Predictors of antipsychotic medication change

被引:8
|
作者
Sernyak, MJ
Leslie, D
Rosenheck, R
机构
[1] Yale Univ, Sch Med, Dept Psychiat, New Haven, CT USA
[2] VA NE Program Evaluat Ctr, New Haven, CT USA
[3] Yale Univ, Dept Psychiat, Sch Epidemiol & Publ Hlth, New Haven, CT 06520 USA
[4] Bristol Myers Squibb Co, New York, NY 10154 USA
来源
关键词
Schizophrenia; Health Promotion; Powerful Predictor; Clinical Variable; Service Utilization;
D O I
10.1007/BF02287330
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Atypical antipsychotics account for more than 60% of antipsychotic prescriptions written for the treatment of schizophrenia. While switching front one antipsychotic to another is a dynamic process, there has been no research on individual patient and institutional characteristics that predict antipsychotic switching. VA national administrative data were used to identify patients (it = 9660) with schizophrenia maintained on antipsychotic medication. Logistic regression was used to identify predictors of medication switching. Independent variables included information about service utilization, sociodemographic and clinical variables as well as institutional characteristics. This model was repeated for more specific switches between classes of medications and between specific medications. High levels of outpatient and inpatient service use were the most powerful predictors of switching. Sociodemographic, institutional, diagnostic, and functional measures were also predictive in some cases. Controlling for independent sociodemographic, diagnostic, and functional measures, frequency of clinical contact was the most robust predictor of switching antipsychotics.
引用
收藏
页码:85 / 94
页数:10
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