Sampling coverage of the Arkansas all-payer claims database by County's persistent poverty designation

IF 3.1 2区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Health Services Research Pub Date : 2024-06-16 DOI:10.1111/1475-6773.14342
Chenghui Li PhD, Cheng Peng PhD, Peter DelNero PhD, Mahima Saini B.Pharm, Mario Schootman PhD
{"title":"Sampling coverage of the Arkansas all-payer claims database by County's persistent poverty designation","authors":"Chenghui Li PhD,&nbsp;Cheng Peng PhD,&nbsp;Peter DelNero PhD,&nbsp;Mahima Saini B.Pharm,&nbsp;Mario Schootman PhD","doi":"10.1111/1475-6773.14342","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Objectives</h3>\n \n <p>To evaluate the quality of Arkansas All-Payer Claims Database (APCD) for disparity research in persistent poverty areas by determining (1) its representativeness of Arkansas population, (2) variation by county, and (3) differences in coverage between persistent poverty and other counties.</p>\n </section>\n \n <section>\n \n <h3> Data Sources</h3>\n \n <p>Cross-sectional study using 2019 Arkansas APCD member enrollment data and county-level data from various agencies.</p>\n </section>\n \n <section>\n \n <h3> Data Collection/Extraction Methods</h3>\n \n <p>An alias identifier linked persons across insurance plans. County FIPS codes were used to extract county-level variables.</p>\n </section>\n \n <section>\n \n <h3> Study Design</h3>\n \n <p>Cohort 1 included individuals with ≥1 day of medical coverage in 2019. Cohort 2 included individuals with medical coverage in June, 2019. Cohort 3 included individuals with continuous medical coverage in 2019. Sampling proportions of a county's population in the three cohorts were compared between persistent poverty and other counties. Inverse-variance weighted linear regression was used to identify county-level socioeconomic and demographic characteristics associated with inclusion in each cohort.</p>\n </section>\n \n <section>\n \n <h3> Principal Findings</h3>\n \n <p>In 2019, 73.6% of Arkansans had medical coverage for ≥1 day (Cohort 1), 66.3% had coverage in June (Cohort 2), and 58.8% had continuous coverage (Cohort 3) in APCD. Sampling proportions varied by county (median[range]: Cohort 1, 78% [58%–95%]; Cohort 2, 71% [51%–88%]; and Cohort 3, 64% [44%–80%]), and were higher among persistent poverty counties than others for all three cohorts (mean [SD], persistent poverty vs. other: Cohort 1: 80.9% [6.4%] vs. 77.1% [6.3%], <i>p</i> = 0.04; Cohort 2: 74.0% [6.4%] vs. 70.1% [6.2%], <i>p</i> = 0.03; Cohort 3: 66.4% [6.1%] vs. 62.7% [6.0%], <i>p</i> = 0.03). In the 2019 APCD, larger counties and those with higher proportions of females or persons 65+ years had higher coverage, whereas counties with higher per capita household income, median home value, or disproportionately more persons of other races (non-White and non-Black) had lower coverage (<i>p</i> &lt; 0.05 for all three cohorts).</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>The Arkansas APCD had good coverage of Arkansas population. Coverage was higher in persistent poverty counties than others.</p>\n </section>\n </div>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2024-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Services Research","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1475-6773.14342","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0

Abstract

Objectives

To evaluate the quality of Arkansas All-Payer Claims Database (APCD) for disparity research in persistent poverty areas by determining (1) its representativeness of Arkansas population, (2) variation by county, and (3) differences in coverage between persistent poverty and other counties.

Data Sources

Cross-sectional study using 2019 Arkansas APCD member enrollment data and county-level data from various agencies.

Data Collection/Extraction Methods

An alias identifier linked persons across insurance plans. County FIPS codes were used to extract county-level variables.

Study Design

Cohort 1 included individuals with ≥1 day of medical coverage in 2019. Cohort 2 included individuals with medical coverage in June, 2019. Cohort 3 included individuals with continuous medical coverage in 2019. Sampling proportions of a county's population in the three cohorts were compared between persistent poverty and other counties. Inverse-variance weighted linear regression was used to identify county-level socioeconomic and demographic characteristics associated with inclusion in each cohort.

Principal Findings

In 2019, 73.6% of Arkansans had medical coverage for ≥1 day (Cohort 1), 66.3% had coverage in June (Cohort 2), and 58.8% had continuous coverage (Cohort 3) in APCD. Sampling proportions varied by county (median[range]: Cohort 1, 78% [58%–95%]; Cohort 2, 71% [51%–88%]; and Cohort 3, 64% [44%–80%]), and were higher among persistent poverty counties than others for all three cohorts (mean [SD], persistent poverty vs. other: Cohort 1: 80.9% [6.4%] vs. 77.1% [6.3%], p = 0.04; Cohort 2: 74.0% [6.4%] vs. 70.1% [6.2%], p = 0.03; Cohort 3: 66.4% [6.1%] vs. 62.7% [6.0%], p = 0.03). In the 2019 APCD, larger counties and those with higher proportions of females or persons 65+ years had higher coverage, whereas counties with higher per capita household income, median home value, or disproportionately more persons of other races (non-White and non-Black) had lower coverage (p < 0.05 for all three cohorts).

Conclusions

The Arkansas APCD had good coverage of Arkansas population. Coverage was higher in persistent poverty counties than others.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
阿肯色州所有付费者索赔数据库的抽样覆盖范围,按县的持续贫困状况分类。
目标:通过确定(1)阿肯色州人口的代表性,(2)各县的差异,以及(3)持续贫困县和其他县之间的覆盖率差异,评估阿肯色州所有纳税人索赔数据库(APCD)的质量,以便在持续贫困地区开展差异研究:横断面研究使用 2019 年阿肯色州 APCD 会员注册数据和来自不同机构的县级数据:一个别名标识符将不同保险计划的人员联系起来。县级 FIPS 代码用于提取县级变量:队列 1 包括 2019 年医疗保险天数≥1 天的个人。队列 2 包括 2019 年 6 月有医疗保险的个人。队列 3 包括 2019 年有连续医疗保险的个人。比较了持续贫困县和其他县在三个组群中的人口抽样比例。采用逆方差加权线性回归法确定与纳入每个队列相关的县级社会经济和人口特征:2019 年,在 APCD 中,73.6% 的阿肯色人医疗保险≥1 天(队列 1),66.3% 的人在 6 月份有保险(队列 2),58.8% 的人有连续保险(队列 3)。抽样比例因县而异(中位数[范围]:组群 1,78% [58%-95%];组群 2,71% [51%-88%];组群 3,64% [44%-80%]),在所有三个组群中,持续贫困县的抽样比例均高于其他县(持续贫困县与其他县的平均值 [SD]:组群 1:80.9%;组群 2:78% [58%-95%];组群 3:64% [44%-80%]):组群 1:80.9% [6.4%] vs. 77.1% [6.3%],p = 0.04;组群 2:74.0% [6.4%] vs. 70.1% [6.2%],p = 0.03;组群 3:66.4% [6.1%] vs. 62.7% [6.0%],p = 0.03)。在 2019 年的 APCD 中,较大的县以及女性或 65 岁以上人口比例较高的县的覆盖率较高,而人均家庭收入、房屋价值中位数较高的县或其他种族(非白人和非黑人)人口比例过高的县的覆盖率较低(p 结论:阿肯色州 APCD 对阿肯色州人口的覆盖率较高。持续贫困县的覆盖率高于其他县。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Health Services Research
Health Services Research 医学-卫生保健
CiteScore
4.80
自引率
5.90%
发文量
193
审稿时长
4-8 weeks
期刊介绍: Health Services Research (HSR) is a peer-reviewed scholarly journal that provides researchers and public and private policymakers with the latest research findings, methods, and concepts related to the financing, organization, delivery, evaluation, and outcomes of health services. Rated as one of the top journals in the fields of health policy and services and health care administration, HSR publishes outstanding articles reporting the findings of original investigations that expand knowledge and understanding of the wide-ranging field of health care and that will help to improve the health of individuals and communities.
期刊最新文献
Quality improvement lessons learned from National Implementation of the "Patient Safety Events in Community Care: Reporting, Investigation, and Improvement Guidebook". Connecting unstably housed veterans living in rural areas to health care: Perspectives from Health Care Navigators. A structured approach to modifying an implementation package while scaling up a complex evidence-based practice. Evaluation of regional variation in racial and ethnic differences in patient experience among Veterans Health Administration primary care users. Effect of mental health staffing inputs on initiation of care among recently separated Veterans.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1