Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, The University of Tennessee, Knoxville, Tennessee, United States of America.
PLoS One. 2024 Jun 4;19(6):e0298182. doi: 10.1371/journal.pone.0298182. eCollection 2024.
Hospitalizations due to diabetes complications are potentially preventable with effective management of the condition in the outpatient setting. Diabetes-related hospitalization (DRH) rates can provide valuable information about access, utilization, and efficacy of healthcare services. However, little is known about the local geographic distribution of DRH rates in Florida. Therefore, the objectives of this study were to investigate the geographic distribution of DRH rates at the ZIP code tabulation area (ZCTA) level in Florida, identify significant local clusters of high hospitalization rates, and describe characteristics of ZCTAs within the observed spatial clusters.
Hospital discharge data from 2016 to 2019 were obtained from the Florida Agency for Health Care Administration through a Data Use Agreement with the Florida Department of Health. Raw and spatial empirical Bayes smoothed DRH rates were computed at the ZCTA level. High-rate DRH clusters were identified using Tango's flexible spatial scan statistic. Choropleth maps were used to display smoothed DRH rates and significant high-rate spatial clusters. Demographic, socioeconomic, and healthcare-related characteristics of cluster and non-cluster ZCTAs were compared using the Wilcoxon rank sum test for continuous variables and Chi-square test for categorical variables.
There was a total of 554,133 diabetes-related hospitalizations during the study period. The statewide DRH rate was 8.5 per 1,000 person-years, but smoothed rates at the ZCTA level ranged from 0 to 101.9. A total of 24 significant high-rate spatial clusters were identified. High-rate clusters had a higher percentage of rural ZCTAs (60.9%) than non-cluster ZCTAs (41.8%). The median percent of non-Hispanic Black residents was significantly (p < 0.0001) higher in cluster ZCTAs than in non-cluster ZCTAs. Populations of cluster ZCTAs also had significantly (p < 0.0001) lower median income and educational attainment, and higher levels of unemployment and poverty compared to the rest of the state. In addition, median percent of the population with health insurance coverage and number of primary care physicians per capita were significantly (p < 0.0001) lower in cluster ZCTAs than in non-cluster ZCTAs.
This study identified geographic disparities of DRH rates at the ZCTA level in Florida. The identification of high-rate DRH clusters provides useful information to guide resource allocation such that communities with the highest burdens are prioritized to reduce the observed disparities. Future research will investigate determinants of hospitalization rates to inform public health planning, resource allocation and interventions.
通过在门诊环境中对病情进行有效管理，可预防因糖尿病并发症导致的住院治疗。糖尿病相关住院率（DRH）可以提供有关医疗服务获取、使用和效果的宝贵信息。然而，对于佛罗里达州的 DRH 率的当地地理分布情况却知之甚少。因此，本研究的目的是调查佛罗里达州邮政编码分区（ZCTA）层面的 DRH 率的地理分布情况，确定高住院率的显著局部聚集，并描述观察到的空间聚集内的 ZCTA 特征。
通过与佛罗里达州卫生部签订数据使用协议，从佛罗里达州卫生保健管理局获得 2016 年至 2019 年的住院数据。在 ZCTA 层面计算原始和空间经验贝叶斯平滑 DRH 率。使用 Tango 的灵活空间扫描统计方法确定高住院率的 DRH 聚集。使用分层线图显示平滑的 DRH 率和显著的高住院率空间聚集。使用 Wilcoxon 秩和检验比较连续变量和卡方检验比较分类变量，比较聚集和非聚集 ZCTA 的人口统计学、社会经济学和医疗保健相关特征。
研究期间共有 554133 例糖尿病相关住院治疗。全州 DRH 率为 8.5/1000 人年，但 ZCTA 层面的平滑率范围为 0 至 101.9。确定了 24 个显著的高住院率空间聚集。高住院率聚集的农村 ZCTA 比例（60.9%）高于非聚集 ZCTA（41.8%）。非西班牙裔黑人居民比例中位数在聚集 ZCTA 中明显高于非聚集 ZCTA（p<0.0001）。与全州其他地区相比，聚集 ZCTA 的人口中位数收入和教育程度明显较低（p<0.0001），失业率和贫困率较高。此外，聚集 ZCTA 的人口医疗保险覆盖率中位数和每千人初级保健医生人数明显低于非聚集 ZCTA（p<0.0001）。
本研究确定了佛罗里达州 ZCTA 层面 DRH 率的地理差异。高住院率 DRH 聚集的确定为指导资源分配提供了有用的信息，以便优先考虑负担最重的社区，以减少观察到的差异。未来的研究将调查住院率的决定因素，以为公共卫生规划、资源分配和干预措施提供信息。
