Huang Zhong, Jack Matthew, O'Leary Kevin J, Nutescu Edith A, Chen Thomas, Ruhnke Gregory W, George David, House Larry K, Knoebel Randall, Hartman Seth, Choksi Anish, Yeo Kiang-Teck J, Perera Minoli A, Ratain Mark J, Meltzer David O, O'Donnell Peter H
Pritzker School of Medicine, The University of Chicago, Chicago, Illinois, USA.
Center for Personalized Therapeutics, The University of Chicago, Chicago, Illinois, USA.
Clin Transl Sci. 2025 Apr;18(4):e70193. doi: 10.1111/cts.70193.
Medication prescribing is imperfect, and unintended side effects complicate patient care. Pharmacogenomics (PGx) is an emerging solution that associates genotypes with personalized drug-related outcomes, but it has not been widely adopted. We hypothesize that patient and provider attributes may predict and promote PGx utilization. We studied PGx using data from the ACCOuNT study, a multi-institutional prospective trial that implemented broad preemptive PGx result delivery for African American inpatients [Clinicaltrials.gov NCT03225820]. Patients were genotyped, and their PGx information was made available within an integrated informatics portal. Utilization of PGx data (defined as the active choice to review PGx information) was left to the enrolled provider's discretion. Our primary endpoint was to identify patient and care team attributes associated with PGx use. We identified statistically significant univariate predictors and utilized logistic regression to compare relative predictiveness. This study included 187 patients (60.4% female, median age 55, 75.4% treated at the University of Chicago, 17.6% at Northwestern University, and 7.0% at the University of Illinois Chicago) and 188 providers (63.8% MD, 22.3% PharmD, 6.4% PA, and 7.4% APN). In multivariate analysis, we found that the use of PGx information in a prior admission significantly predicted the use in subsequent admissions (OR 7.62, p < 0.05). Similarly, pharmacist participation on care teams significantly predicted PGx use (OR 4.52, p < 0.05). In the first systematic analysis of the impact of patient and care team factors on inpatient PGx clinical decision support (CDS) adoption, we found that actionable care team attributes, such as pharmacist participation or successful initial adoption measures, predict PGx CDS use.
药物处方并不完美,意外的副作用使患者护理变得复杂。药物基因组学(PGx)是一种新兴的解决方案,它将基因型与个性化的药物相关结果联系起来,但尚未得到广泛应用。我们假设患者和医疗服务提供者的属性可能预测并促进PGx的使用。我们使用ACCOuNT研究的数据来研究PGx,这是一项多机构前瞻性试验,为非裔美国住院患者实施了广泛的前瞻性PGx结果传递[Clinicaltrials.gov NCT03225820]。对患者进行基因分型,并在综合信息学门户网站中提供他们的PGx信息。PGx数据的使用(定义为主动选择查看PGx信息)由参与的医疗服务提供者自行决定。我们的主要终点是确定与PGx使用相关的患者和护理团队属性。我们确定了具有统计学意义的单变量预测因素,并使用逻辑回归来比较相对预测能力。本研究包括187名患者(60.4%为女性,中位年龄55岁,75.4%在芝加哥大学接受治疗,17.6%在西北大学,7.0%在伊利诺伊大学芝加哥分校)和188名医疗服务提供者(63.8%为医学博士,22.3%为药学博士,6.4%为执业助理医师,7.4%为高级实践护士)。在多变量分析中,我们发现先前住院时使用PGx信息显著预测了后续住院时的使用情况(比值比7.62,p<0.05)。同样,药剂师参与护理团队也显著预测了PGx的使用(比值比4.52,p<0.05)。在对患者和护理团队因素对住院患者PGx临床决策支持(CDS)采用的影响进行的首次系统分析中,我们发现可采取行动的护理团队属性,如药剂师的参与或成功的初始采用措施,可预测PGx CDS的使用。