Implementation of an automated scheduling tool improves schedule quality and resident satisfaction.

Rotation schedules for residents must balance individual preferences, compliance with Accreditation Council for Graduate Medical Education guidelines, and institutional staffing requirements. Automation has the potential to improve the consistency and quality of schedules. We designed a novel rotati...

Full description

Bibliographic Details
Main Authors: Frederick M Howard, Catherine A Gao, Christopher Sankey
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0236952
_version_ 1818986496314572800
author Frederick M Howard
Catherine A Gao
Christopher Sankey
author_facet Frederick M Howard
Catherine A Gao
Christopher Sankey
author_sort Frederick M Howard
collection DOAJ
description Rotation schedules for residents must balance individual preferences, compliance with Accreditation Council for Graduate Medical Education guidelines, and institutional staffing requirements. Automation has the potential to improve the consistency and quality of schedules. We designed a novel rotation scheduling tool, the Automated Internal Medicine Scheduler (AIMS), and evaluated schedule quality and resident satisfaction and perceptions of fairness after implementation. We compared schedule uniformity, fulfillment of resident preferences, and conflicting shift assignments for the hand-made 2017-2018 schedule, and the AIMS-generated 2018-2019 schedule. Residents were surveyed in September 2018 to assess perception of schedule quality and fairness. With AIMS, 71/74 (96.0%) interns and 66/82 (80.5%) residents were assigned to their first-choice rotation, a significant increase from the 50/72 (69.4%) interns and 25/82 (30.5%) residents assigned their first-choice in the 2017-2018 academic year. AIMS also yielded significant improvements in the number of night shift/day shift conflicts at the time of rotation switches for interns, with a significant decrease to 0.3 conflicts per intern compared to 0.7 with the prior manual schedule. Twenty-two of 82 residents (27%) completed the survey, and average satisfaction and perception of fairness were 0.7 and 0.9 points higher on a 5-point Likert scale for the AIMS-generated schedule when compared to the non-AIMS schedule. There was no significant difference in the preference for assigned vacation blocks, or in variance for night or ICU rotations. Automated scheduling improved several metrics of schedule quality, as well as resident satisfaction. Future directions include evaluation of the tool in other residency programs and comparison with alternative scheduling algorithms.
first_indexed 2024-12-20T18:51:43Z
format Article
id doaj.art-b459c24b0d654531ab7de445ea9b068f
institution Directory Open Access Journal
issn 1932-6203
language English
last_indexed 2024-12-20T18:51:43Z
publishDate 2020-01-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS ONE
spelling doaj.art-b459c24b0d654531ab7de445ea9b068f2022-12-21T19:29:35ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01158e023695210.1371/journal.pone.0236952Implementation of an automated scheduling tool improves schedule quality and resident satisfaction.Frederick M HowardCatherine A GaoChristopher SankeyRotation schedules for residents must balance individual preferences, compliance with Accreditation Council for Graduate Medical Education guidelines, and institutional staffing requirements. Automation has the potential to improve the consistency and quality of schedules. We designed a novel rotation scheduling tool, the Automated Internal Medicine Scheduler (AIMS), and evaluated schedule quality and resident satisfaction and perceptions of fairness after implementation. We compared schedule uniformity, fulfillment of resident preferences, and conflicting shift assignments for the hand-made 2017-2018 schedule, and the AIMS-generated 2018-2019 schedule. Residents were surveyed in September 2018 to assess perception of schedule quality and fairness. With AIMS, 71/74 (96.0%) interns and 66/82 (80.5%) residents were assigned to their first-choice rotation, a significant increase from the 50/72 (69.4%) interns and 25/82 (30.5%) residents assigned their first-choice in the 2017-2018 academic year. AIMS also yielded significant improvements in the number of night shift/day shift conflicts at the time of rotation switches for interns, with a significant decrease to 0.3 conflicts per intern compared to 0.7 with the prior manual schedule. Twenty-two of 82 residents (27%) completed the survey, and average satisfaction and perception of fairness were 0.7 and 0.9 points higher on a 5-point Likert scale for the AIMS-generated schedule when compared to the non-AIMS schedule. There was no significant difference in the preference for assigned vacation blocks, or in variance for night or ICU rotations. Automated scheduling improved several metrics of schedule quality, as well as resident satisfaction. Future directions include evaluation of the tool in other residency programs and comparison with alternative scheduling algorithms.https://doi.org/10.1371/journal.pone.0236952
spellingShingle Frederick M Howard
Catherine A Gao
Christopher Sankey
Implementation of an automated scheduling tool improves schedule quality and resident satisfaction.
PLoS ONE
title Implementation of an automated scheduling tool improves schedule quality and resident satisfaction.
title_full Implementation of an automated scheduling tool improves schedule quality and resident satisfaction.
title_fullStr Implementation of an automated scheduling tool improves schedule quality and resident satisfaction.
title_full_unstemmed Implementation of an automated scheduling tool improves schedule quality and resident satisfaction.
title_short Implementation of an automated scheduling tool improves schedule quality and resident satisfaction.
title_sort implementation of an automated scheduling tool improves schedule quality and resident satisfaction
url https://doi.org/10.1371/journal.pone.0236952
work_keys_str_mv AT frederickmhoward implementationofanautomatedschedulingtoolimprovesschedulequalityandresidentsatisfaction
AT catherineagao implementationofanautomatedschedulingtoolimprovesschedulequalityandresidentsatisfaction
AT christophersankey implementationofanautomatedschedulingtoolimprovesschedulequalityandresidentsatisfaction