Nir Menachemi, Justin Blackburn, David J Becker, Michael A Morrisey, Bisakha Sen, Cathy Caldwell
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Additionally, we examine the extent to which these two claims-based approaches to measuring quality differ in assessments of disparities in quality of care across subgroups of children.</p><p><strong>Results: </strong>Statistically significant differences in rates were identified when comparing the two definitions for calculating each quality measure. Measure differences ranged from a 1.9 percentage point change for measure #13 (receiving preventive dental services) to a 25.5 percentage point change for measure #12 (adolescent well-care visit). We were able to identify subgroups based upon family income, rural location, and chronic disease status with differences in quality within the core measures. However, some identified disparities were sensitive to the approach used to calculate the quality measure.</p><p><strong>Conclusions: </strong>Differences in CHIP design and structure, across states and over time, may limit the usefulness of select claims-based core measures for detecting disparities accurately. Additional guidance and research may be necessary before reporting of the measures becomes mandatory.</p>","PeriodicalId":89601,"journal":{"name":"Medicare & medicaid research review","volume":"3 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2013-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4001808/pdf/mmrr2013-003-03-a04.pdf","citationCount":"1","resultStr":"{\"title\":\"Measuring prevention more broadly: an empirical assessment of CHIPRA core measures.\",\"authors\":\"Nir Menachemi, Justin Blackburn, David J Becker, Michael A Morrisey, Bisakha Sen, Cathy Caldwell\",\"doi\":\"10.5600/mmrr.003.03.a04\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To assess limitations of using select Children's Health Insurance Program Reauthorization Act (CHIPRA) core claims-based measures in capturing the preventive services that may occur in the clinical setting.</p><p><strong>Methods: </strong>We use claims data from ALL Kids, the Alabama Children's Health Insurance Program (CHIP), to calculate each of four quality measures under two alternative definitions: (1) the formal claims-based guidelines outlined in the CMS Technical Specifications, and (2) a broader definition of appropriate claims for identifying preventive service use. Additionally, we examine the extent to which these two claims-based approaches to measuring quality differ in assessments of disparities in quality of care across subgroups of children.</p><p><strong>Results: </strong>Statistically significant differences in rates were identified when comparing the two definitions for calculating each quality measure. Measure differences ranged from a 1.9 percentage point change for measure #13 (receiving preventive dental services) to a 25.5 percentage point change for measure #12 (adolescent well-care visit). We were able to identify subgroups based upon family income, rural location, and chronic disease status with differences in quality within the core measures. 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引用次数: 1
摘要
目的:评估使用儿童健康保险计划再授权法案(CHIPRA)核心索赔为基础的措施在捕捉可能发生在临床环境中的预防服务的局限性。方法:我们使用来自阿拉巴马州儿童健康保险计划(CHIP) ALL Kids的索赔数据,在两种不同的定义下计算四种质量指标:(1)CMS技术规范中概述的基于索赔的正式指南,以及(2)用于识别预防性服务使用的适当索赔的更广泛定义。此外,我们研究了这两种基于索赔的测量质量的方法在评估儿童亚组护理质量差异方面的差异程度。结果:在比较计算每个质量度量的两种定义时,确定了统计学上显着的差异。测量差异从措施#13(接受预防性牙科服务)的1.9个百分点变化到措施#12(青少年保健访问)的25.5个百分点变化不等。我们能够根据家庭收入、农村地区和慢性疾病状况确定亚组,这些亚组在核心测量中存在质量差异。然而,一些已确定的差异对用于计算质量度量的方法很敏感。结论:不同州和不同时期CHIP设计和结构的差异可能会限制选择基于索赔的核心措施准确检测差异的有效性。在强制性报告这些措施之前,可能需要额外的指导和研究。
Measuring prevention more broadly: an empirical assessment of CHIPRA core measures.
Objective: To assess limitations of using select Children's Health Insurance Program Reauthorization Act (CHIPRA) core claims-based measures in capturing the preventive services that may occur in the clinical setting.
Methods: We use claims data from ALL Kids, the Alabama Children's Health Insurance Program (CHIP), to calculate each of four quality measures under two alternative definitions: (1) the formal claims-based guidelines outlined in the CMS Technical Specifications, and (2) a broader definition of appropriate claims for identifying preventive service use. Additionally, we examine the extent to which these two claims-based approaches to measuring quality differ in assessments of disparities in quality of care across subgroups of children.
Results: Statistically significant differences in rates were identified when comparing the two definitions for calculating each quality measure. Measure differences ranged from a 1.9 percentage point change for measure #13 (receiving preventive dental services) to a 25.5 percentage point change for measure #12 (adolescent well-care visit). We were able to identify subgroups based upon family income, rural location, and chronic disease status with differences in quality within the core measures. However, some identified disparities were sensitive to the approach used to calculate the quality measure.
Conclusions: Differences in CHIP design and structure, across states and over time, may limit the usefulness of select claims-based core measures for detecting disparities accurately. Additional guidance and research may be necessary before reporting of the measures becomes mandatory.