Kang Hyojung, Sohn Min-Woong, Kim Soyoun, Zhang Siyao, Balkrishnan Rajesh, Anderson Roger, McCall Anthony, McMurry Timothy, Lobo Jennifer Mason
Department of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA.
Department of Health Management and Policy, College of Public Health, University of Kentucky, Lexington, KY, USA.
Health Serv Outcomes Res Methodol. 2024 Jun;24(2):200-210. doi: 10.1007/s10742-023-00310-5. Epub 2023 Aug 9.
Annual preventive care is essential for diabetes patients to reduce the risk of complications including hypoglycemic events and blindness. Our aim was to examine the relative efficiency of Diabetes Belt (DB) and non-Diabetes Belt (NDB) counties in providing recommended preventive care for Medicare beneficiaries with diabetes using available health professional resources and to understand county-level socioeconomic factors associated with inefficient provision of preventive care. A data envelopment analysis (DEA) model was developed to assess relative efficiency of counties in providing diabetes preventive care. Logistic regression was performed to identify socioeconomic characteristics associated with inefficiencies. We used Medicare claims data to extract individual-level information of diabetes preventive service use and obtained county-level estimates of health resources information from the Area Health Resources File. More than 80% of counties had more than 10% inefficiencies on average. Compared to counties in the NDB, the odds of being inefficient were 2.44 times more likely in the DB (OR 2.44, CI 1.67-3.58). Counties with lower median income, with a smaller proportion of non-Hispanic Black population, and in a rural area had higher odds of being inefficient in providing preventive care. Our DEA results showed that counties in the DB and NDB were mostly inefficient. The availability of care providers may be less of a problem than how efficiently the resources are used in providing preventive care. Identifying sources of inefficiency within each community with low resource utilization and developing targeted strategies is needed to improve uptake of preventive care cost-effectively.
年度预防性护理对于糖尿病患者降低并发症风险至关重要，这些并发症包括低血糖事件和失明。我们的目的是利用现有的卫生专业资源，研究糖尿病带（DB）县和非糖尿病带（NDB）县为医疗保险受益糖尿病患者提供推荐预防性护理的相对效率，并了解与预防性护理提供效率低下相关的县级社会经济因素。我们开发了一种数据包络分析（DEA）模型来评估各县提供糖尿病预防性护理的相对效率。进行逻辑回归以确定与效率低下相关的社会经济特征。我们使用医疗保险理赔数据提取糖尿病预防性服务使用的个人层面信息，并从地区卫生资源文件中获取县级卫生资源信息估计值。超过80%的县平均效率低下超过10%。与NDB县相比，DB县效率低下的几率高出2.44倍（OR 2.44，CI 1.67 - 3.58）。收入中位数较低、非西班牙裔黑人人口比例较小且位于农村地区的县，提供预防性护理效率低下的几率更高。我们的DEA结果表明，DB县和NDB县大多效率低下。护理提供者的可获得性可能不如资源在提供预防性护理时的使用效率那样成为问题。需要确定每个资源利用率低的社区内效率低下的根源，并制定有针对性的策略，以经济高效地提高预防性护理的利用率。
