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Case Reports
. 2024 May 15;7(2):ooae023.
doi: 10.1093/jamiaopen/ooae023. eCollection 2024 Jul.

Integrating clinical research into electronic health record workflows to support a learning health system

Nicole H Goldhaber  1 , Marni B Jacobs  2 , Louise C Laurent  2 , Rob Knight  3   4   5 , Wenhong Zhu  6 , Dean Pham  6 , Allen Tran  6 , Sandip P Patel  7 , Michael Hogarth  8 , Christopher A Longhurst  3   8
Affiliations
Case Reports

Integrating clinical research into electronic health record workflows to support a learning health system

Nicole H Goldhaber et al. JAMIA Open. .

Abstract

Objective: Integrating clinical research into routine clinical care workflows within electronic health record systems (EHRs) can be challenging, expensive, and labor-intensive. This case study presents a large-scale clinical research project conducted entirely within a commercial EHR during the COVID-19 pandemic.

Case report: The UCSD and UCSDH COVID-19 NeutraliZing Antibody Project (ZAP) aimed to evaluate antibody levels to SARS-CoV-2 virus in a large population at an academic medical center and examine the association between antibody levels and subsequent infection diagnosis.

Results: The project rapidly and successfully enrolled and consented over 2000 participants, integrating the research trial with standing COVID-19 testing operations, staff, lab, and mobile applications. EHR-integration increased enrollment, ease of scheduling, survey distribution, and return of research results at a low cost by utilizing existing resources.

Conclusion: The case study highlights the potential benefits of EHR-integrated clinical research, expanding their reach across multiple health systems and facilitating rapid learning during a global health crisis.

Keywords: COVID-19 antibodies; EHR-integration; clinical informatics; clinical research; interoperability.

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Conflict of interest statement

The authors have no competing interests to declare.

Figures

Figure 1.
Figure 1.
Alignment of clinical care and research trials through the electronic health record (EHR) at a learning healthcare system.
Figure 2.
Figure 2.
ZAP enrollment over time. Solid line representing participants who consented to the study, and dotted line representing participants who consented and from whom samples were collected and recorded.
See this image and copyright information in PMC

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