The Effect of a Community-Based Medical School on the State and Local Physician Workforce

Relationship Between Residency Match Distance From Medical School and Virtual Application, School Characteristics, and Specialty Competitiveness

INTRODUCTION

The COVID-19 pandemic has disrupted the residency match process by eliminating away rotations and changing from in-person to virtual interviews. In this study, we explore the impact of the COVID-19 pandemic on the geographic match distance of United States (US) senior medical students across all specialties.

METHODS

We collected publicly available student match data between 2018 and 2021 from US allopathic medical schools and calculated match distance between medical school and residency training using a novel metric - the "match space." Match space was codified by whether the student matched at their home institution, home state, adjacent state, same or adjacent US census division (non-adjacent state) or skipped at least one US census division. Adjusting for covariates, ordinal logistic regression correlated school and specialty characteristics with match distance pre- and post-pandemic for all specialties. We defined and ranked specialty competitiveness using predictive values from factor analysis.

RESULTS

A total of 34,672 students representing 66 medical schools from 28 states matched into 26 specialties in 50 states and Canada. Fifty-nine percent of students were from public institutions, and 27% of schools ranked in the top 40 for research. The mean percentage of in-state students by school was 60.3% (range 3-100%). Match space was lower after the pandemic (adjusted odds ratio (OR) 0.94, 95% CI 0.90-0.98; p=0.006), from schools with higher in-state percentages (OR 0.74, 95% CI 0.72-0.76), from top National Institutes of Health-funded institutions (OR 0.88, 95% CI 0.85-0.92), from the Northeast (OR 0.71, 95% CI 0.67-0.75; Midwest reference), and the West (OR 0.67, 95% 0.60-0.74). Match space was higher for students graduating from private schools (OR 1.11, 95% CI 1.05-1.19), from the South (OR 1.62, 95% CI 1.2-1.33), and matching into more competitive specialties (OR 1.08, 95% CI 1.02-1.14). The top five most competitive specialties were Plastic Surgery, Neurosurgery, Dermatology, Orthopedic Surgery, and Otolaryngology. Internal Medicine ranked eighth.

CONCLUSIONS

After the COVID-19 pandemic, students graduating from US allopathic schools matched closer to their home institution. Students attending public schools, schools with more in-state matriculants, and schools with higher research rankings also matched closer to their home institutions. Specialty competitiveness and US census region also impacted match distance. Our study adds insight into how geographic match patterns were influenced by school, specialty choice, and the pandemic.

Medical education interventions influencing physician distribution into underserved communities: a scoping review

BACKGROUND AND OBJECTIVE

Physician maldistribution is a global problem that hinders patients' abilities to access healthcare services. Medical education presents an opportunity to influence physicians towards meeting the healthcare needs of underserved communities when establishing their practice. Understanding the impact of educational interventions designed to offset physician maldistribution is crucial to informing health human resource strategies aimed at ensuring that the disposition of the physician workforce best serves the diverse needs of all patients and communities.

METHODS

A scoping review was conducted using a six-stage framework to help map current evidence on educational interventions designed to influence physicians' decisions or intention to establish practice in underserved areas. A search strategy was developed and used to conduct database searches. Data were synthesized according to the types of interventions and the location in the medical education professional development trajectory, that influence physician intention or decision for rural and underserved practice locations.

RESULTS

There were 130 articles included in the review, categorized according to four categories: preferential admissions criteria, undergraduate training in underserved areas, postgraduate training in underserved areas, and financial incentives. A fifth category was constructed to reflect initiatives comprised of various combinations of these four interventions. Most studies demonstrated a positive impact on practice location, suggesting that selecting students from underserved or rural areas, requiring them to attend rural campuses, and/or participate in rural clerkships or rotations are influential in distributing physicians in underserved or rural locations. However, these studies may be confounded by various factors including rural origin, pre-existing interest in rural practice, and lifestyle. Articles also had various limitations including self-selection bias, and a lack of standard definition for underservedness.

CONCLUSIONS

Various educational interventions can influence physician practice location: preferential admissions criteria, rural experiences during undergraduate and postgraduate medical training, and financial incentives. Educators and policymakers should consider the social identity, preferences, and motivations of aspiring physicians as they have considerable impact on the effectiveness of education initiatives designed to influence physician distribution in underserved locations.

Rurality and Origin-Destination Trajectories of Medical School Application and Matriculation in the United States

Physician shortages are more pronounced in rural than in urban areas. The geography of medical school application and matriculation could provide insights into geographic differences in physician availability. Using data from the Association of American Medical Colleges (AAMC), we conducted geospatial analyses, and developed origin-destination (O-D) trajectories and conceptual graphs to understand the root cause of rural physician shortages. Geographic disparities exist at a significant level in medical school applications in the US. The total number of medical school applications increased by 38% from 2001 to 2015, but the number had decreased by 2% in completely rural counties. Most counties with no medical school applicants were in rural areas (88%). Rurality had a significant negative association with the application rate and explained 15.3% of the variation at the county level. The number of medical school applications in a county was disproportional to the population by rurality. Applicants from completely rural counties (2% of the US population) represented less than 1% of the total medical school applications. Our results can inform recruitment strategies for new medical school students, elucidate location decisions of new medical schools, provide recommendations to close the rural-urban gap in medical school applications, and reduce physician shortages in rural areas.

Are Michigan State University medical school (MSU-CHM) alumni more likely to practice in the region of their graduate medical education primary care program compared to non-MSU-CHM alumni?

BACKGROUND

Over the past 10 years, three new MD schools have been created in the state of Michigan, while the Michigan State University College of Human Medicine (MSU-CHM) has increased their class size to 850 students. The aim of this study was to determine if MSU-CHM alumni who graduate from an MSU-affiliated primary care residency from a single graduate medical education (GME) training program in Michigan are more likely to go on to practice in close proximity to the location of their training program immediately after graduation compared to non MSU-CHM alumni. Changes over time in the proportion of primary care graduates who received fellowship training immediately following residency were also compared between these groups.

METHODS

A review of historical data was performed for all 2000-2016 primary care (Family Medicine, FM; Internal Medicine, IM; Internal Medicine-Pediatrics, IMP; Pediatrics, Peds) program graduates sponsored by Grand Rapids Medical Education Partners (GRMEP). Study variables included primary care program, gender, age at graduation, fellowship training, practice location immediately after graduation and undergraduate medical education location. Summary statistics were calculated for the data. Comparisons were made using the chi-square test or Fisher's Exact test when appropriate. Significance was assessed at p < 0.05.

RESULTS

There were 478 primary care program graduates who went into practice immediately following graduation, 102 of whom also graduated from MSU-CHM. Just over half of the graduates were female and the average age at graduation was 32 years. There were 152 FM, 150 IM, 50 IMP and 126 Peds graduates. Those that graduated from both MSU-CHM and GRMEP were more likely to practice in Michigan immediately after residency training (79.4% vs 52.0%; p < 0.001), as well as within 100 miles of GRMEP (71.6% vs 46.4%; p < 0.001). There were 8% of MSU-CHM primary care graduates who went on to fellowship training from 2000 to 2009, increasing to 34% from 2010 to 2016 (p < 0.001).

CONCLUSION

Medical school graduates of MSU-CHM who receive GME training in primary care are more likely to practice medicine within close proximity to their training site than non MSU-CHM graduates. However, plans for fellowship after training may add one caveat to this finding.