A Bayesian hierarchical model for characterizing the diffusion of new antipsychotic drugs.
A Bayesian hierarchical model for characterizing the diffusion of new antipsychotic drugs.
复制标题
表征新型抗精神病药物扩散的贝叶斯层次模型。
DOI:
10.1111/biom.13324
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发表时间:
2021-06
期刊:
影响因子:
1.9
通讯作者:
Normand SL
中科院分区:
文献类型:
--
作者:
Gu C;Huskamp H;Donohue J;Normand SL
New prescription medications are a primary driver of spending growth in the United States. For patients with severe mental illnesses, second generation antipsychotic (SGA) medications feature prominently. However, many SGAs are costly, particularly before generic entry, and some may increase the risk of diabetes. Because physicians play a prominent role in new prescription adoption, understanding their prescribing behaviors is policy-relevant. Several features of prescription data, such as different antipsychotic choice sets over time, variable physician prescription volumes, and correlation among drug choices within physicians, complicate inferences. We propose a multivariate Bayesian hierarchical model with piecewise random effects to characterize the diffusion of new antipsychotic drugs. This model captures the complex prescriber-specific relationships among the different diffusion processes and takes advantage of the Bayesian paradigm to quantify uncertainty for all parameters straightforwardly. To evaluate the prescribing patterns for each physician, we propose various indices to identify early new SGA adopters. A sample of nearly 17,000 U.S. physicians whose antipsychotic drug prescribing information was collected between January 1, 1997 and December 31, 2007 illustrates the methods. Determinants of high prescription rates and adoption speeds of new SGAs included physician sex, age, hospital affiliation, physician specialty, and office location. Large within- and between-provider variations in prescribing patterns of new SGAs were identified. Early adopters for one drug were not early adopters for another drug.
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DOI:
10.1176/appi.ps.201200186
发表时间:
2013-04-01
期刊:
Psychiatric services (Washington, D.C.)
影响因子:
--
作者:
Huskamp HA;O'Malley AJ;Horvitz-Lennon M;Taub AL;Berndt ER;Donohue JM
通讯作者:
Donohue JM
影响因子:
3.8
作者:
Slade, Eric P.;Simoni-Wastila, Linda
通讯作者:
Simoni-Wastila, Linda
DOI:
10.1016/j.hjdsi.2017.09.004
发表时间:
2018-03
期刊:
Healthcare (Amsterdam, Netherlands)
影响因子:
--
作者:
Anderson TS;Lo-Ciganic WH;Gellad WF;Zhang R;Huskamp HA;Choudhry NK;Chang CH;Richards-Shubik S;Guclu H;Jones B;Donohue JM
通讯作者:
Donohue JM
影响因子:
2.4
作者:
Ruppert, D
通讯作者:
Ruppert, D
影响因子:
3.7
作者:
Normand, SLT;Glickman, ME;Gatsonis, CA
通讯作者:
Gatsonis, CA