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Learning optimal opioid prescribing and monitoring: a simulation study of medical residents

OBJECTIVE: Hospitalized patients often receive opioids. There is a lack of consensus regarding evidence-based guidelines or training programs for effective management of pain in the hospital. We investigated the viability of using an Internet-based opioid dosing simulator to teach residents appropri...

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Autores principales: Kannampallil, Thomas G, McNutt, Robert, Falck, Suzanne, Galanter, William L, Patterson, Dave, Darabi, Houshang, Sharabiani, Ashkan, Schiff, Gordon, Odwazny, Richard, Vaida, Allen J, Wilkie, Diana J, Lambert, Bruce L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6951957/
https://www.ncbi.nlm.nih.gov/pubmed/31984336
http://dx.doi.org/10.1093/jamiaopen/ooy026
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author Kannampallil, Thomas G
McNutt, Robert
Falck, Suzanne
Galanter, William L
Patterson, Dave
Darabi, Houshang
Sharabiani, Ashkan
Schiff, Gordon
Odwazny, Richard
Vaida, Allen J
Wilkie, Diana J
Lambert, Bruce L
author_facet Kannampallil, Thomas G
McNutt, Robert
Falck, Suzanne
Galanter, William L
Patterson, Dave
Darabi, Houshang
Sharabiani, Ashkan
Schiff, Gordon
Odwazny, Richard
Vaida, Allen J
Wilkie, Diana J
Lambert, Bruce L
author_sort Kannampallil, Thomas G
collection PubMed
description OBJECTIVE: Hospitalized patients often receive opioids. There is a lack of consensus regarding evidence-based guidelines or training programs for effective management of pain in the hospital. We investigated the viability of using an Internet-based opioid dosing simulator to teach residents appropriate use of opioids to treat and manage acute pain. MATERIALS AND METHODS: We used a prospective, longitudinal design to evaluate the effects of simulator training. In face-to-face didactic sessions, we taught 120 (108 internal medicine and 12 family medicine) residents principles of pain management and how to use the simulator. Each trainee completed 10 training and, subsequently, 5 testing trials on the simulator. For each trial, we collected medications, doses, routes and times of administration, pain scores, and a summary score. We used mixed-effects regression models to assess the impact of simulation training on simulation performance scores, variability in pain score trajectories, appropriate use of short- and long-acting opioids, and use of naloxone. RESULTS: Trainees completed 1582 simulation trials (M = 13.2, SD = 6.8), with sustained improvements in their simulated pain management practices. Over time, trainees improved their overall simulated pain management scores (b = 0.05, P < .01), generated lower pain score trajectories with less variability (b = −0.02, P < .01), switched more rapidly from short-acting to long-acting agents (b = −0.50, P < .01), and used naloxone less often (b = −0.10, P < .01). DISCUSSION AND CONCLUSIONS: Trainees translated their understanding of didactically presented principles of pain management to their performance on simulated patient cases. Simulation-based training presents an opportunity for improving opioid-based inpatient acute pain management.
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spelling pubmed-69519572020-01-24 Learning optimal opioid prescribing and monitoring: a simulation study of medical residents Kannampallil, Thomas G McNutt, Robert Falck, Suzanne Galanter, William L Patterson, Dave Darabi, Houshang Sharabiani, Ashkan Schiff, Gordon Odwazny, Richard Vaida, Allen J Wilkie, Diana J Lambert, Bruce L JAMIA Open Research and Applications OBJECTIVE: Hospitalized patients often receive opioids. There is a lack of consensus regarding evidence-based guidelines or training programs for effective management of pain in the hospital. We investigated the viability of using an Internet-based opioid dosing simulator to teach residents appropriate use of opioids to treat and manage acute pain. MATERIALS AND METHODS: We used a prospective, longitudinal design to evaluate the effects of simulator training. In face-to-face didactic sessions, we taught 120 (108 internal medicine and 12 family medicine) residents principles of pain management and how to use the simulator. Each trainee completed 10 training and, subsequently, 5 testing trials on the simulator. For each trial, we collected medications, doses, routes and times of administration, pain scores, and a summary score. We used mixed-effects regression models to assess the impact of simulation training on simulation performance scores, variability in pain score trajectories, appropriate use of short- and long-acting opioids, and use of naloxone. RESULTS: Trainees completed 1582 simulation trials (M = 13.2, SD = 6.8), with sustained improvements in their simulated pain management practices. Over time, trainees improved their overall simulated pain management scores (b = 0.05, P < .01), generated lower pain score trajectories with less variability (b = −0.02, P < .01), switched more rapidly from short-acting to long-acting agents (b = −0.50, P < .01), and used naloxone less often (b = −0.10, P < .01). DISCUSSION AND CONCLUSIONS: Trainees translated their understanding of didactically presented principles of pain management to their performance on simulated patient cases. Simulation-based training presents an opportunity for improving opioid-based inpatient acute pain management. Oxford University Press 2018-06-27 /pmc/articles/PMC6951957/ /pubmed/31984336 http://dx.doi.org/10.1093/jamiaopen/ooy026 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of the American Medical Informatics Association. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Research and Applications
Kannampallil, Thomas G
McNutt, Robert
Falck, Suzanne
Galanter, William L
Patterson, Dave
Darabi, Houshang
Sharabiani, Ashkan
Schiff, Gordon
Odwazny, Richard
Vaida, Allen J
Wilkie, Diana J
Lambert, Bruce L
Learning optimal opioid prescribing and monitoring: a simulation study of medical residents
title Learning optimal opioid prescribing and monitoring: a simulation study of medical residents
title_full Learning optimal opioid prescribing and monitoring: a simulation study of medical residents
title_fullStr Learning optimal opioid prescribing and monitoring: a simulation study of medical residents
title_full_unstemmed Learning optimal opioid prescribing and monitoring: a simulation study of medical residents
title_short Learning optimal opioid prescribing and monitoring: a simulation study of medical residents
title_sort learning optimal opioid prescribing and monitoring: a simulation study of medical residents
topic Research and Applications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6951957/
https://www.ncbi.nlm.nih.gov/pubmed/31984336
http://dx.doi.org/10.1093/jamiaopen/ooy026
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