医疗补助计划扩展前后肯塔基州 2 型糖尿病患者可预防住院治疗的变化。

Annals of Saudi medicine Pub Date : 2024-03-01 Epub Date: 2024-04-04 DOI:10.5144/0256-4947.2024.73
Turky Arbaein, Bert Little, Sarah Monshi, Ahmed M Al-Wathinani, Amal Zaidan
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引用次数: 0

摘要

背景:与门诊治疗相比,住院治疗需要更多的资源,费用也更高。因此,与 2 型糖尿病相关的可预防住院治疗是研究医疗系统效率的一个重要课题:分析肯塔基州在扩大医疗补助计划之前(2010-2013 年)和扩大医疗补助计划之后(2014-2017 年)2 型糖尿病相关可预防住院率的县级差异:设计:地理制图和聚类分析:数据来自美国的一个州:我们使用 KID 数据生成与 2 型糖尿病相关的可预防性住院的地理映射图,以直观地显示住院率。我们纳入了肯塔基州所有 18 岁及以上、ICD9/10 主要诊断代码为 2 型糖尿病的出院患者。然后,我们采用聚类分析技术,比较肯塔基州各县在医疗补助扩展前后 2 型糖尿病相关可预防住院率的县级差异:结果:从 2010 年到 2017 年,与 2 型糖尿病相关的可预防性住院出院率在医疗补助扩展后期间显著下降(P=.001)。空间统计分析显示,在医疗补助扩展前后,肯塔基州南部、东部和东南部的 2 型糖尿病相关可预防性住院率相似的县出现了明显的空间聚集(Z 值为正,莫兰指数值为正(P>.05))。此外,在医疗补助扩展前和扩展后,该州北部、西部和中部地区与 2 型糖尿病相关的可预防住院率较低的县出现了明显的聚集(Z 值和莫兰指数值均为正数(P>.05)):肯塔基州东南部各县在这两个时期都出现了可避免的高住院率的显著聚集现象。关注肯塔基州的弱势县和经济不平等问题,可以降低未来与 2 型糖尿病相关的可预防住院率:我们使用的是去标识化数据,无法深入了解每位患者的住院频率。单个患者可能多次住院,并作为多个个体计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The variation in preventable hospitalization in patients with type 2 diabetes in Kentucky before and after the Medicaid expansion.

Background: Hospitalizations are more resource intensive and expensive than outpatient care. Therefore, type 2 diabetes-related preventable hospitalization are a major topic of research efficiency in the healthcare system.

Objectives: Analyze county level variation in type 2 diabetes-related preventable hospitalization rates in Kentucky before the Medicaid expansion (2010-2013) and after the Medicaid expansion (2014-2017).

Design: Geographic mapping and cluster analysis.

Setting: Data for a state of the United States of America.

Methods: We used the KID data to generate geographic mapping for type 2 diabetes-related preventable hospitalizations to visualize rates. We included all Kentucky discharges of age 18 years and older with the ICD9/10 principal diagnosis code for type 2 diabetes. Then, we conducted cluster analysis techniques to compare county-level variation in type 2 diabetes-related preventable hospitalization rates across Kentucky counties pre- and post-Medicaid expansion.

Main outcome and measures: County type 2 diabetes-related preventable hospitalization pre- and post-Medicaid expansion.

Results: From 2010-2017, type 2 diabetes-related preventable hospitalization discharge rates reduced significantly in the period of the post-Medicaid expansion (P=.001). The spatial statistics analysis revealed a significant spatial clustering of counties with similar rates of type 2 diabetes-related preventable hospitalization in the south, east, and southeastern Kentucky pre- and post-Medicaid expansion (positive z-score and positive Moran's Index value (P>.05). Also, there was a significant clustering of counties with low type 2 diabetes-related preventable hospitalization rates in the north, west, and central regions of the state pre-Medicaid expansion and post-Medicaid expansion (positive z-score and positive Moran's Index value (P>.05).

Conclusion: Kentucky counties in the southeast have experienced a significant clustering of highly avoidable hospitalization rates during both periods. Focusing on the vulnerable counties and the economic inequality in Kentucky could lead to efforts to lowering future type 2 diabetes-related preventable hospitalization rates.

Limitations: We used de-identified data which does not provide insights into the frequency of hospitalizations per patient. An individual patient may be hospitalized several times and counted as several individuals.

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