University of Michigan, Department of Neurology, Ann Arbor, MI 48109, USA; University of Michigan, Institute for Healthcare Policy and Innovation, Ann Arbor, MI 48109, USA.
University of Michigan, Institute for Healthcare Policy and Innovation, Ann Arbor, MI 48109, USA; Department of General Internal Medicine, Bern University Hospital, Inselspital, University of Bern, Bern, Switzerland; Institute of Primary Health Care (BIHAM), University of Bern, Switzerland; Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI 48109, USA.
Epilepsy Behav. 2022 Jan;126:108428. doi: 10.1016/j.yebeh.2021.108428. Epub 2021 Dec 1.
To describe polypharmacy composition, and the degree to which patients versus providers contribute to variation in medication fills, in people with epilepsy.
We performed a retrospective study of Medicare beneficiaries with epilepsy (antiseizure medication plus diagnostic codes) in 2014 (N = 78,048). We described total number of medications and prescribers, and specific medications. Multilevel models evaluated the percentage of variation in two outcomes (1. number of medications per patient-provider dyad, and 2. whether a medication was filled within thirty days of a visit) due to patient-to-patient differences versus provider-to-provider differences.
Patients filled a median of 12 (interquartile range [IQR] 8-17) medications, from median of 5 (IQR 3-7) prescribers. Twenty-two percent filled an opioid, and 61% filled at least three central nervous system medications. Levetiracetam was the most common medication (40%), followed by hydrocodone/acetaminophen (27%). The strongest predictor of medications per patient was Charlson comorbidity index (7.5 [95% confidence interval (CI) 7.2-7.8] additional medications for index 8+ versus 0). Provider-to-provider variation explained 36% of variation in number of medications per patient, whereas patient-to-patient variation explained only 2% of variation. Provider-to-provider variation explained 57% of variation in whether a patient filled a medication within 30 days of a visit, whereas patient-to-patient variation explained only 30% of variation.
Patients with epilepsy fill a large number of medications from a large number of providers, including high-risk medications. Variation in medication fills was substantially more related to provider-to-provider rather than patient-to-patient variation. The better understanding of drivers of high-prescribing practices may reduce avoidable medication-related harms.
描述癫痫患者的多种药物治疗方案组成,以及患者和医生在药物治疗方案中的差异对药物使用的影响。
我们对 2014 年医疗保险受益人群中患有癫痫(抗癫痫药物加诊断代码)的患者(n=78048)进行了回顾性研究。我们描述了患者使用药物的种类和数量,以及具体的药物种类。多水平模型评估了两种结果(1. 每个患者-医生组合中药物的数量;2. 药物是否在就诊后 30 天内开具)的患者间差异和医生间差异对结果的影响程度。
患者平均使用了 12 种(四分位间距[IQR]8-17)药物,来自 5 位(IQR 3-7)医生。22%的患者使用了阿片类药物,61%的患者使用了至少三种中枢神经系统药物。左乙拉西坦是最常用的药物(40%),其次是氢可酮/对乙酰氨基酚(27%)。预测患者使用药物种类的最强因素是 Charlson 合并症指数(指数 8+的患者比指数 0 的患者多使用 7.5[95%置信区间(CI)7.2-7.8]种药物)。医生间差异解释了患者使用药物数量的 36%的变异,而患者间差异仅解释了 2%的变异。医生间差异解释了患者是否在就诊后 30 天内开具药物的 57%的变异,而患者间差异仅解释了 30%的变异。
癫痫患者使用了大量的药物,这些药物来自大量的医生,包括高风险的药物。药物使用的差异主要与医生间的差异有关,而不是患者间的差异。更好地了解导致高处方率的因素可能会减少可避免的药物相关伤害。