Mark Holmes, PhD, is a Professor in the Department of Health Policy and Management in the University of North Carolina Gillings School of Global Public Health and Director of the Cecil G. Sheps Center for Health Services Research, where he is also the Director of the North Carolina Rural Health Research and Policy Analysis Center and the Co-Director of the Program on Health Care Economics and Finance at the Cecil G. Sheps Center for Health Services Research. His interests include hospital finance, rural health, workforce, health policy, and patient-centered outcomes research. In 2014, he received the Phillip and Ruth Hettleman Prize for Artistic and Scholarly Achievement by Young Faculty. In 2015 he was named Outstanding Researcher by the National Rural Health Association. Previously, he was Vice President of the North Carolina Institute of Medicine, where he gained experience in North Carolina health policy. He previously served on the board of the North Carolina Health Insurance Risk Pool. His state policy work led to his 2010 Health Care Hero "Rising Star" award from the Triangle Business Journal. He is a member of the Editorial Boards of the Journal of Rural Health and the NCMJ.
Areas of Expertise (6)
Patient-Centered Outcome Research
Policy Implementation and Development
National Rural Health Association, 2015
Phillip and Ruth Hettleman Prize for Artistic and Scholarly Achievement by Young Faculty
40 Under 40 Leadership Award
Triangle Business Journal, 2012
Rising Star Award
Triangle Business Journal, 2010
Michigan State University: BS, Mathematics and Economics
University of North Carolina at Chapel Hill: PhD, Economics
Research Grants (6)
Rural Health Research Center Cooperative Agreement Program (PI: Holmes GM)
UNC-CH Training Program in Health Services Research (PI: Holmes GM)
AHRQ, 5 T32 HS000032
Medicare Rural Hospital Flexibility Program Evaluation (PI: Moscovice I)
HRSA, U27RH01080 (Subcontract with University of Minnesota)
North Carolina Clinical Genomic Evaluation By Next-Gen Exome Sequencing 2 (PI: Berg)
National Human Genome Research Institute, 2U01HG006487-05
University of North Carolina Women’s Interagency HIV Study (UNC WIHS) (PI: Adimora A)
National Human Genome Research Institute, 2U01HG006487-05
Rural Residency Planning and Development Technical Assistance Center (PI: Page)
Federal Office of Rural Health Policy, UK6RH32513
HPM 880 Principles of Health Policy Research Methods
First course in the department’s sequence in empirical analysis. Covers principles of statistical inference, univariate and bivariate analysis, statistical software applications, and mathematical concepts necessary for linear regression and further topics.
HPM 873 Policy Seminar in Health Policy and Management
Seminar on policy issues in Health Policy and Management
How can we improve health and health care in rural America?Carolina Public Health Magazine
Mark Holmes, PhD and George Pink, PhD
About 46 million people – 15 percent of the country’s population – live in rural America. Rural Americans produce most of our food, much of our energy – and they build strong, cooperative communities. However, they face many challenges when it comes to health and health care. Median income is lower in rural areas, and there’s more poverty. The population is also older and aging rapidly, which means that rural residents will require more health care over time.
Rural Health Care Costs Are They Higher and Why Might They Differ from Urban Health Care Costs?North Carolina Medical Journal, January 2018
Dunc Williams Jr, MHA, MTS and Mark Holmes, PhD
Do health care costs differ between rural and urban populations, and if so, why might that be? Rural Americans are more vulnerable than their urban counterparts, which could lead us to suspect rural health care costs are higher. However, the answer may differ depending on how costs are measured and who is paying.
Health Disparities in AppalachiaAppalachian Regional Commission, August 2017
Julie L. Marshall, Logan Thomas, Nancy M. Lane, G. Mark Holmes, Thomas A. Arcury, Randy Randolph, Pam Silberman, William Holding, Lisa Villamil, Sharita Thomas, Maura Lane, Janine Latus, Jonathan Rodgers, and Kelly Ivey PDA, Inc.; Cecil G. Sheps Center for Health Services Research; Appalachian Regional Commission
"Creating a Culture of Health in Appalachia: Disparities and Bright Spots" is an innovative research initiative sponsored by the Robert Wood Johnson Foundation (RWJF) and the Appalachian Regional Commission (ARC) and administered by the Foundation for a Healthy Kentucky. This multi-part health research project will, in successive reports: measure population health and document disparities in health outcomes in the Appalachian Region compared to the United States as a whole, as well as disparities within the Appalachian Region; identify “Bright Spots,” or communities that exhibit better-than-expected health outcomes given their resources; and explore a sample of the Bright Spot communities through in-depth, field-based case studies. Taken together, these reports will provide a basis for understanding and addressing health issues in the Appalachian Region. This research initiative aims to identify factors that support a culture of health in Appalachian communities and explore replicable activities, programs, or policies that encourage better-than-expected health outcomes that could translate into actions that other communities can replicate.
A Methodology for Using Workforce Data to Decide Which Specialties and States to Target for Graduate Medical Education ExpansionThe Evolving U.S. Health Workforce
Erin P. Fraher Ph.D., M.P.P. Andy Knapton M.Sc. George M. Holmes Ph.D.
Abstract Objective To outline a methodology for allocating graduate medical education (GME) training positions based on data from a workforce projection model. Data Sources Demand for visits is derived from the Medical Expenditure Panel Survey and Census data. Physician supply, retirements, and geographic mobility are estimated using concatenated AMA Masterfiles and ABMS certification data. The number and specialization behaviors of residents are derived from the AAMC's GMETrack survey. Design We show how the methodology could be used to allocate 3,000 new GME slots over 5 years—15,000 total positions—by state and specialty to address workforce shortages in 2026. Extraction Methods We use the model to identify shortages for 19 types of health care services provided by 35 specialties in 50 states. Principal Findings The new GME slots are allocated to nearly all specialties, but nine states and the District of Columbia do not receive any new positions. Conclusions This analysis illustrates an objective, evidence‐based methodology for allocating GME positions that could be used as the starting point for discussions about GME expansion or redistribution.
Developing Physician Migration Estimates for Workforce ModelsHealth Services Research
George M. Holmes, Ph.D. and Erin P. Fraher, Ph.D., M.P.P.
Objective To understand factors affecting specialty heterogeneity in physician migration. Data Sources/Study Setting Physicians in the 2009 American Medical Association Masterfile data were matched to those in the 2013 file. Office locations were geocoded in both years to one of 293 areas of the country. Estimated utilization, calculated for each specialty, was used as the primary predictor of migration. Physician characteristics (e.g., specialty, age, sex) were obtained from the 2009 file. Area characteristics and other factors influencing physician migration (e.g., rurality, presence of teaching hospital) were obtained from various sources. Study Design We modeled physician location decisions as a two‐part process: First, the physician decides whether to move. Second, conditional on moving, a conditional logit model estimates the probability a physician moved to a particular area. Separate models were estimated by specialty and whether the physician was a resident. Principal Findings Results differed between specialties and according to whether the physician was a resident in 2009, indicating heterogeneity in responsiveness to policies. Physician migration was higher between geographically proximate states with higher utilization for that specialty. Conclusions Models can be used to estimate specialty‐specific migration patterns for more accurate workforce modeling, including simulations to model the effect of policy changes.
To What Extent do Community Characteristics Explain Differences in Closure among Financially Distressed Rural Hospitals?Journal of Health Care Poor Underserved, 2016
Thomas SR, Holmes GM, Pink GH
Abstract From January 2005 through December 2015, 105 rural hospitals closed. This study examined associations between community characteristics and rural hospital closure. Compared with other rural hospitals that were at high risk of financial distress but remained open over the same time period, closed rural hospitals had a smaller market share (p < .0001) despite being in areas with higher population density (p < .05), were located nearer to another hospital (p < .0001), and were located in markets that had a higher rate of unemployment (p < .05) and a higher percentage of Black (p < .05) and Hispanic (p < .01) residents. These results have three implications for rural health policy: rural hospital closures may disproportionately affect racial and ethnic minorities, community characteristics in combination with other factors make it likely that rural hospital closures will continue, and rural hospital closures illuminate the need for new models of reimbursement and health care delivery to meet the needs of rural communities.
Capsule Commentary for Tsilimingras et al., Post- Discharge Adverse Events Among Urban and Rural Patients of an Urban Community Hospital: A Prospective Cohort StudyJournal of General Internal Medicine
Comment on Post-Discharge Adverse Events Among Urban and Rural Patients of an Urban Community Hospital: A Prospective Cohort Study