Medical profiling: improving standards and risk adjustments using hierarchical models
The conclusions from a profile analysis to identify performance extremes can be affected substantially by the standards and statistical methods used and by the adequacy of risk adjustment. Medically meaningful standards are proposed to replace common statistical standards. Hierarchical regression me...
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| Veröffentlicht in: | Journal of health economics 2000-05, Vol.19 (3), p.291-309 |
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| container_end_page | 309 |
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| container_issue | 3 |
| container_start_page | 291 |
| container_title | Journal of health economics |
| container_volume | 19 |
| creator | Burgess, James F. Christiansen, Cindy L. Michalak, Sarah E. Morris, Carl N. |
| description | The conclusions from a profile analysis to identify performance extremes can be affected substantially by the standards and statistical methods used and by the adequacy of risk adjustment. Medically meaningful standards are proposed to replace common statistical standards. Hierarchical regression methods can handle several levels of random variation, make risk adjustments for the providers' case-mix differences, and address the proposed standards. These methods determine probabilities needed to make meaningful profiles of medical units based on standards set by all appropriate parties. |
| doi_str_mv | 10.1016/S0167-6296(99)00034-X |
| format | Article |
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Medically meaningful standards are proposed to replace common statistical standards. Hierarchical regression methods can handle several levels of random variation, make risk adjustments for the providers' case-mix differences, and address the proposed standards. 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| fulltext | fulltext |
| identifier | ISSN: 0167-6296 |
| ispartof | Journal of health economics, 2000-05, Vol.19 (3), p.291-309 |
| issn | 0167-6296 1879-1646 |
| language | eng |
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| source | MEDLINE; RePEc; Applied Social Sciences Index & Abstracts (ASSIA); Access via ScienceDirect (Elsevier) |
| subjects | Health administration Health care Health care delivery Health economics Health management Health services Hierarchical models Hospitals, Veterans - statistics & numerical data Intensive Care Units - statistics & numerical data Methods Models, Statistical Patient Readmission - statistics & numerical data Poisson Distribution Profiling standards Quality Assurance, Health Care - organization & administration Quality Assurance, Health Care - statistics & numerical data Regression analysis Regression-to-the-mean Risk Risk adjustment Risk Adjustment - methods Risk Adjustment - statistics & numerical data Risk assessment Statistical analysis Statistical methods Studies |
| title | Medical profiling: improving standards and risk adjustments using hierarchical models |
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