Identifying patient subgroups who benefit most from a treatment: using administrative claims data to uncover treatment heterogeneity.
作者： M. Haim Erder , James E. Signorovitch , Juliana Setyawan , Hongbo Yang , Kejal Parikh
DOI: 10.3111/13696998.2012.689270
关键词:
摘要: AbstractObjectives:To illustrate how claims data can be used to (1) develop outcome scores that predict response a traditional treatment and (2) estimate the economic impact of individualized assignment newer based on score. An example application is two treatments for attention deficit hyperactivity disorder (ADHD): osmotic-release oral system methylphenidate (OROS-MPH) lisdexamfetamine dimesylate (LDX).Methods:Adolescents with ADHD initiating OROS-MPH (n = 6320) or LDX (n = 6394) were selected from MarketScan database. A model was developed predicting risk switching/augmentation using multiple baseline characteristics. The applied an independent sample stratify patients by their predicted and, within each stratum, ADHD-related total costs compared between inverse probability weighting.Results:The prediction resulted in ...
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