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Habit and Automaticity in Medical Alert Override: Cohort Study

BACKGROUND: Prior literature suggests that alert dismissal could be linked to physicians’ habits and automaticity. The evidence for this perspective has been mainly observational data. This study uses log data from an electronic medical records system to empirically validate this perspective. OBJECT...

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Autores principales: Wang, Le, Goh, Kim Huat, Yeow, Adrian, Poh, Hermione, Li, Ke, Yeow, Joannas Jie Lin, Tan, Gamaliel, Soh, Christina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892274/
https://www.ncbi.nlm.nih.gov/pubmed/35171102
http://dx.doi.org/10.2196/23355
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author Wang, Le
Goh, Kim Huat
Yeow, Adrian
Poh, Hermione
Li, Ke
Yeow, Joannas Jie Lin
Tan, Gamaliel
Soh, Christina
author_facet Wang, Le
Goh, Kim Huat
Yeow, Adrian
Poh, Hermione
Li, Ke
Yeow, Joannas Jie Lin
Tan, Gamaliel
Soh, Christina
author_sort Wang, Le
collection PubMed
description BACKGROUND: Prior literature suggests that alert dismissal could be linked to physicians’ habits and automaticity. The evidence for this perspective has been mainly observational data. This study uses log data from an electronic medical records system to empirically validate this perspective. OBJECTIVE: We seek to quantify the association between habit and alert dismissal in physicians. METHODS: We conducted a retrospective analysis using the log data comprising 66,049 alerts generated from hospitalized patients in a hospital from March 2017 to December 2018. We analyzed 1152 physicians exposed to a specific clinical support alert triggered in a hospital’s electronic medical record system to estimate the extent to which the physicians’ habit strength, which had been developed from habitual learning, impacted their propensity toward alert dismissal. We further examined the association between a physician’s habit strength and their subsequent incidences of alert dismissal. Additionally, we recorded the time taken by the physician to respond to the alert and collected data on other clinical and environmental factors related to the alerts as covariates for the analysis. RESULTS: We found that a physician’s prior dismissal of alerts leads to their increased habit strength to dismiss alerts. Furthermore, a physician’s habit strength to dismiss alerts was found to be positively associated with incidences of subsequent alert dismissals after their initial alert dismissal. Alert dismissal due to habitual learning was also found to be pervasive across all physician ranks, from junior interns to senior attending specialists. Further, the dismissal of alerts had been observed to typically occur after a very short processing time. Our study found that 72.5% of alerts were dismissed in under 3 seconds after the alert appeared, and 13.2% of all alerts were dismissed in under 1 second after the alert appeared. We found empirical support that habitual dismissal is one of the key factors associated with alert dismissal. We also found that habitual dismissal of alerts is self-reinforcing, which suggests significant challenges in disrupting or changing alert dismissal habits once they are formed. CONCLUSIONS: Habitual tendencies are associated with the dismissal of alerts. This relationship is pervasive across all levels of physician rank and experience, and the effect is self-reinforcing.
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spelling pubmed-88922742022-03-10 Habit and Automaticity in Medical Alert Override: Cohort Study Wang, Le Goh, Kim Huat Yeow, Adrian Poh, Hermione Li, Ke Yeow, Joannas Jie Lin Tan, Gamaliel Soh, Christina J Med Internet Res Original Paper BACKGROUND: Prior literature suggests that alert dismissal could be linked to physicians’ habits and automaticity. The evidence for this perspective has been mainly observational data. This study uses log data from an electronic medical records system to empirically validate this perspective. OBJECTIVE: We seek to quantify the association between habit and alert dismissal in physicians. METHODS: We conducted a retrospective analysis using the log data comprising 66,049 alerts generated from hospitalized patients in a hospital from March 2017 to December 2018. We analyzed 1152 physicians exposed to a specific clinical support alert triggered in a hospital’s electronic medical record system to estimate the extent to which the physicians’ habit strength, which had been developed from habitual learning, impacted their propensity toward alert dismissal. We further examined the association between a physician’s habit strength and their subsequent incidences of alert dismissal. Additionally, we recorded the time taken by the physician to respond to the alert and collected data on other clinical and environmental factors related to the alerts as covariates for the analysis. RESULTS: We found that a physician’s prior dismissal of alerts leads to their increased habit strength to dismiss alerts. Furthermore, a physician’s habit strength to dismiss alerts was found to be positively associated with incidences of subsequent alert dismissals after their initial alert dismissal. Alert dismissal due to habitual learning was also found to be pervasive across all physician ranks, from junior interns to senior attending specialists. Further, the dismissal of alerts had been observed to typically occur after a very short processing time. Our study found that 72.5% of alerts were dismissed in under 3 seconds after the alert appeared, and 13.2% of all alerts were dismissed in under 1 second after the alert appeared. We found empirical support that habitual dismissal is one of the key factors associated with alert dismissal. We also found that habitual dismissal of alerts is self-reinforcing, which suggests significant challenges in disrupting or changing alert dismissal habits once they are formed. CONCLUSIONS: Habitual tendencies are associated with the dismissal of alerts. This relationship is pervasive across all levels of physician rank and experience, and the effect is self-reinforcing. JMIR Publications 2022-02-16 /pmc/articles/PMC8892274/ /pubmed/35171102 http://dx.doi.org/10.2196/23355 Text en ©Le Wang, Kim Huat Goh, Adrian Yeow, Hermione Poh, Ke Li, Joannas Jie Lin Yeow, Gamaliel Tan, Christina Soh. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 16.02.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Wang, Le
Goh, Kim Huat
Yeow, Adrian
Poh, Hermione
Li, Ke
Yeow, Joannas Jie Lin
Tan, Gamaliel
Soh, Christina
Habit and Automaticity in Medical Alert Override: Cohort Study
title Habit and Automaticity in Medical Alert Override: Cohort Study
title_full Habit and Automaticity in Medical Alert Override: Cohort Study
title_fullStr Habit and Automaticity in Medical Alert Override: Cohort Study
title_full_unstemmed Habit and Automaticity in Medical Alert Override: Cohort Study
title_short Habit and Automaticity in Medical Alert Override: Cohort Study
title_sort habit and automaticity in medical alert override: cohort study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892274/
https://www.ncbi.nlm.nih.gov/pubmed/35171102
http://dx.doi.org/10.2196/23355
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