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Appl Clin Inform 2024; 15(01): 192-198
DOI: 10.1055/a-2250-6305
Case Report

An Electronic Health Record Alert for Inpatient Coronavirus Disease 2019 Vaccinations Increases Vaccination Ordering and Uncovers Workflow Inefficiencies

Kameron Collin Black
1   Department of Medicine, Oregon Health and Science University, Portland, Oregon
,
Nicole Ashley Snyder
2   Rocky Vista University, Parker, Colorado
,
Mengyu Zhou
1   Department of Medicine, Oregon Health and Science University, Portland, Oregon
,
Zhen Zhu
1   Department of Medicine, Oregon Health and Science University, Portland, Oregon
,
Colby Uptegraft
3   Health Informatics Directorate, Defense Health Agency, Falls Church, Virginia
,
Ani Chintalapani
1   Department of Medicine, Oregon Health and Science University, Portland, Oregon
4   Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, Oregon
,
Benjamin Orwoll
4   Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, Oregon
5   Department of Pediatrics, Oregon Health and Science University, Portland, Oregon
› Author Affiliations Funding None.
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Abstract

Background Despite mortality benefits, only 19.9% of U.S. adults are fully vaccinated against the coronavirus disease 2019 (COVID-19). The inpatient setting is an opportune environment to update vaccinations, and inpatient electronic health record (EHR) alerts have been shown to increase vaccination rates.

Objective Our objective was to evaluate whether an EHR alert could increase COVID-19 vaccinations in eligible hospitalized adults by prompting providers to order the vaccine.

Methods This was a quasiexperimental pre–post-interventional design study at an academic and community hospital in the western United States between 1 January, 2021 and 31 October, 2021. Inclusion criteria were unvaccinated hospitalized adults. A soft-stop, interruptive EHR alert prompted providers to order COVID-19 vaccines for those with an expected discharge date within 48 hours and interest in vaccination. The outcome measured was the proportion of all eligible patients for whom vaccines were ordered and administered before and after alert implementation.

Results Vaccine ordering rates increased from 4.0 to 13.0% at the academic hospital (odds ratio [OR]: 4.01, 95% confidence interval [CI]: 3.39–4.74, p < 0.001) and from 7.4 to 11.6% at the community hospital (OR: 1.62, 95% CI: 1.23–2.13, p < 0.001) after alert implementation. Administration increased postalert from 3.6 to 12.7% at the academic hospital (OR: 3.21, 95% CI: 2.70–3.82, p < 0.001) but was unchanged at the community hospital, 6.7 to 6.7% (OR: 0.99, 95% CI: 0.73–1.37, p = 0.994). Further analysis revealed infrequent vaccine availability at the community hospital.

Conclusion Vaccine ordering rates improved at both sites after alert implementation. Vaccine administration rates, however, only improved at the academic hospital, likely due in part to vaccine dispensation inefficiency at the community hospital. This study demonstrates the potential impact of complex workflow patterns on new EHR alert success and provides a rationale for subsequent qualitative workflow analysis with alert implementation.

Keywords

computerized soft-stop - clinical decision support - electronic health records - decision support systems - vaccination - COVID-19 - academic hospital

Author Contributions

K.C.B contributed in conceptualization, investigation, methodology, and writing. N.S. was involved in investigation, and writing. M.Z. contributed in conceptualization, investigation, supervision, writing. Z.Z. helped in writing. C.U. contributed in conceptualization, writing, supervision. A.C. contributed in writing, and supervision while B.O was in volved in investigation, writing, and supervision.


Protection of Human and Animal Subjects

This study was reviewed by the OHSU Institutional Review Board and deemed exempt (STUDY00026409).


Data Availability

The data involved in this study are available in the article.




Publication History

Received: 03 July 2023

Accepted: 19 January 2024

Accepted Manuscript online:
22 January 2024

Article published online:
06 March 2024

© 2024. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

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