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Background <p>Chronic lower respiratory disease, heart disease, and diabetes have a higher prevalence in rural areas. Previous studies raise concerns that a lower supply of physicians is associated with negative outcomes.</p> Objective <p>To assess disease burden across the 88 counties in Ohio, including Appalachian and non-Appalachian counties, and examine associations with the number of healthcare providers.</p> Methods <p>We utilized data sourced from the Centers for Medicare &amp; Medicaid Services (CMS) and the Mapping Medicare Disparities tool. We conducted ANOVA to compare the mean number of primary care physicians (PCP), specialty physicians, advanced practice providers (APP), and other healthcare providers for Ohio counties. We calculated mean prevalence, principal cost, and prevention quality indicator (PQI) by health condition. We analyzed the relationship between healthcare providers and the PQI across counties, and examined differences in healthcare providers and disease burden between Appalachian and non-Appalachian regions.</p> Results <p>The mean number of providers per 100,000 people significantly differed between PCP, specialty physicians, APP, and other healthcare providers (<i>F</i> = 13.9, <i>P</i> &lt; 0.001). The prevalence of hypertension (mean = 67.0, SD = 2.2) and diabetes (mean = 27.1, SD = 2.4) was the highest of the selected conditions. The number of preventable hospitalizations from chronic conditions (mean = 2024.9, SD = 526.8) was significantly higher (<i>P</i> &lt; 0.001) than the number of preventable hospitalizations from acute conditions (mean = 851.6, SD = 262.2). The multivariate mixed effects model of PCP*Specialist*APP*Other was the best predictive model for all health conditions (<i>P</i> &lt; 0.001). COPD (mean = 17.4, SD = 2.8) and diabetes (mean = 28.4, SD = 2.3) in Appalachian counties were significantly higher (<i>P</i> &lt; 0.001) than COPD (mean = 13.7, SD = 1.9) and diabetes (mean = 26.2, SD = 2.1) in non-Appalachian counties.</p> Conclusion <p>This study found higher PQI scores for chronic conditions than acute conditions, indicating the need for higher-quality outpatient care to prevent avoidable hospital admissions. Further, Appalachian counties had fewer other healthcare providers and many counties lacked specialist physicians, highlighting significant disparities in healthcare access in Appalachian Ohio.</p>

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Measuring the Impact of Healthcare Provider Availability on Quality of Care and Disease Burden in Ohio: A Cross-Sectional Study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月7日

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  • Samuel Borgemenke,
  • D’Nair Newsom,
  • Halie Leftwich,
  • Lucille Gideon,
  • Elizabeth A. Beverly

摘要

Background

Chronic lower respiratory disease, heart disease, and diabetes have a higher prevalence in rural areas. Previous studies raise concerns that a lower supply of physicians is associated with negative outcomes.

Objective

To assess disease burden across the 88 counties in Ohio, including Appalachian and non-Appalachian counties, and examine associations with the number of healthcare providers.

Methods

We utilized data sourced from the Centers for Medicare & Medicaid Services (CMS) and the Mapping Medicare Disparities tool. We conducted ANOVA to compare the mean number of primary care physicians (PCP), specialty physicians, advanced practice providers (APP), and other healthcare providers for Ohio counties. We calculated mean prevalence, principal cost, and prevention quality indicator (PQI) by health condition. We analyzed the relationship between healthcare providers and the PQI across counties, and examined differences in healthcare providers and disease burden between Appalachian and non-Appalachian regions.

Results

The mean number of providers per 100,000 people significantly differed between PCP, specialty physicians, APP, and other healthcare providers (F = 13.9, P < 0.001). The prevalence of hypertension (mean = 67.0, SD = 2.2) and diabetes (mean = 27.1, SD = 2.4) was the highest of the selected conditions. The number of preventable hospitalizations from chronic conditions (mean = 2024.9, SD = 526.8) was significantly higher (P < 0.001) than the number of preventable hospitalizations from acute conditions (mean = 851.6, SD = 262.2). The multivariate mixed effects model of PCP*Specialist*APP*Other was the best predictive model for all health conditions (P < 0.001). COPD (mean = 17.4, SD = 2.8) and diabetes (mean = 28.4, SD = 2.3) in Appalachian counties were significantly higher (P < 0.001) than COPD (mean = 13.7, SD = 1.9) and diabetes (mean = 26.2, SD = 2.1) in non-Appalachian counties.

Conclusion

This study found higher PQI scores for chronic conditions than acute conditions, indicating the need for higher-quality outpatient care to prevent avoidable hospital admissions. Further, Appalachian counties had fewer other healthcare providers and many counties lacked specialist physicians, highlighting significant disparities in healthcare access in Appalachian Ohio.