds ratio, Electronic health records, Medical screening, Quality assurance, Confidence intervals |
| Abstract: | Introduction: Indicator condition (IC)-guided HIV testing is recommended internationally as a cost-effective strategy but remains inconsistently implemented, particularly in emergency departments (EDs). Electronic health record (EHR) alerts may improve adherence; however, real-world uptake depends on organizational and specialty-level determinants. Methods: Prospective case study conducted between August 2023 and April 2025. A non-interruptive EHR alert was triggered by predefined IC-related laboratory orders and antimicrobial prescriptions. Crucially, the alert was only fired if HIV serology was not already requested, meaning that the accepted tests represented true additional screening. Clinicians could accept or decline testing with a single click. Acceptance patterns were analyzed by age group, clinical service, weekday versus weekend, and diurnal versus nocturnal shifts. The analysis employed descriptive stratification to evaluate confounding between patient age and clinical service volume. Results: Among 3,240 alert activations, 523 were accepted (16.1%), resulting in 398 completed tests. Eight patients tested positive (2.01%), including four actionable cases (1.01%). Two declined alerts were followed by subsequent diagnoses of advanced HIV infection. The apparent lower uptake in younger patients was service-level confounded by the concentration of alerts within gynecology/obstetrics (53.7% of all alerts in 18-37-year-olds; global gynecology uptake 3.5%). Outside gynecology, baseline acceptance was consistently higher (15-38%) across all age categories, demonstrating that the apparent age gradient was profoundly confounded by service distribution. Conclusion: Apparent age-related differences in alert uptake were attenuated after stratification by service distribution rather than intrinsic clinician bias regarding patient age. Specialty culture, workflow alignment, and ownership of preventive tasks appear to be central to the adoption of digital alerts in ED settings. [ABSTRACT FROM AUTHOR] |
| Copyright of Inquiry (00469580) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 195627715 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Implementing Indicator Condition–Guided HIV Screening Alerts in the Emergency Department: Lessons Learned from a Case Study. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Fanjul%2C+Francisco%22">Fanjul, Francisco</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> franciscoj.fanjul@ssib.es</i><br /><searchLink fieldCode="AR" term="%22Macià+Romero%2C+Maria+Dolores%22">Macià Romero, Maria Dolores</searchLink><relatesTo>2,3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fraile%2C+Pablo%22">Fraile, Pablo</searchLink><relatesTo>2,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Guiu%2C+Alexandra%22">Guiu, Alexandra</searchLink><relatesTo>3,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Campins%2C+Antoni%22">Campins, Antoni</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ferré%2C+Adrià%22">Ferré, Adrià</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pinecki%2C+Sophia%22">Pinecki, Sophia</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Riera%2C+Melchor%22">Riera, Melchor</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Inquiry+%2800469580%29%22">Inquiry (00469580)</searchLink>. 7/24/2026, Vol. 63, p1-7. 7p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Longitudinal+method%22">Longitudinal method</searchLink><br />*<searchLink fieldCode="DE" term="%22Case+studies%22">Case studies</searchLink><br /><searchLink fieldCode="DE" term="%22Diagnosis+of+HIV+infections%22">Diagnosis of HIV infections</searchLink><br /><searchLink fieldCode="DE" term="%22Patient+compliance%22">Patient compliance</searchLink><br /><searchLink fieldCode="DE" term="%22Effect+sizes+%28Statistics%29%22">Effect sizes (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Clinical+decision+support+systems%22">Clinical decision support systems</searchLink><br /><searchLink fieldCode="DE" term="%22Hospital+emergency+services%22">Hospital emergency services</searchLink><br /><searchLink fieldCode="DE" term="%22HIV+infections%22">HIV infections</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Chi-squared+test%22">Chi-squared test</searchLink><br /><searchLink fieldCode="DE" term="%22Odds+ratio%22">Odds ratio</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+health+records%22">Electronic health records</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+screening%22">Medical screening</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+assurance%22">Quality assurance</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Introduction: Indicator condition (IC)-guided HIV testing is recommended internationally as a cost-effective strategy but remains inconsistently implemented, particularly in emergency departments (EDs). Electronic health record (EHR) alerts may improve adherence; however, real-world uptake depends on organizational and specialty-level determinants. Methods: Prospective case study conducted between August 2023 and April 2025. A non-interruptive EHR alert was triggered by predefined IC-related laboratory orders and antimicrobial prescriptions. Crucially, the alert was only fired if HIV serology was not already requested, meaning that the accepted tests represented true additional screening. Clinicians could accept or decline testing with a single click. Acceptance patterns were analyzed by age group, clinical service, weekday versus weekend, and diurnal versus nocturnal shifts. The analysis employed descriptive stratification to evaluate confounding between patient age and clinical service volume. Results: Among 3,240 alert activations, 523 were accepted (16.1%), resulting in 398 completed tests. Eight patients tested positive (2.01%), including four actionable cases (1.01%). Two declined alerts were followed by subsequent diagnoses of advanced HIV infection. The apparent lower uptake in younger patients was service-level confounded by the concentration of alerts within gynecology/obstetrics (53.7% of all alerts in 18-37-year-olds; global gynecology uptake 3.5%). Outside gynecology, baseline acceptance was consistently higher (15-38%) across all age categories, demonstrating that the apparent age gradient was profoundly confounded by service distribution. Conclusion: Apparent age-related differences in alert uptake were attenuated after stratification by service distribution rather than intrinsic clinician bias regarding patient age. Specialty culture, workflow alignment, and ownership of preventive tasks appear to be central to the adoption of digital alerts in ED settings. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Inquiry (00469580) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1177/00469580261468834 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 7 StartPage: 1 Subjects: – SubjectFull: Longitudinal method Type: general – SubjectFull: Case studies Type: general – SubjectFull: Diagnosis of HIV infections Type: general – SubjectFull: Patient compliance Type: general – SubjectFull: Effect sizes (Statistics) Type: general – SubjectFull: Research funding Type: general – SubjectFull: Clinical decision support systems Type: general – SubjectFull: Hospital emergency services Type: general – SubjectFull: HIV infections Type: general – SubjectFull: Descriptive statistics Type: general – SubjectFull: Chi-squared test Type: general – SubjectFull: Odds ratio Type: general – SubjectFull: Electronic health records Type: general – SubjectFull: Medical screening Type: general – SubjectFull: Quality assurance Type: general – SubjectFull: Confidence intervals Type: general Titles: – TitleFull: Implementing Indicator Condition–Guided HIV Screening Alerts in the Emergency Department: Lessons Learned from a Case Study. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Fanjul, Francisco – PersonEntity: Name: NameFull: Macià Romero, Maria Dolores – PersonEntity: Name: NameFull: Fraile, Pablo – PersonEntity: Name: NameFull: Guiu, Alexandra – PersonEntity: Name: NameFull: Campins, Antoni – PersonEntity: Name: NameFull: Ferré, Adrià – PersonEntity: Name: NameFull: Pinecki, Sophia – PersonEntity: Name: NameFull: Riera, Melchor IsPartOfRelationships: – BibEntity: Dates: – D: 24 M: 07 Text: 7/24/2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 00469580 Numbering: – Type: volume Value: 63 Titles: – TitleFull: Inquiry (00469580) Type: main |
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