TY - JOUR
T1 - Designing an electronic medical record alert to identify hospitalised patients with HIV
T2 - Successes and challenges
AU - El-Nahal, Walid
AU - Grader-Beck, Thomas
AU - Gebo, Kelly
AU - Holmes, Elizabeth
AU - Herne, Kayla
AU - Moore, Richard
AU - Thompson, David
AU - Berry, Stephen
N1 - Publisher Copyright:
© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
PY - 2022/6/15
Y1 - 2022/6/15
N2 - 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.
AB - 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.
KW - Common Data Elements
KW - Electronic Health Records
KW - Infectious Diseases Medicine
KW - PatientIdentification Systems
UR - http://www.scopus.com/inward/record.url?scp=85132080365&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85132080365&partnerID=8YFLogxK
U2 - 10.1136/bmjhci-2021-100521
DO - 10.1136/bmjhci-2021-100521
M3 - Article
C2 - 35705318
AN - SCOPUS:85132080365
SN - 2058-4555
VL - 29
JO - BMJ Health and Care Informatics
JF - BMJ Health and Care Informatics
IS - 1
M1 - e100521
ER -