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HMO Marketing and Selection Bias

Are Tefra HMOs Skimming

Datos Bibliográficos

ID9104928
AutoresRichard Lichtenstein (autor de correspondencia), J W Thomas (0000-0002-2098-6458, Health Services Research & Development, autor de correspondencia), Bruce A Watkins (0000-0002-2793-4538, University of Michigan), Bruce Watkins, Christopher Puto, Christopher P Puto (University of Arizona), James M Lepkowski (University of Michigan), James Lepkowski, Janet Adams-Watson, Janet G Adams-Watson (Health Services Research & Development), Bridget Simone, David Vest (Colorado State University)
Año1992
Volumen30
Número4
Páginas329-346
Fecha de publicación1992-04-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaMedical Care (JOURNAL)
Identificadores de la revistaISSN: 0025-7079 • E-ISSN: 1537-1948
EditorialOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/00005650-199204000-00004
PMID1556881
OpenAlexW2025552704
IdiomaEN
Citas recibidas1
Referencias citadas4

The research evidence indicates that health maintenance organizations (HMOs) participating in the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) At-Risk Program tend to experience favorable selection. Although favorable selection might result from patient decisions, a common conjecture is that it can be induced by HMOs through their marketing activities. The purpose of this study is to examine the relationship between HMO marketing strategies and selection bias in TEFRA At-Risk HMOs. A purposive sample of 22 HMOs that were actively marketing their TEFRA programs was selected and data on organizational characteristics, market area characteristics, and HMO marketing decisions were collected. To measure selection bias in these HMOs, the functional health status of approximately 300 enrollees in each HMO was compared to that of 300 non-enrolling beneficiaries in the same area. Three dependent variables, reflecting selection bias at the mean, the low health tail, and the high health tail of the health status distribution were created. Weighted least squares regressions were then used to identify relationships between marketing elements and selection bias. Subject to the statistical limitations of the study, our conclusion is that it is doubtful that HMO marketing decisions are responsible for the prevalence of favorable selection in HMO enrollment. It also appears unlikely that HMOs were differentially targeting healthy and unhealthy segments of the Medicare market

Biology · Business · Machine learning · MEDLINE · Selection (genetic algorithm) · Selection bias · Statistics · Computer Science · Healthcare Policy and Management · Marketing · Mathematics

  • Boutique to Booming

    Andrew S Kelly•Journal of Health Politics Policy…•2016

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    J W Thomas, Richard Lichtenstein•Medical Care•1986

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    Anita L Stewart, John E Ware et al.•Medical Care•1981

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    Richard Lichtenstein, J W Thomas et al.•Medical Care•1991

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    Louis Guttman•American Sociological Review•1944

Obras citantes distintas1
Citas por año0,1
Intervalo de citas2016 - 2016 (1)
Velocidad de citaciónhistorical
Altamente citadoNo
Tipos de citaNeutras: 1
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