Designing an electronic medical record alert to identify hospitalised patients with HIV: successes and challenges. Issue 1 (15th June 2022)

• Record Type: Journal Article
• Authors: El-Nahal, Walid; Grader-Beck, Thomas; Gebo, Kelly; Holmes, Elizabeth; Herne, Kayla; Moore, Richard; Thompson, David; Berry, Stephen
• Is Part Of: BMJ health & care informatics. Volume 29:Issue 1(2022)
• Publication Date: 2022-06-15
• Subjects: Electronic Health Records -- Common Data Elements -- PatientIdentification Systems -- Infectious Diseases Medicine; Medical informatics -- Great Britain -- Periodicals; Information storage and retrieval systems -- Medical care -- Periodicals; Primary care (Medicine) -- Great Britain -- Data processing -- Periodicals; 362.10285
• DOI: 10.1136/bmjhci-2021-100521
• Languages: English
• ISSNs: 2632-1009

Abstract

Abstract : Objectives: Electronic medical record (EMR) tools can identify specific populations among hospitalised patients, allowing targeted interventions to improve care quality and safety. We created an EMR alert using readily available data elements to identify hospitalised people with HIV (PWH) to facilitate a quality improvement study intended to address two quality/safety concerns (connecting hospitalised PWH to outpatient HIV care and reducing medication errors). Here, we describe the design and implementation of the alert and analyse its accuracy of identifying PWH. Methods: The EMR alert was designed to trigger for at least one of four criteria: (1) an HIV ICD-10-CM code in a problem list, (2) HIV antiretroviral medication(s) on medication lists, (3) an HIV-1 RNA assay ordered or (4) a positive HIV-antibody result. We used manual chart reviews and an EMR database search to determine the sensitivity and positive predictive value (PPV) of the overall alert and its individual criteria. Results: Over a 24-month period, the alert functioned as intended, notifying an intervention team and a data abstraction team about admissions of PWH. Manual review of 1634 hospitalisations identified 18 PWH hospitalisations, all captured by the alert (sensitivity 100%, 95% CI 82.4% to 100.0%). Over the 24 months, the alert triggered for 1191 hospitalisations. Of these, 1004 were PWH hospitalisations, PPV=84.3% (95% CI 82.2% to 86.4%). Using fewer criteria (eg, using only ICD-10-CM codes) identified fewer PWH but increased PPV. Conclusion: An EMR alert effectively identified hospitalised PWH for a quality improvement intervention. Similar alerts might be adapted as tools to facilitate interventions for other chronic diseases.