Abstract
This case study of antipsychotic drug use in nursing homes illustrates the potential benefits and limits of multilevel hierarchical linear analysis in long-term care research. Multilevel (MLn) logistic regression models were used to assess changes in exposure and average daily dose and their associations with resident and facility characteristics following implementation of the 1987 Omnibus Budget Reconciliation Act regulations. Data were obtained for 8,158 elderly Oregon Medicaid residents residing in 128 facilities between July 1991 and December 1994. Findings support the general hypothesis that resident characteristics are the main determinants of drug use and that drug use decreased over time among some resident populations and some facility types. Although challenges were encountered in the use of the MLn software, hierarchical modeling has advantages that make it attractive for long-term care multilevel applications such as the drug use study reported here.
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