Giving Your Electronic Health Record a Checkup After COVID-19: A Practical Framework for Reviewing Clinical Decision Support in Light of the Telemedicine Expansion.

COVID-19 EHR ambulatory care clinical decision support electronic health record framework implementation telemedicine

Journal

JMIR medical informatics
ISSN: 2291-9694
Titre abrégé: JMIR Med Inform
Pays: Canada
ID NLM: 101645109

Informations de publication

Date de publication:
27 Jan 2021
Historique:
received: 10 07 2020
accepted: 15 12 2020
revised: 12 10 2020
pubmed: 6 1 2021
medline: 6 1 2021
entrez: 5 1 2021
Statut: epublish

Résumé

The transformation of health care during COVID-19, with the rapid expansion of telemedicine visits, presents new challenges to chronic care and preventive health providers. Clinical decision support (CDS) is critically important to chronic care providers, and CDS malfunction is common during times of change. It is essential to regularly reassess an organization's ambulatory CDS program to maintain care quality. This is especially true after an immense change, like the COVID-19 telemedicine expansion. Our objective is to reassess the ambulatory CDS program at a large academic medical center in light of telemedicine's expansion in response to the COVID-19 pandemic. Our clinical informatics team devised a practical framework for an intrapandemic ambulatory CDS assessment focused on the impact of the telemedicine expansion. This assessment began with a quantitative analysis comparing CDS alert performance in the context of in-person and telemedicine visits. Board-certified physician informaticists then completed a formal workflow review of alerts with inferior performance in telemedicine visits. Informaticists then reported on themes and optimization opportunities through the existing CDS governance structure. Our assessment revealed that 10 of our top 40 alerts by volume were not firing as expected in telemedicine visits. In 3 of the top 5 alerts, providers were significantly less likely to take action in telemedicine when compared to office visits. Cumulatively, alerts in telemedicine encounters had an action taken rate of 5.3% (3257/64,938) compared to 8.3% (19,427/233,636) for office visits. Observations from a clinical informaticist workflow review included the following: (1) Telemedicine visits have different workflows than office visits. Some alerts developed for the office were not appearing at the optimal time in the telemedicine workflow. (2) Missing clinical data is a common reason for the decreased alert firing seen in telemedicine visits. (3) Remote patient monitoring and patient-reported clinical data entered through the portal could replace data collection usually completed in the office by a medical assistant or registered nurse. In a large academic medical center at the pandemic epicenter, an intrapandemic ambulatory CDS assessment revealed clinically significant CDS malfunctions that highlight the importance of reassessing ambulatory CDS performance after the telemedicine expansion.

Sections du résumé

BACKGROUND BACKGROUND
The transformation of health care during COVID-19, with the rapid expansion of telemedicine visits, presents new challenges to chronic care and preventive health providers. Clinical decision support (CDS) is critically important to chronic care providers, and CDS malfunction is common during times of change. It is essential to regularly reassess an organization's ambulatory CDS program to maintain care quality. This is especially true after an immense change, like the COVID-19 telemedicine expansion.
OBJECTIVE OBJECTIVE
Our objective is to reassess the ambulatory CDS program at a large academic medical center in light of telemedicine's expansion in response to the COVID-19 pandemic.
METHODS METHODS
Our clinical informatics team devised a practical framework for an intrapandemic ambulatory CDS assessment focused on the impact of the telemedicine expansion. This assessment began with a quantitative analysis comparing CDS alert performance in the context of in-person and telemedicine visits. Board-certified physician informaticists then completed a formal workflow review of alerts with inferior performance in telemedicine visits. Informaticists then reported on themes and optimization opportunities through the existing CDS governance structure.
RESULTS RESULTS
Our assessment revealed that 10 of our top 40 alerts by volume were not firing as expected in telemedicine visits. In 3 of the top 5 alerts, providers were significantly less likely to take action in telemedicine when compared to office visits. Cumulatively, alerts in telemedicine encounters had an action taken rate of 5.3% (3257/64,938) compared to 8.3% (19,427/233,636) for office visits. Observations from a clinical informaticist workflow review included the following: (1) Telemedicine visits have different workflows than office visits. Some alerts developed for the office were not appearing at the optimal time in the telemedicine workflow. (2) Missing clinical data is a common reason for the decreased alert firing seen in telemedicine visits. (3) Remote patient monitoring and patient-reported clinical data entered through the portal could replace data collection usually completed in the office by a medical assistant or registered nurse.
CONCLUSIONS CONCLUSIONS
In a large academic medical center at the pandemic epicenter, an intrapandemic ambulatory CDS assessment revealed clinically significant CDS malfunctions that highlight the importance of reassessing ambulatory CDS performance after the telemedicine expansion.

Identifiants

pubmed: 33400683
pii: v9i1e21712
doi: 10.2196/21712
pmc: PMC7842852
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e21712

Informations de copyright

©Jonah Feldman, Adam Szerencsy, Devin Mann, Jonathan Austrian, Ulka Kothari, Hye Heo, Sam Barzideh, Maureen Hickey, Catherine Snapp, Rod Aminian, Lauren Jones, Paul Testa. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 27.01.2021.

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Auteurs

Jonah Feldman (J)

Medical Center Information Technology, NYU Langone Health, New York, NY, United States.
Department of Medicine, NYU Long Island School of Medicine, Mineola, NY, United States.

Adam Szerencsy (A)

Medical Center Information Technology, NYU Langone Health, New York, NY, United States.
Department of Medicine, NYU Grossman School of Medicine, New York, NY, United States.

Devin Mann (D)

Medical Center Information Technology, NYU Langone Health, New York, NY, United States.
Department of Population Health, NYU Grossman School of Medicine, New York, NY, United States.

Jonathan Austrian (J)

Medical Center Information Technology, NYU Langone Health, New York, NY, United States.
Department of Medicine, NYU Grossman School of Medicine, New York, NY, United States.

Ulka Kothari (U)

Medical Center Information Technology, NYU Langone Health, New York, NY, United States.
Department of Pediatrics, NYU Long Island School of Medicine, Mineola, NY, United States.

Hye Heo (H)

Medical Center Information Technology, NYU Langone Health, New York, NY, United States.
Department of Obstetrics and Gynecology, NYU Long Island School of Medicine, Mineola, NY, United States.

Sam Barzideh (S)

Medical Center Information Technology, NYU Langone Health, New York, NY, United States.
Department of Orthopedics, NYU Long Island School of Medicine, Mineola, NY, United States.

Maureen Hickey (M)

Medical Center Information Technology, NYU Langone Health, New York, NY, United States.

Catherine Snapp (C)

Medical Center Information Technology, NYU Langone Health, New York, NY, United States.

Rod Aminian (R)

Medical Center Information Technology, NYU Langone Health, New York, NY, United States.

Lauren Jones (L)

Medical Center Information Technology, NYU Langone Health, New York, NY, United States.

Paul Testa (P)

Medical Center Information Technology, NYU Langone Health, New York, NY, United States.

Classifications MeSH