Impact of medical student origins on the likelihood of ultimately practicing in areas of low vs high socio-economic status

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Abstract

Introduction: Medical schools are in general over-represented by students from high socio-economic status backgrounds. The University of Western Australia Medical School has been progressively widening the participation of students from a broader spectrum of the community both through expanded selection criteria and quota-based approaches for students of rural, indigenous and other socio-educationally disadvantaged backgrounds. We proposed that medical students entering medical school from such backgrounds would ultimately be more likely to practice in areas of increased socio-economic disadvantage. Methods: The current practice address of 2829 medical students who commenced practice from 1980 to 2011 was ascertained from the Australian Health Practitioner Regulation Agency (AHPRA) Database. Logistic regression was utilised to determine the predictors of the likelihood of the current practice address being in the lower 8 socio-economic deciles versus the top 2 socio-economic deciles. Results: Those who were categorised in the lower 8 socio-economic deciles at entry to medical school had increased odds of a current practice address in the lower 8 socio-economic deciles 5 or more years after graduation (OR 2.05, 95% CI 1.72, 2.45, P <0.001). Other positive univariate predictors included age at medical degree completion (for those 25 years or older vs those 24 years or younger OR 1.53, 95% CI 1.27, 1.84, P <0.001), being female (OR 1.26, 95% CI 1.07, 1.48, P = 0.005) and having a general practice versus specialist qualification (OR 4.16, 95% CI 3.33, 5.19, P <0.001). Negative predictors included having attended an independent school vs a government school (OR 0.77, 95% CI 0.64, 0.92, P <0.001) or being originally from overseas vs being born in Oceania (OR 0.80, 95% CI 0.67, 0.96, P = 0.017). After adjustment for potential confounders in multivariate logistic regression, those in the lower 8 socio-economic deciles at entry to medical school still had increased odds of having a current practice address in the lower 8 socio-economic deciles (OR 1.63, 95% CI 1.34, 1.99, P <0.001). Conclusion: Widening participation in medical school to students from more diverse socio-educational backgrounds is likely to increase the distribution of the medical workforce to ultimate service across areas representative of a broader socio-economic spectrum.

LanguageEnglish
Article number1
JournalBMC Medical Education
Volume17
Issue number1
DOIs
Publication statusPublished - 5 Jan 2017

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Medical Students
medical student
Economics
Medical Schools
economics
school
Students
student
Logistic Models
Oceania
logistics
regression
Western Australia
participation
Vulnerable Populations
General Practice
overseas
Patient Selection
qualification
Databases

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@article{9f01b10cf9bf4de295c785b854158adc,
title = "Impact of medical student origins on the likelihood of ultimately practicing in areas of low vs high socio-economic status",
abstract = "Introduction: Medical schools are in general over-represented by students from high socio-economic status backgrounds. The University of Western Australia Medical School has been progressively widening the participation of students from a broader spectrum of the community both through expanded selection criteria and quota-based approaches for students of rural, indigenous and other socio-educationally disadvantaged backgrounds. We proposed that medical students entering medical school from such backgrounds would ultimately be more likely to practice in areas of increased socio-economic disadvantage. Methods: The current practice address of 2829 medical students who commenced practice from 1980 to 2011 was ascertained from the Australian Health Practitioner Regulation Agency (AHPRA) Database. Logistic regression was utilised to determine the predictors of the likelihood of the current practice address being in the lower 8 socio-economic deciles versus the top 2 socio-economic deciles. Results: Those who were categorised in the lower 8 socio-economic deciles at entry to medical school had increased odds of a current practice address in the lower 8 socio-economic deciles 5 or more years after graduation (OR 2.05, 95{\%} CI 1.72, 2.45, P <0.001). Other positive univariate predictors included age at medical degree completion (for those 25 years or older vs those 24 years or younger OR 1.53, 95{\%} CI 1.27, 1.84, P <0.001), being female (OR 1.26, 95{\%} CI 1.07, 1.48, P = 0.005) and having a general practice versus specialist qualification (OR 4.16, 95{\%} CI 3.33, 5.19, P <0.001). Negative predictors included having attended an independent school vs a government school (OR 0.77, 95{\%} CI 0.64, 0.92, P <0.001) or being originally from overseas vs being born in Oceania (OR 0.80, 95{\%} CI 0.67, 0.96, P = 0.017). After adjustment for potential confounders in multivariate logistic regression, those in the lower 8 socio-economic deciles at entry to medical school still had increased odds of having a current practice address in the lower 8 socio-economic deciles (OR 1.63, 95{\%} CI 1.34, 1.99, P <0.001). Conclusion: Widening participation in medical school to students from more diverse socio-educational backgrounds is likely to increase the distribution of the medical workforce to ultimate service across areas representative of a broader socio-economic spectrum.",
keywords = "Medical students, Medical workforce, Medically underserved areas, Socio-economic status, Widening access",
author = "Puddey, {Ian B.} and Playford, {Denese E.} and Annette Mercer",
year = "2017",
month = "1",
day = "5",
doi = "10.1186/s12909-016-0842-7",
language = "English",
volume = "17",
journal = "BMC Medical Education",
issn = "1472-6920",
publisher = "BioMed Central",
number = "1",

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TY - JOUR

T1 - Impact of medical student origins on the likelihood of ultimately practicing in areas of low vs high socio-economic status

AU - Puddey, Ian B.

AU - Playford, Denese E.

AU - Mercer, Annette

PY - 2017/1/5

Y1 - 2017/1/5

N2 - Introduction: Medical schools are in general over-represented by students from high socio-economic status backgrounds. The University of Western Australia Medical School has been progressively widening the participation of students from a broader spectrum of the community both through expanded selection criteria and quota-based approaches for students of rural, indigenous and other socio-educationally disadvantaged backgrounds. We proposed that medical students entering medical school from such backgrounds would ultimately be more likely to practice in areas of increased socio-economic disadvantage. Methods: The current practice address of 2829 medical students who commenced practice from 1980 to 2011 was ascertained from the Australian Health Practitioner Regulation Agency (AHPRA) Database. Logistic regression was utilised to determine the predictors of the likelihood of the current practice address being in the lower 8 socio-economic deciles versus the top 2 socio-economic deciles. Results: Those who were categorised in the lower 8 socio-economic deciles at entry to medical school had increased odds of a current practice address in the lower 8 socio-economic deciles 5 or more years after graduation (OR 2.05, 95% CI 1.72, 2.45, P <0.001). Other positive univariate predictors included age at medical degree completion (for those 25 years or older vs those 24 years or younger OR 1.53, 95% CI 1.27, 1.84, P <0.001), being female (OR 1.26, 95% CI 1.07, 1.48, P = 0.005) and having a general practice versus specialist qualification (OR 4.16, 95% CI 3.33, 5.19, P <0.001). Negative predictors included having attended an independent school vs a government school (OR 0.77, 95% CI 0.64, 0.92, P <0.001) or being originally from overseas vs being born in Oceania (OR 0.80, 95% CI 0.67, 0.96, P = 0.017). After adjustment for potential confounders in multivariate logistic regression, those in the lower 8 socio-economic deciles at entry to medical school still had increased odds of having a current practice address in the lower 8 socio-economic deciles (OR 1.63, 95% CI 1.34, 1.99, P <0.001). Conclusion: Widening participation in medical school to students from more diverse socio-educational backgrounds is likely to increase the distribution of the medical workforce to ultimate service across areas representative of a broader socio-economic spectrum.

AB - Introduction: Medical schools are in general over-represented by students from high socio-economic status backgrounds. The University of Western Australia Medical School has been progressively widening the participation of students from a broader spectrum of the community both through expanded selection criteria and quota-based approaches for students of rural, indigenous and other socio-educationally disadvantaged backgrounds. We proposed that medical students entering medical school from such backgrounds would ultimately be more likely to practice in areas of increased socio-economic disadvantage. Methods: The current practice address of 2829 medical students who commenced practice from 1980 to 2011 was ascertained from the Australian Health Practitioner Regulation Agency (AHPRA) Database. Logistic regression was utilised to determine the predictors of the likelihood of the current practice address being in the lower 8 socio-economic deciles versus the top 2 socio-economic deciles. Results: Those who were categorised in the lower 8 socio-economic deciles at entry to medical school had increased odds of a current practice address in the lower 8 socio-economic deciles 5 or more years after graduation (OR 2.05, 95% CI 1.72, 2.45, P <0.001). Other positive univariate predictors included age at medical degree completion (for those 25 years or older vs those 24 years or younger OR 1.53, 95% CI 1.27, 1.84, P <0.001), being female (OR 1.26, 95% CI 1.07, 1.48, P = 0.005) and having a general practice versus specialist qualification (OR 4.16, 95% CI 3.33, 5.19, P <0.001). Negative predictors included having attended an independent school vs a government school (OR 0.77, 95% CI 0.64, 0.92, P <0.001) or being originally from overseas vs being born in Oceania (OR 0.80, 95% CI 0.67, 0.96, P = 0.017). After adjustment for potential confounders in multivariate logistic regression, those in the lower 8 socio-economic deciles at entry to medical school still had increased odds of having a current practice address in the lower 8 socio-economic deciles (OR 1.63, 95% CI 1.34, 1.99, P <0.001). Conclusion: Widening participation in medical school to students from more diverse socio-educational backgrounds is likely to increase the distribution of the medical workforce to ultimate service across areas representative of a broader socio-economic spectrum.

KW - Medical students

KW - Medical workforce

KW - Medically underserved areas

KW - Socio-economic status

KW - Widening access

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U2 - 10.1186/s12909-016-0842-7

DO - 10.1186/s12909-016-0842-7

M3 - Article

VL - 17

JO - BMC Medical Education

T2 - BMC Medical Education

JF - BMC Medical Education

SN - 1472-6920

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