BACKGROUND: Use of atypical antipsychotics for "off-label" indications, such as behavioral and psychological symptoms of dementia, depression, and bipolar disorder, have been frequently reported, although not systematically studied. We describe the pattern of atypical antipsychotic use among nursing home residents and identify demographic and clinical correlates. METHOD: We conducted a cross-sectional study on 139,714 nursing home residents living in 1732 nursing homes in 5 U.S. states from Jan. 1, 1999, to Jan. 31, 2000. Data were obtained from the computerized Minimum Data Set (MDS) assessment records. RESULTS: Behavior problems associated with cognitive impairment were manifest in 86,514 residents, and, of these, 18.2% received an antipsychotic. Approximately 11% received an atypical antipsychotic, while 6.8% received a conventional agent. Clinical correlates of atypical antipsychotic use were Parkinson's disease (adjusted odds ratio [OR] = 1.57, 95% confidence interval [CI] = 1.34 to 1.84), depression (OR = 1.35, 95% CI = 1.24 to 1.46), antidepressant use (OR = 1.38, 95% CI = 1.27 to 1.49), Alzheimer's disease (OR = 1.21, 95% CI = 1.12 to 1.32), non-Alzheimer dementia (OR = 1.15, 95% CI = 1.07 to 1.24), and cholinesterase inhibitor use (OR = 1.74, 95% CI = 1.52 to 1.98). Severe functional impairment was inversely related to atypical antipsychotic use (OR = 0.76, 95% CI = 0.65 to 0.89). CONCLUSION: Atypical antipsychotics are now used more than conventional antipsychotic agents in U.S. nursing homes. Indications and dosages seem appropriate relative to labeling. Clinical and demographic differences between atypical and conventional antipsychotic users tend to be relatively small, suggesting that other factors may explain the choice of prescribing physicians. The impact of facility factors, economic forces, and physician characteristics needs to be investigated.
BACKGROUND: Use of atypical antipsychotics for "off-label" indications, such as behavioral and psychological symptoms of dementia, depression, and bipolar disorder, have been frequently reported, although not systematically studied. We describe the pattern of atypical antipsychotic use among nursing home residents and identify demographic and clinical correlates. METHOD: We conducted a cross-sectional study on 139,714 nursing home residents living in 1732 nursing homes in 5 U.S. states from Jan. 1, 1999, to Jan. 31, 2000. Data were obtained from the computerized Minimum Data Set (MDS) assessment records. RESULTS: Behavior problems associated with cognitive impairment were manifest in 86,514 residents, and, of these, 18.2% received an antipsychotic. Approximately 11% received an atypical antipsychotic, while 6.8% received a conventional agent. Clinical correlates of atypical antipsychotic use were Parkinson's disease (adjusted odds ratio [OR] = 1.57, 95% confidence interval [CI] = 1.34 to 1.84), depression (OR = 1.35, 95% CI = 1.24 to 1.46), antidepressant use (OR = 1.38, 95% CI = 1.27 to 1.49), Alzheimer's disease (OR = 1.21, 95% CI = 1.12 to 1.32), non-Alzheimer dementia (OR = 1.15, 95% CI = 1.07 to 1.24), and cholinesterase inhibitor use (OR = 1.74, 95% CI = 1.52 to 1.98). Severe functional impairment was inversely related to atypical antipsychotic use (OR = 0.76, 95% CI = 0.65 to 0.89). CONCLUSION: Atypical antipsychotics are now used more than conventional antipsychotic agents in U.S. nursing homes. Indications and dosages seem appropriate relative to labeling. Clinical and demographic differences between atypical and conventional antipsychotic users tend to be relatively small, suggesting that other factors may explain the choice of prescribing physicians. The impact of facility factors, economic forces, and physician characteristics needs to be investigated.
Authors: Jennifer Tjia; Sarah L Cutrona; Daniel Peterson; George Reed; Susan E Andrade; Susan L Mitchell Journal: J Am Geriatr Soc Date: 2014-11-04 Impact factor: 5.562
Authors: Krista F Huybrechts; M Alan Brookhart; Kenneth J Rothman; Rebecca A Silliman; Tobias Gerhard; Stephen Crystal; Sebastian Schneeweiss Journal: Am J Epidemiol Date: 2011-09-20 Impact factor: 4.897
Authors: Joseph T Hanlon; Xiaoqiang Wang; Nicholas G Castle; Roslyn A Stone; Steven M Handler; Todd P Semla; Mary Jo Pugh; Dan R Berlowitz; Maurice W Dysken Journal: J Am Geriatr Soc Date: 2011-08-08 Impact factor: 5.562