Risk Factors for Adverse Events in Patients With Breast, Colorectal, and Lung Cancer

JOURNAL OF PATIENT SAFETY(2021)

引用 1|浏览25
暂无评分
摘要
Objective The aim of the study was to identify risk factors associated with medical errors and iatrogenic injuries during an initial course of cancer-directed treatment. Methods In this retrospective cohort study of 400 patients 18 years or older undergoing an initial course of treatment for breast, colorectal, or lung cancer at a comprehensive cancer center, we abstracted patient, disease, and treatment-related variables from the electronic medical record. We examined adverse events (AEs) and preventable AEs by risk factor using the chi(2) or Fisher exact tests. We estimated the association between risk factors and the relative risk of an additional AE or preventable AE in multivariable negative binomial regression models with backwards selection (P < 0.1). Results There were 304 AEs affecting 136 patients (34%) and 97 preventable AEs affecting 53 patients (13%). In multivariable analyses, AEs were overrepresented in those with lung cancer compared with patients with breast cancer (incident rate ratio = 1.9, 95% confidence interval = 1.1-3.2). Nonwhite race (1.6, 1.0-2.6), Hispanic or Latino ethnicity (2.0, 0.9-4.1), advanced disease (1.7, 1.1-2.6), use of each additional class of high-risk nonchemotherapy medication (1.6, 1.3-1.9), and chemotherapy (2.1, 1.3-3.3) were all associated with risk of an additional AE. Preventable AEs were associated with lung cancer (7.4, 2.4-23.2), Hispanic or Latino ethnicity (5.5, 1.7-17.9), and high-risk nonchemotherapy medications (1.5, 1.2-2.0). Conclusions Risk factors for AEs among patients with cancer reflected patients' underlying disease, cancer-directed therapy, and high-risk noncancer medications. The association of AEs with ethnicity merits further research. Risk factor models could be used prospectively to identify patients with cancer at increased risk of harm.
更多
查看译文
关键词
adverse event, medical error, patient safety, oncology, risk factors, epidemiology
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要