title: Predicting nursing home length of stay and outcome with a resource-based classification system.
abstract: The anticipated demographic changes with an increasing number of elderly force us to plan and use health care resources more efficiently. In this study we have used the components of a case-mix measure for nursing homes; the Resource Utilization Groups (RUG-II), to predict length of stay (LOS) and outcome in geriatric institutions. We have shown that the RUG categories and an activities of daily living (ADL) index differ significantly in both respects, but that other variables might be of more clinical value when establishing a prospective payment system, based on LOS in geriatric institutions.
authors.affiliation: Karolinska Institute.
authors.forename: G
authors.initials: G
authors.lastname: Ljunggren
authors.forename: L
authors.initials: L
authors.lastname: Brandt
mesh_terms: D000203:Activities of Daily Living; D000368:Aged; D003430:Cross-Sectional Studies; D003953:Diagnosis-Related Groups; D006295:Health Resources / Q000145:classification; D006707:Homes for the Aged / Q000191:economics / Q000458:organization & administration / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D008134:Long-Term Care / Q000145:classification*; D009735:Nursing Homes / Q000191:economics / Q000458:organization & administration / Q000706:statistics & numerical data*; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D010351:Patient Discharge / Q000706:statistics & numerical data; D013548:Sweden