Petterson Stephen
Robert Graham Center, Washington, DC 20036, United States.
Health Aff Sch. 2023 Nov 3;1(5):qxad063. doi: 10.1093/haschl/qxad063. eCollection 2023 Nov.
The Area Deprivation Index (ADI) is a widely used measure recently selected for several federal payment models that adjusts payments based on where beneficiaries live. A recent debate in focuses on seemingly implausible ADI rankings in major cities and across New York. At the root of the issue is the importance of standardization of measures prior to calculating index scores. Neighborhood Atlas researchers are implicitly arguing that their choice to not standardize is of little consequence. Using the same data and methods as the Neighborhood Atlas, this paper focuses on this choice by calculating and comparing standardized and unstandardized ADI scores. The calculated unstandardized ADI nearly perfectly matches the Neighborhood Atlas ADI ( > 0.9999), whereas the correlation with a standardized version is much lower ( = 0.7245). The main finding is that, without standardization, the ADI is reducible to a weighted average of just 2 measures-income and home values-certainly not the advertised multidimensional measure. Federal programs that have incorporated the ADI risk poorly allocating scarce resources meant to reduce health inequities.
区域贫困指数(ADI)是一种广泛使用的衡量指标,最近被选用于几种联邦支付模式,这些模式根据受益人的居住地点调整支付金额。最近在[具体范围未明确]的一场辩论聚焦于大城市以及纽约各地看似不合理的ADI排名。问题的根源在于在计算指数得分之前进行测量标准化的重要性。邻里地图集研究人员含蓄地认为他们不进行标准化的选择影响不大。本文使用与邻里地图集相同的数据和方法,通过计算和比较标准化和非标准化的ADI得分来关注这一选择。计算得出的非标准化ADI与邻里地图集的ADI几乎完全匹配(>0.9999),而与标准化版本的相关性则低得多(=0.7245)。主要发现是,未经标准化处理,ADI可简化为仅两项指标(收入和房屋价值)的加权平均值,这显然不是所宣称的多维度衡量指标。采用ADI的联邦项目存在资源分配不当的风险,而这些资源本应用于减少健康不平等现象。