HMO Marketing and Selection Bias
Are Tefra HMOs Skimming
Datos Bibliográficos
| ID | 9104928 |
|---|---|
| Autores | Richard 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) |
| Año | 1992 |
| Volumen | 30 |
| Número | 4 |
| Páginas | 329-346 |
| Fecha de publicación | 1992-04-01 |
| Peer Reviewed | Sí |
| Open Access | No |
| Tipo | ARTICLE |
| Revista | Medical Care (JOURNAL) |
| Identificadores de la revista | ISSN: 0025-7079 • E-ISSN: 1537-1948 |
| Editorial | Ovid Technologies (Wolters Kluwer Health) (PUBLISHER) |
| DOI | 10.1097/00005650-199204000-00004 |
| PMID | 1556881 |
| OpenAlex | W2025552704 |
| Idioma | EN |
| Citas recibidas | 1 |
| Referencias citadas | 4 |
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
| Obras citantes distintas | 1 |
|---|---|
| Citas por año | 0,1 |
| Intervalo de citas | 2016 - 2016 (1) |
| Velocidad de citación | historical |
| Altamente citado | No |
| Tipos de cita | Neutras: 1 |