The Neighborhood Deprivation Index and Provider Geocoding Identify Critical Catchment Areas for Diabetes Outreach
The Neighborhood Deprivation Index and Provider Geocoding Identify Critical Catchment Areas for Diabetes Outreach
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DOI：
10.1210/clinem/dgaa462
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发表时间：
2020-09-01
影响因子：
5.8
通讯作者：
Maahs, David M.
中科院分区：
文献类型：
--
作者：
Walker, Ashby F.;Hu, Hui;Maahs, David M.
目的：在佛罗里达州和加利福尼亚州设计 ECHOT 1 型糖尿病 (T1D) 项目时，将社区剥夺指数 (NDI) 与每个州的初级保健提供者 (PCP) 和内分泌科医生的地理编码结合使用，以同时识别内分泌提供者密度低的地区和健康风险/贫困高的地区。 NDI 衡量了贫困的许多方面，这些方面已被证明是健康结果的关键指标。方法：使用 2013-2017 年美国社区调查 (ACS) 5 年估计数据来创建加利福尼亚州和佛罗里达州的 NDI 地图。此外，通过 Google 地理编码 API 和 TravelTime 搜索应用程序编程接口 (API)，使用两个州的 PCP 和内分泌科医生公开提供的提供商目录进行地理编码和 30 分钟车程缓冲。结果：根据这些发现，我们将高需求服务区域定义为 (1) 距最近的内分泌科医生超过 30 分钟车程，但距最近的 PCP 不到 30 分钟车程的区域； (2) 最高四分位数的 NDI； (3) 人口数量高于中位数（人口普查区为 5199 人，人口普查区块组为 1394 人）。在加利福尼亚州和佛罗里达州的 12 181 个人口普查区和 34 490 个人口普查街区组中，我们确定了符合这些标准的 57 个普查区和 215 个街区组作为高需求集水区。结论：地理空间分析提供了重要的初始方法步骤，可以有效地集中糖尿病项目开发的外展工作。 NDI 与地理编码提供者目录的集成可以实现更具成本效益和有针对性的干预措施，以覆盖最脆弱的 T1D 人群。
Purpose: In designing a Project ECHOT type 1 diabetes (T1D) program in Florida and California, the Neighborhood Deprivation Index (NDI) was used in conjunction with geocoding of primary care providers (PCPs) and endocrinologists in each state to concurrently identify areas with low endocrinology provider density and high health risk/poverty areas. The NDI measures many aspects of poverty proven to be critical indicators of health outcomes.Methods: The data from the 2013-2017 American Community Survey (ACS) 5-year estimates were used to create NDI maps for California and Florida. In addition, geocoding and 30-minute drive-time buffers were performed using publicly available provider directories for PCPs and endocrinologists in both states by Google Geocoding API and the TravelTime Search Application Programming Interface (API).Results: Based on these findings, we defined high-need catchment areas as areas with (1) more than a 30-minute drive to the nearest endocrinologist but within a 30-minute drive to the nearest PCP; (2) an NDI in the highest quartile; and (3) a population above the median (5199 for census tracts, and 1394 for census block groups). Out of the 12 181 census tracts and 34 490 census block groups in California and Florida, we identified 57 tracts and 215 block groups meeting these criteria as high-need catchment areas.Conclusion: Geospatial analysis provides an important initial methodologic step to effectively focus outreach efforts in diabetes program development. The integration of the NDI with geocoded provider directories enables more cost-effective and targeted interventions to reach the most vulnerable populations living with T1D.