Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-24T17:04:08.079Z Has data issue: false hasContentIssue false

Predicting Nursing Home Length of Stay and Outcome with a Resource-Based Classification System

Published online by Cambridge University Press:  10 March 2009

Gunnar Ljunggren
Affiliation:
Karolinska Institute and Huddinge Hospital
Lena Brandt
Affiliation:
Karolinska Institute and Huddinge Hospital

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.

Type
General Essays
Copyright
Copyright © Cambridge University Press 1996

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.Cooney, L. M. Jr., & Fries, B. E.Validation and use of resource utilization groups as a case-mix measure for long-term care. Medical Care, 1985, 23, 123–32.CrossRefGoogle ScholarPubMed
2.Coughlin, T. A., McBride, T. D., & Liu, K.Determinants of transitory and permanent nursing home admissions. Medical Care, 1990, 28, 616–31.CrossRefGoogle ScholarPubMed
3.Fries, B. E., & Cooney, L. M. Jr.Resource utilization groups: A patient classification system for long-term. Medical Care, 1985, 23, 110–22.CrossRefGoogle ScholarPubMed
4.Fries, B. E., Schneider, D. P., Foley, W. J. et al. Refining a case-mix measure for nursing homes. Resource Utilization Groups (RUG-III). Medical Care, 1994, 32, 668–85.CrossRefGoogle ScholarPubMed
5.Haalboom, J. R.The costs of decubitus (in Dutch). Ned Tijdschr Geneeskd, 1991, 135, 606–10.Google ScholarPubMed
6.Hauser, B., Robinson, J., Powers, J. S., & Laubacher, M. A.The evaluation of an intermediate care-geriatric evaluation unit in a Veterans Administration Hospital. Southern Medical Journal, 1991, 84, 597602.Google Scholar
7.Kalbfleisch, J. D., & Prentice, R. L.The statistical analysis of failure time data. New York: J. Wiley & Sons, 1980.Google Scholar
8.Lewis, M. A., Leake, B., Clark, V., & Leal-Sotelo, M.Case mix and outcomes of nursing home patients: The importance of prior nursing home care and admission from home versus hospital. Medical Care, 1989, 27, 376–85.CrossRefGoogle Scholar
9.Ljunggren, G.Resource utilization in geriatric care: Studies of case-mix, length of stay, and outcome. Academic thesis. Stockholm: Karolinska Institute, 1992.Google Scholar
10.Ljunggren, G., Fries, B. E., & Winblad, U.International validation and reliability testing of a patient classification system for long-term care. European Journal of Gerontology, 1992, 1, 372–83.Google Scholar
11.Ljunggren, G., Jonsson, E., & Winblad, B. Prolonged stays in long-term care in Stockholm, 19721989. Unpublished.Google Scholar
12.Löök, J.On the effects of an autonomous day care programme for elderly patients in rehabilitation. Academic thesis. Stockholm: Karolinska Institute, 1991.Google Scholar
13.Morrisey, M. A., Sloan, F. A., & Valvona, J.Medicare prospective payment and posthospital transfers to subacute care. Medical Care, 1988, 26, 685–98.CrossRefGoogle ScholarPubMed
14.National Central Bureau of Statistics. The future population of Sweden: Projections for the years 1991–2025. Demographic reports 1991:1. Stockholm: The National Central Bureau of Statistics, 1991.Google Scholar
15.Rubenstein, L. Z., Campbell, L. J., & Kane, R. L., (eds.) Geriatric assessment. Philadelphia, PA: WB Saunders, 1987.Google ScholarPubMed
16.SAS Institute. SAS/STAT guide for personal computers, version 6. Gary, IN: SAS Institute Inc., 1987.Google Scholar
17.Schneider, D., Fries, B. E., Foley, W. et al. Case mix measurement for nursing home payment: Resource utilization groups (RUG-II). Health Care Financing Review, 1988, annual supplement, 39.Google Scholar
18.Stout, R. W., & Crawford, V.Active-life expectancy and terminal dependency: Trends in long-term geriatric care over 33 years. Lancet, 1988, 1, 281–83.CrossRefGoogle ScholarPubMed
19.Svanborg, A.The health of the elderly population: Results from longitudinal studies with age-cohort comparisons. Ciba Foundation Symposium, 1988, 134, 316.Google ScholarPubMed
20.Texas Department of Human Services. Texas nursing home case mix project: Continuation application. HCFA Grant Award # ll-C-98688/02. Austin, TX: Department of Human Services, 1986.Google Scholar