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Transparency in Admissions and Personalized Learning Through Resident Patient Selection

Background: Adult learning (andragogy) posits that adult learners have an improved educational experience when engaged in self-directed learning. The decision to allocate patients to the teaching service vs a nonresident service varies according to institution. Previously, our institution focused on...

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Autores principales: Archibald, Andrea, Zimmerman, Paul, Seay, Winn, Verma, Lalit, Wilson, Jonathan, Sharma, Poonam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Division of Ochsner Clinic Foundation 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8929219/
https://www.ncbi.nlm.nih.gov/pubmed/35355634
http://dx.doi.org/10.31486/toj.21.0066
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author Archibald, Andrea
Zimmerman, Paul
Seay, Winn
Verma, Lalit
Wilson, Jonathan
Sharma, Poonam
author_facet Archibald, Andrea
Zimmerman, Paul
Seay, Winn
Verma, Lalit
Wilson, Jonathan
Sharma, Poonam
author_sort Archibald, Andrea
collection PubMed
description Background: Adult learning (andragogy) posits that adult learners have an improved educational experience when engaged in self-directed learning. The decision to allocate patients to the teaching service vs a nonresident service varies according to institution. Previously, our institution focused on faculty perception of learning value as the deciding factor in patient assignment. We hypothesized that transitioning to a process in which adult learners (residents) select patients for their teams based on their own identified learning needs could improve the educational experience without adversely impacting the workflow for nonteaching teams. Methods: A new patient assignment model focused on learner-driven identification of patients for their own inpatient service, consistent with the principle of andragogy, was created. This patient assignment strategy was tested during a 1-month pilot period followed by a 5-month implementation period with 20 senior residents and 31 hospitalists. Both residents and hospitalists were surveyed after the intervention. Results: Sixteen of 20 residents completed the paper survey, and 100% of the respondents indicated “yes” when asked if they were able to direct cases to their team that were in line with their learning goals and if the new process should continue. Twenty-one of 31 hospitalists responded to the electronic survey; 81% of responding hospitalists reported a slightly positive to very positive impact on the hospitalist workflow, and 76% felt the new process should continue. The new patient assignment model had no negative impact on case mix index or length of stay. Conclusion: Restructuring patient assignment processes based on educational theory may improve resident education and improve hospitalist workflow.
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spelling pubmed-89292192022-03-29 Transparency in Admissions and Personalized Learning Through Resident Patient Selection Archibald, Andrea Zimmerman, Paul Seay, Winn Verma, Lalit Wilson, Jonathan Sharma, Poonam Ochsner J Original Research Background: Adult learning (andragogy) posits that adult learners have an improved educational experience when engaged in self-directed learning. The decision to allocate patients to the teaching service vs a nonresident service varies according to institution. Previously, our institution focused on faculty perception of learning value as the deciding factor in patient assignment. We hypothesized that transitioning to a process in which adult learners (residents) select patients for their teams based on their own identified learning needs could improve the educational experience without adversely impacting the workflow for nonteaching teams. Methods: A new patient assignment model focused on learner-driven identification of patients for their own inpatient service, consistent with the principle of andragogy, was created. This patient assignment strategy was tested during a 1-month pilot period followed by a 5-month implementation period with 20 senior residents and 31 hospitalists. Both residents and hospitalists were surveyed after the intervention. Results: Sixteen of 20 residents completed the paper survey, and 100% of the respondents indicated “yes” when asked if they were able to direct cases to their team that were in line with their learning goals and if the new process should continue. Twenty-one of 31 hospitalists responded to the electronic survey; 81% of responding hospitalists reported a slightly positive to very positive impact on the hospitalist workflow, and 76% felt the new process should continue. The new patient assignment model had no negative impact on case mix index or length of stay. Conclusion: Restructuring patient assignment processes based on educational theory may improve resident education and improve hospitalist workflow. Academic Division of Ochsner Clinic Foundation 2022 2022 /pmc/articles/PMC8929219/ /pubmed/35355634 http://dx.doi.org/10.31486/toj.21.0066 Text en ©2022 by the author(s); Creative Commons Attribution License (CC BY) https://creativecommons.org/licenses/by/4.0/©2022 by the author(s); licensee Ochsner Journal, Ochsner Clinic Foundation, New Orleans, LA. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (creativecommons.org/licenses/by/4.0/legalcode) that permits unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
spellingShingle Original Research
Archibald, Andrea
Zimmerman, Paul
Seay, Winn
Verma, Lalit
Wilson, Jonathan
Sharma, Poonam
Transparency in Admissions and Personalized Learning Through Resident Patient Selection
title Transparency in Admissions and Personalized Learning Through Resident Patient Selection
title_full Transparency in Admissions and Personalized Learning Through Resident Patient Selection
title_fullStr Transparency in Admissions and Personalized Learning Through Resident Patient Selection
title_full_unstemmed Transparency in Admissions and Personalized Learning Through Resident Patient Selection
title_short Transparency in Admissions and Personalized Learning Through Resident Patient Selection
title_sort transparency in admissions and personalized learning through resident patient selection
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8929219/
https://www.ncbi.nlm.nih.gov/pubmed/35355634
http://dx.doi.org/10.31486/toj.21.0066
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