Hi, my name is Samuel Borgmanke, and I am a third year medical student at Ohio University Heritage College of Osteopathic Medicine, and this is my project on the implications of health care accessibility and patient outcomes. So a little background information. Unintentional injury, stroke, chronic lower respiratory disease, heart disease, and cancer have a higher prevalence in rural areas. Previous studies have also raised concern that a lower supply of physicians is associated with a higher mortality of these conditions. So what were the motivations that caused us to research this topic? Rural areas, particularly in Appalachia, experience disproportionate rates of preventable hospitalizations and mortality with significant disparities linked to socioeconomic status, geographic location, and limited health care access. Previous studies suggest a correlation between decreased physician density and higher mortality rates, but the effects of access to care, especially in rural Ohio, remain unexplored. We aimed in this project to analyze the relationship between quality of care, health care provider density, and the links in reducing preventable deaths with acute and chronic conditions in underserved communities. Our findings may help inform health care entities of the necessity of targeting improved primary and preventable care in rural regions. Ultimately, this project aims to address the health care workforce shortage and link it to the consequences of preventable mortality. So our research question was, how does the density of health care providers in rural Appalachian counties in Ohio correlate with the quality of preventable care and reducing mortality rates from chronic lower respiratory disease, heart disease, and diabetes? So this project used data sourced from the Centers for Medicare and Medicaid Services and the Mapping Medicare Disparities Tool. With this data, we conducted a NOVA test to compare the mean number of primary care physicians, specialty physicians, and other health care providers for Ohio counties. And this is broken down in Table 1, where we looked at the primary care physicians, the specialty physicians, and other health care providers. So primary care physicians are MDs or DOs that practiced in a primary care specialty, which we defined as family medicine, geriatrics, general internal medicine, pediatrics, and OB-GYN. Specialty physicians were MDs or DOs that were in any other specialty that was not included in the primary care physicians. Other health care providers were defined as health care providers that were not physicians. So nurse anesthetists, physician assistants, podiatrists, optometrists, PTs, OTs, chiropractors, registered dieticians, dentists, speech pathologists, etc. So these three categories were compared by mean provider rate. So the number of providers per 100,000 people in Ohio were calculated. And what we found was that there is a significant difference in the number of providers by category. So other health care providers, there are significantly more than primary care physicians or specialty physicians. In addition to just looking at these raw category numbers, we calculated the mean prevalence, principal costs, prevention quality indicator by health condition. We also analyzed the relationship between health care providers and the PQI across counties and examined differences in health care providers, disease burden, and quality of care between Appalachian and non-Appalachian regions. So PQI is defined as the total number of hospitalizations for a given condition per 100,000 persons by county for the year 2022. So what were the results? The mean number of providers per 100,000 people significantly differed by category, as we showed in Table 1. The prevalence of hypertension and diabetes were the highest of the selected conditions. So we selected conditions ranging from asthma, acute myocardial infarction, COPD, diabetes, hypertension. And what we found was that the prevalence of hypertension and diabetes were the highest of those selected conditions. In addition, the number of preventable hospitalizations for acute and chronic conditions was significantly different. For chronic conditions had way more higher hospitalizations than acute conditions. And this kind of lends itself to the idea that a lot of these hospitalizations are preventable. If patients had access to care for some of these chronic conditions, these hospitalizations may not have even occurred in the first place. And finally, when comparing Appalachian and non-Appalachian regions, this is seen in Table 2, there was a significant difference in the proportion of counties without specialist physicians. So Appalachian counties were underserved in certain specialties like cardiology, where patients may have to travel extended amounts of time. In order to have an appointment with a specialty physician, because they would not have one in their specific county. And Appalachian counties also had a significantly higher prevalence of acute MI, COPD, and diabetes. So not only did Appalachian counties not have access to care, they had higher rates of these health conditions. And conditions such as COPD and diabetes are chronic in nature, where patients need access to care for long-term treatment, consistent access to health care is of utmost importance and may benefit. So in conclusion, we found PQI, the prevention quality indicator, was higher for chronic conditions, indicating the need for high quality outpatient care in order to prevent hospital admissions for chronic conditions. Furthermore, Appalachian counties in Ohio had significantly lower numbers of specialist physicians and other health care providers demonstrating significant disparities in the region, where patients in Appalachia may be relying on their primary care physician to work outside of their traditional scope of practice, because they don't have access to specialist physicians. Thank you for listening.

healthcare accessibility

Appalachian Ohio

chronic diseases

provider density

preventable care