Academic Journal

Case-mix adjustment of the National CAHPS benchmarking data 1.0: a violation of model assumptions?

التفاصيل البيبلوغرافية
العنوان: Case-mix adjustment of the National CAHPS benchmarking data 1.0: a violation of model assumptions?
المؤلفون: Elliott, Marc N., Swartz, Richard, Adams, John, Spritzer, Karen L., Hays, Ron D., Elliott, M N, Swartz, R, Adams, J, Spritzer, K L, Hays, R D
المصدر: Health Services Research; Jul2001, Vol. 36 Issue 3, p555-573, 19p
مصطلحات موضوعية: MEDICAL care, CONSUMER attitudes, MEDICAID, HEALTH planning, HEALTH insurance, HEALTH policy
مستخلص: Objective: To compare models for the case-mix adjustment of consumer reports and ratings of health care.Data Sources: The study used the Consumer Assessment of Health Plans (CAHPS) survey 1.0 National CAHPS Benchmarking Database data from 54 commercial and 31 Medicaid health plans from across the United States: 19,541 adults (age > or = 18 years) in commercial plans and 8,813 adults in Medicaid plans responded regarding their own health care, and 9,871 Medicaid adults responded regarding the health care of their minor children.Study Design: Four case-mix models (no adjustment; self-rated health and age; health, age, and education; and health, age, education, and plan interactions) were compared on 21 ratings and reports regarding health care for three populations (adults in commercial plans, adults in Medicaid plans, and children in Medicaid plans). The magnitude of case-mix adjustments, the effects of adjustments on plan rankings, and the homogeneity of these effects across plans were examined.Data Extraction: All ratings and reports were linearly transformed to a possible range of 0 to 100 for comparability.Principal Findings: Case-mix adjusters, especially self-rated health, have substantial effects, but these effects vary substantially from plan to plan, a violation of standard case-mix assumptions.Conclusion: Case-mix adjustment of CAHPS data needs to be re-examined, perhaps by using demographically stratified reporting or by developing better measures of response bias. [ABSTRACT FROM AUTHOR]
Copyright of Health Services Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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Academic Journal
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Array ( [Name] => Abstract [Label] => Abstract [Group] => Ab [Data] => <bold>Objective: </bold>To compare models for the case-mix adjustment of consumer reports and ratings of health care.<bold>Data Sources: </bold>The study used the Consumer Assessment of Health Plans (CAHPS) survey 1.0 National CAHPS Benchmarking Database data from 54 commercial and 31 Medicaid health plans from across the United States: 19,541 adults (age > or = 18 years) in commercial plans and 8,813 adults in Medicaid plans responded regarding their own health care, and 9,871 Medicaid adults responded regarding the health care of their minor children.<bold>Study Design: </bold>Four case-mix models (no adjustment; self-rated health and age; health, age, and education; and health, age, education, and plan interactions) were compared on 21 ratings and reports regarding health care for three populations (adults in commercial plans, adults in Medicaid plans, and children in Medicaid plans). The magnitude of case-mix adjustments, the effects of adjustments on plan rankings, and the homogeneity of these effects across plans were examined.<bold>Data Extraction: </bold>All ratings and reports were linearly transformed to a possible range of 0 to 100 for comparability.<bold>Principal Findings: </bold>Case-mix adjusters, especially self-rated health, have substantial effects, but these effects vary substantially from plan to plan, a violation of standard case-mix assumptions.<bold>Conclusion: </bold>Case-mix adjustment of CAHPS data needs to be re-examined, perhaps by using demographically stratified reporting or by developing better measures of response bias. [ABSTRACT FROM AUTHOR] )
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