The Impact of Electronic Health Record-Based Simulation During Intern Boot Camp: Interventional Study.

electronic health records medical education simulation training usability

Journal

JMIR medical education
ISSN: 2369-3762
Titre abrégé: JMIR Med Educ
Pays: Canada
ID NLM: 101684518

Informations de publication

Date de publication:
09 Mar 2021
Historique:
received: 17 11 2020
accepted: 29 01 2021
revised: 11 01 2021
entrez: 9 3 2021
pubmed: 10 3 2021
medline: 10 3 2021
Statut: epublish

Résumé

Accurate data retrieval is an essential part of patient care in the intensive care unit (ICU). The electronic health record (EHR) is the primary method for data storage and data review. We previously reported that residents participating in EHR-based simulations have varied and nonstandard approaches to finding data in the ICU, with subsequent errors in recognizing patient safety issues. We hypothesized that a novel EHR simulation-based training exercise would decrease EHR use variability among intervention interns, irrespective of prior EHR experience. This study aims to understand the impact of a novel, short, high-fidelity, simulation-based EHR learning activity on the intern data gathering workflow and satisfaction. A total of 72 internal medicine interns across the 2018 and 2019 academic years underwent a dedicated EHR training session as part of a week-long boot camp early in their training. We collected data on previous EHR and ICU experience for all subjects. Training consisted of 1 hour of guided review of a high-fidelity, simulated ICU patient chart focusing on best navigation practices for data retrieval. Specifically, the activity focused on using high- and low-yield data visualization screens determined by expert consensus. The intervention group interns then had 20 minutes to review a new simulated patient chart before the group review. EHR screen navigation was captured using screen recording software and compared with data from existing ICU residents performing the same task on the same medical charts (N=62). Learners were surveyed immediately and 6 months after the activity to assess satisfaction and preferred EHR screen use. Participants found the activity useful and enjoyable immediately and after 6 months. Intervention interns used more individual screens than reference residents (18 vs 20; P=.008), but the total number of screens used was the same (35 vs 38; P=.30). Significantly more intervention interns used the 10 most common screens (73% vs 45%; P=.001). Intervention interns used high-yield screens more often and low-yield screens less often than the reference residents, which are persistent on self-report 6 months later. A short, high-fidelity, simulation-based learning activity focused on provider-specific data gathering was found to be enjoyable and to modify navigation patterns persistently. This suggests that workflow-specific simulation-based EHR training throughout training is of educational benefit to residents.

Sections du résumé

BACKGROUND BACKGROUND
Accurate data retrieval is an essential part of patient care in the intensive care unit (ICU). The electronic health record (EHR) is the primary method for data storage and data review. We previously reported that residents participating in EHR-based simulations have varied and nonstandard approaches to finding data in the ICU, with subsequent errors in recognizing patient safety issues. We hypothesized that a novel EHR simulation-based training exercise would decrease EHR use variability among intervention interns, irrespective of prior EHR experience.
OBJECTIVE OBJECTIVE
This study aims to understand the impact of a novel, short, high-fidelity, simulation-based EHR learning activity on the intern data gathering workflow and satisfaction.
METHODS METHODS
A total of 72 internal medicine interns across the 2018 and 2019 academic years underwent a dedicated EHR training session as part of a week-long boot camp early in their training. We collected data on previous EHR and ICU experience for all subjects. Training consisted of 1 hour of guided review of a high-fidelity, simulated ICU patient chart focusing on best navigation practices for data retrieval. Specifically, the activity focused on using high- and low-yield data visualization screens determined by expert consensus. The intervention group interns then had 20 minutes to review a new simulated patient chart before the group review. EHR screen navigation was captured using screen recording software and compared with data from existing ICU residents performing the same task on the same medical charts (N=62). Learners were surveyed immediately and 6 months after the activity to assess satisfaction and preferred EHR screen use.
RESULTS RESULTS
Participants found the activity useful and enjoyable immediately and after 6 months. Intervention interns used more individual screens than reference residents (18 vs 20; P=.008), but the total number of screens used was the same (35 vs 38; P=.30). Significantly more intervention interns used the 10 most common screens (73% vs 45%; P=.001). Intervention interns used high-yield screens more often and low-yield screens less often than the reference residents, which are persistent on self-report 6 months later.
CONCLUSIONS CONCLUSIONS
A short, high-fidelity, simulation-based learning activity focused on provider-specific data gathering was found to be enjoyable and to modify navigation patterns persistently. This suggests that workflow-specific simulation-based EHR training throughout training is of educational benefit to residents.

Identifiants

pubmed: 33687339
pii: v7i1e25828
doi: 10.2196/25828
pmc: PMC8081274
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e25828

Subventions

Organisme : AHRQ HHS
ID : R01 HS023793
Pays : United States
Organisme : AHRQ HHS
ID : R18 HS021637
Pays : United States

Informations de copyright

©Matthew E Miller, Gretchen Scholl, Sky Corby, Vishnu Mohan, Jeffrey A Gold. Originally published in JMIR Medical Education (http://mededu.jmir.org), 09.03.2021.

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Auteurs

Matthew E Miller (ME)

Division of Pulmonary and Critical Care Medicine, Oregon Health & Science University, Portland, OR, United States.

Gretchen Scholl (G)

Department of Medical Informatics, Oregon Health & Science University, Portland, OR, United States.

Sky Corby (S)

Division of Pulmonary and Critical Care Medicine, Oregon Health & Science University, Portland, OR, United States.

Vishnu Mohan (V)

Department of Medical Informatics, Oregon Health & Science University, Portland, OR, United States.

Jeffrey A Gold (JA)

Division of Pulmonary and Critical Care Medicine, Oregon Health & Science University, Portland, OR, United States.

Classifications MeSH