Borgemenke Samuel, Newsom D'Nair, Leftwich Halie, Gideon Lucille, Beverly Elizabeth A
Department of Medicine, 1 Ohio University, Ohio University Heritage College of Osteopathic Medicine, Athens, USA.
Department of Primary Care, The Ohio University Diabetes Institute, 1 Ohio University, Athens, OH, USA.
J Gen Intern Med. 2025 May;40(7):1511-1518. doi: 10.1007/s11606-024-09312-6. Epub 2025 Jan 7.
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.
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.
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.
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 PCPSpecialistAPP*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.
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.
慢性下呼吸道疾病、心脏病和糖尿病在农村地区的患病率较高。以往的研究引发了人们对医生供应不足会带来不良后果的担忧。
评估俄亥俄州88个县（包括阿巴拉契亚县和非阿巴拉契亚县）的疾病负担，并研究其与医疗服务提供者数量的关联。
我们利用了来自医疗保险和医疗补助服务中心（CMS）以及“医疗保险差异地图”工具的数据。我们进行了方差分析，以比较俄亥俄州县的初级保健医生（PCP）、专科医生、高级执业提供者（APP）和其他医疗服务提供者的平均数量。我们按健康状况计算了平均患病率、主要成本和预防质量指标（PQI）。我们分析了各县医疗服务提供者与PQI之间的关系，并研究了阿巴拉契亚地区和非阿巴拉契亚地区在医疗服务提供者和疾病负担方面的差异。
每10万人中各类医疗服务提供者的平均数量在PCP、专科医生、APP和其他医疗服务提供者之间存在显著差异（F = 13.9，P < 0.001）。在所选定的疾病中，高血压（平均 = 67.0，标准差 = 2.2）和糖尿病（平均 = 27.1，标准差 = 2.4）的患病率最高。慢性病导致的可预防住院次数（平均 = 2024.9，标准差 = 526.8）显著高于急性病导致的可预防住院次数（平均 = 851.6，标准差 = 262.2）（P < 0.001）。PCP专科医生APP*其他人员的多变量混合效应模型是所有健康状况的最佳预测模型（P < 0.001）。阿巴拉契亚县的慢性阻塞性肺疾病（COPD，平均 = 17.4，标准差 = 2.8）和糖尿病（平均 = 28.4，标准差 = 2.3）患病率显著高于非阿巴拉契亚县的COPD（平均 = 13.7，标准差 = 1.9）和糖尿病（平均 = 26.2，标准差 = 2.1）（P < 0.001）。
本研究发现慢性病的PQI得分高于急性病，这表明需要更高质量的门诊护理来预防可避免的住院。此外，阿巴拉契亚县的其他医疗服务提供者较少，许多县缺乏专科医生，这凸显了俄亥俄州阿巴拉契亚地区在医疗服务可及性方面的显著差异。
