Evidence map›Paper›PMID 34986760›Full record

ArticleMedical education online2022

Maximizing clinical rotation placements for US medical students: exploring an optimization model.

Gary L Beck Dallaghan, Xi Lin, J Kyle Melvin, Julie Golding, Beat Steiner, Vidyadhar Kulkarni

Abstract read
In one paragraph

Article in Medical education online, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Gary L Beck DallaghanSchool of Medicine, University of North Carolina, Chapel Hill, NC, USA.ORCID 0000-0002-8539-6969
Xi LinOperations and Decision Technologies, The University of California-Irvine Paul Merage School of Business, Irvine, CA, USA.
J Kyle MelvinThe Department of Family and Community Medicine, UNC Primary Care, Siler City, NC, USA.
Julie GoldingAcademic Affairs for Application Phase, School of Medicine, University of North Carolina, Chapel Hill, NC, USA.
Beat SteinerSchool of Medicine, University of North Carolina, Chapel Hill, NC, USA.ORCID 0000-0002-4569-3547
Vidyadhar KulkarniStatistics and Operations Research, University of North Carolina, Chapel Hill, NC, USA.

Funding

Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
NCATS NIH HHS UL1 TR002489
6 · The paper itself

Abstract

backgroundFor years, US medical schools have relied on community-based, private clinicians to educate medical students. There has been a steady decline in the number of physicians willing to take on medical students in their clinical practices. Recent issues related to the pandemic raise questions about how many patients students should see to have a meaningful clinical experience.

methodsAs part of a 16-week longitudinal clinical experience, medical students spend 2 days each week in a family medicine or internal medicine clinic. As repetition enhances learning, maximizing the number of patients students see is important. Using a mixed integer linear program, we sought to determine the optimal schedule that maximizes the number of patients whom students see during a rotation. Patient visits were collected from January to April 2018 for clinics used by the medical school. By maximizing the minimum number of patients per learner over all non-empty day-clinic combinations, we deliver equitable rotation plans based on our assumptions.

resultsFor this pilot study, multiple experiments were performed with different numbers of students assigned to clinics. Each experiment also generated a weekly rotation plan for a given student. Based on this optimization model, the minimum number of patients per student over 16 weeks was 87 (3 patients per day) and actually increased the number of students who could be assigned to one of the clinics from 1 student per rotation to 8 students.

conclusionsThe mixed integer linear program assigned more students to clinics that have more total visits in order to achieve the optimal and fairest learning quality. In addition, by conducting various experiments on different numbers of students, we observed that we were able to allocate more students without affecting the number of patients students see.

Indexed as

Students, MedicalHumansLearningPilot ProjectsSchools, Medicalclinician educatorMedical studentoperations researchoptimizing schedulespatient care

Identifiers

PMID34986760
PMCPMC8741226

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.