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Related Experiment Video

Updated: Sep 15, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

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Published on: January 8, 2020

Objective Admissions Data and In-State Practice: What Can We Really Predict?

Marlene P Ballejos¹, Jamie Riera², Robert L Williams¹

¹Department of Family and Community Medicine, University of New Mexico School of Medicine, Albuquerque, NM.

Family Medicine

|July 15, 2025

Summary

This summary is machine-generated.

Objective applicant data has limited value in predicting future practice location for medical school graduates. Admissions committees should prioritize holistic review and consider subjective applicant information to address healthcare shortages.

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Area of Science:

Medical Education
Health Services Research
Medical School Admissions

Background:

Holistic review is widely adopted in medical school admissions.
Predicting future practice location remains a challenge for admissions committees.
Addressing regional healthcare shortages necessitates understanding practice location predictors.

Purpose of the Study:

To identify objective applicant attributes that predict future in-state practice location.
To evaluate the effectiveness of objective data in medical school admissions for workforce planning.

Main Methods:

Analysis of eight matriculant cohorts (2006-2013).
Univariate and multiple regression models used to link applicant data to practice location.
Objective data included demographics, academic metrics (MCAT, GPA), and geographic information.

Main Results:

41.7% of graduates practiced in-state.
In-state practitioners were older, more likely to be underrepresented in medicine, from urban high schools, attended in-state colleges, and had lower MCAT scores.
Age, urban high school origin, and MCAT score were significant predictors (R²=0.064).

Conclusions:

Objective applicant data has limited predictive value for future in-state practice.
Holistic review and subjective applicant data are crucial for predicting practice location.
Further research is needed to identify valuable subjective predictors.