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了解你的 ABDs:堪萨斯州医疗补助残疾群体的医疗保健利用情况存在差异。

Learning your ABDs: variation in health care utilization across Kansas Medicaid disability groups.

机构信息

Preventive Medicine & Public Health, University of Kansas School of Medicine, 3901 Rainbow Blvd., MSN 1008, Kansas City, KS 66160, USA.

出版信息

Disabil Health J. 2013 Jul;6(3):220-6. doi: 10.1016/j.dhjo.2013.02.001. Epub 2013 Mar 14.

Abstract

BACKGROUND

State Medicaid programs provide critical health care access for persons with disabilities and older adults. Aged, Blind and Disabled (ABD) programs consist of important disability subgroups that Medicaid programs are not able to readily distinguish.

OBJECTIVE/HYPOTHESIS: The purpose of this project was to create an algorithm based principally on eligibility and claims data to distinguish disability subgroups and characterize differences in demographic characteristics, disease burden, and health care expenditures.

METHODS

We created an algorithm to distinguish Kansas Medicaid enrollees as adults with intellectual or developmental delays (IDD), physical disabilities (PD), severe mental illness (SMI), and older age.

RESULTS

For fiscal year 2009, our algorithm separated 101,464 ABD enrollees into the following disability subgroups: persons with IDD (19.6%), persons with PD (21.0%), older adults (19.7%), persons with SMI (32.8%), and persons not otherwise classified (6.9%). The disease burden present in the IDD, PD, and SMI subgroups was higher than for older adults. Home- and community-based services expenditures were common and highest for persons with IDD and PD. Older adults and persons with SMI had their highest expenditures for long-term care. Mean Medicaid expenditures were consistently higher for adults with IDD followed by adults with PD.

CONCLUSIONS

There are substantial differences between disability subgroups in the Kansas Medicaid ABD population with respect to demographics, disease burden, and health care expenditures. Through this algorithm, state Medicaid programs have the opportunity to collaborate with the most closely aligned service providers reflecting needed services for each disability subgroup.

摘要

背景

州医疗补助计划为残疾人和老年人提供了重要的医疗保健服务。“ aged,Blind and Disabled (ABD)”计划包含了重要的残疾亚组,而医疗补助计划无法轻易区分这些亚组。

目的/假设:本项目的目的是创建一个主要基于资格和索赔数据的算法,以区分残疾亚组,并描述人口统计学特征、疾病负担和医疗保健支出方面的差异。

方法

我们创建了一个算法来区分堪萨斯州医疗补助计划的参保人,将他们分为智力或发育迟缓(IDD)、身体残疾(PD)、严重精神疾病(SMI)和年龄较大的成年人。

结果

在 2009 财年,我们的算法将 101464 名 ABD 参保人分为以下残疾亚组:智力残疾者(19.6%)、身体残疾者(21.0%)、老年人(19.7%)、严重精神疾病患者(32.8%)和其他未分类者(6.9%)。ID、PD 和 SMI 亚组的疾病负担高于老年人。家庭和社区为基础的服务支出很常见,对于 ID 和 PD 患者来说最高。长期护理的支出最高,老年人和患有 SMI 的人。对于医疗补助计划来说,ID 患者的平均支出始终高于 PD 患者。

结论

堪萨斯州医疗补助计划 ABD 人群中的残疾亚组在人口统计学、疾病负担和医疗保健支出方面存在显著差异。通过这个算法,州医疗补助计划有机会与最紧密相关的服务提供者合作,为每个残疾亚组提供所需的服务。

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