Oak Ridge National Laboratory, Oak Ridge, TN, USA.
University of New Mexico School of Medicine, Albuquerque, NM, USA.
BMC Med Inform Decis Mak. 2024 Mar 8;24(1):68. doi: 10.1186/s12911-024-02469-4.
To discover pharmacotherapy prescription patterns and their statistical associations with outcomes through a clinical pathway inference framework applied to real-world data.
We apply machine learning steps in our framework using a 2006 to 2020 cohort of veterans with major depressive disorder (MDD). Outpatient antidepressant pharmacy fills, dispensed inpatient antidepressant medications, emergency department visits, self-harm, and all-cause mortality data were extracted from the Department of Veterans Affairs Corporate Data Warehouse.
Our MDD cohort consisted of 252,179 individuals. During the study period there were 98,417 emergency department visits, 1,016 cases of self-harm, and 1,507 deaths from all causes. The top ten prescription patterns accounted for 69.3% of the data for individuals starting antidepressants at the fluoxetine equivalent of 20-39 mg. Additionally, we found associations between outcomes and dosage change.
For 252,179 Veterans who served in Iraq and Afghanistan with subsequent MDD noted in their electronic medical records, we documented and described the major pharmacotherapy prescription patterns implemented by Veterans Health Administration providers. Ten patterns accounted for almost 70% of the data. Associations between antidepressant usage and outcomes in observational data may be confounded. The low numbers of adverse events, especially those associated with all-cause mortality, make our calculations imprecise. Furthermore, our outcomes are also indications for both disease and treatment. Despite these limitations, we demonstrate the usefulness of our framework in providing operational insight into clinical practice, and our results underscore the need for increased monitoring during critical points of treatment.
通过应用于真实世界数据的临床路径推理框架，发现药物治疗处方模式及其与结果的统计学关联。
我们在框架中应用机器学习步骤，使用 2006 年至 2020 年期间患有重度抑郁症（MDD）的退伍军人队列。从退伍军人事务部企业数据仓库中提取门诊抗抑郁药配药、配给住院抗抑郁药、急诊就诊、自残和全因死亡率数据。
我们的 MDD 队列包括 252179 人。在研究期间，有 98417 次急诊就诊、1016 例自残和 1507 例全因死亡。排名前十的处方模式占开始使用氟西汀等效剂量为 20-39mg 的抗抑郁药的个体数据的 69.3%。此外，我们还发现了结果与剂量变化之间的关联。
对于在伊拉克和阿富汗服役并随后在电子病历中记录有 MDD 的 252179 名退伍军人，我们记录并描述了退伍军人健康管理局提供者实施的主要药物治疗处方模式。十种模式占数据的近 70%。在观察性数据中，抗抑郁药使用与结果之间的关联可能存在混杂。不良事件的数量较少，特别是与全因死亡率相关的不良事件，使得我们的计算不够精确。此外，我们的结果也是疾病和治疗的指征。尽管存在这些局限性，但我们证明了我们的框架在为临床实践提供运营洞察力方面的有用性，并且我们的结果强调了在治疗关键时期需要增加监测。
