University of Michigan, 3550 Rackham, Ann Arbor, MI 48109-1070.
J Manag Care Spec Pharm. 2015 May;21(5):424-30. doi: 10.18553/jmcp.2015.21.5.424.
In usual psychiatric care, antidepressant treatments are selected based on physician and patient preferences rather than being randomly allocated, resulting in spurious associations between these treatments and outcome studies.
To identify factors recorded in electronic medical chart progress notes predictive of antidepressant selection among patients who had received a depression diagnosis.
This retrospective study sample consisted of 556 randomly selected Veterans Health Administration patients diagnosed with depression from April 1, 1999, to September 30, 2004, stratified by the antidepressant agent, geographic region, gender, and year of depression cohort entry. Predictors were obtained from administrative data, and additional variables were abstracted from electronic medical chart notes in the year prior to the start of the antidepressant in 5 categories: clinical symptoms and diagnoses, substance use, life stressors, behavioral/ideation measures (e.g., suicide attempts), and treatments received. Multinomial logistic regression analysis was used to assess the predictors associated with different antidepressant prescribing, and adjusted relative risk ratios (RRR) were reported.
Of the administrative data-based variables, gender, age, illicit drug abuse or dependence, and number of psychiatric medications in the prior year were significantly associated with antidepressant selection. After adjusting for administrative data-based variables, sleep problems (relative risk ratio [RRR] = 2.47) or marital issues (RRR = 2.64) identified in the charts were significantly associated with prescribing mirtazapine rather than sertraline; however, no other chart-based variables showed a significant association or an association with a large magnitude.
Some chart data-based variables were predictive of antidepressant selection, but we neither found many nor found them highly predictive of antidepressant selection in patients treated for depression.
在常规精神科护理中，抗抑郁治疗是基于医生和患者的偏好选择，而不是随机分配，这导致这些治疗方法与结果研究之间存在虚假关联。
确定电子病历进展记录中记录的因素，这些因素可预测在接受抑郁症诊断的患者中选择抗抑郁药物。
本回顾性研究的样本包括 556 名随机选择的退伍军人健康管理局患者，他们在 1999 年 4 月 1 日至 2004 年 9 月 30 日期间被诊断为抑郁症，按抗抑郁药物、地理位置、性别和抑郁症队列进入年份分层。预测因子从行政数据中获得，在开始使用抗抑郁药物前一年的电子病历记录中提取了其他五个类别的额外变量：临床症状和诊断、物质使用、生活压力源、行为/观念测量（例如，自杀企图）和接受的治疗。使用多项逻辑回归分析评估与不同抗抑郁药物处方相关的预测因子，并报告调整后的相对风险比（RRR）。
在基于行政数据的变量中，性别、年龄、非法药物滥用或依赖以及前一年的精神药物数量与抗抑郁药物的选择显著相关。在调整基于行政数据的变量后，在图表中发现的睡眠问题（RRR=2.47）或婚姻问题（RRR=2.64）与开米氮平而非舍曲林的处方显著相关；然而，没有其他基于图表的变量显示出显著的关联或具有大的关联。
一些基于图表数据的变量可以预测抗抑郁药物的选择，但我们既没有发现很多，也没有发现它们对接受抑郁症治疗的患者的抗抑郁药物选择具有高度预测性。
