Department of Medicine, University of Washington School of Medicine, 4245 Roosevelt Way NE, Seattle, WA 98105. Email:
Am J Manag Care. 2023 Sep 1;29(9):439-447. doi: 10.37765/ajmc.2023.89354. Epub 2023 May 1.
To identify factors associated with the minimum necessary information to determine an individual’s eligibility for lung cancer screening (ie, sufficient risk factor documentation) and to characterize clinic-level variability in documentation.
Cross-sectional observational study using electronic health record data from an academic health system in 2019.
We calculated the relative risk of sufficient lung cancer risk factor documentation by patient-, provider-, and system-level variables using Poisson regression models, clustering by clinic. We compared unadjusted, risk-adjusted, and reliability-adjusted proportions of patients with sufficient smoking documentation across 31 clinics using logistic regression models and 2-level hierarchical logit models to estimate reliability-adjusted proportions across clinics.
Among 20,632 individuals, 60% had sufficient risk factor documentation to determine screening eligibility. Patient-level factors inversely associated with risk factor documentation included Black race (relative risk [RR], 0.70; 95% CI, 0.60-0.81), non-English preferred language (RR, 0.60; 95% CI, 0.49-0.74), Medicaid insurance (RR, 0.64; 95% CI, 0.57-0.71), and nonactivated patient portal (RR, 0.85; 95% CI, 0.80-0.90). Documentation varied across clinics. The reliability-adjusted intraclass correlation coefficient decreased from 11.0% (95% CI, 6.9%-17.1%) to 5.3% (95% CI, 3.2%-8.6%), adjusting for covariates.
We found a low rate of sufficient lung cancer risk factor documentation and associations of risk factor documentation based on patient-level factors such as race, insurance status, language, and patient portal activation. Risk factor documentation rates varied across clinics, and only approximately half the variation was explained by factors in our analysis.
确定与确定个体是否有资格进行肺癌筛查所需的最低必要信息（即，有足够的风险因素记录）相关的因素，并描述记录方面的临床差异。
使用 2019 年某学术医疗系统的电子健康记录数据进行的横断面观察性研究。
我们使用泊松回归模型，根据患者、提供者和系统水平的变量计算有足够肺癌风险因素记录的相对风险，通过诊所进行聚类。我们使用逻辑回归模型和 2 级层次逻辑模型比较了 31 家诊所中无调整、风险调整和可靠性调整后有足够吸烟记录的患者比例，以估计诊所间的可靠性调整后比例。
在 20632 名个体中，有 60%的人有足够的风险因素记录来确定筛查资格。与风险因素记录呈负相关的患者水平因素包括：黑人种族（相对风险 [RR]，0.70；95%置信区间 [CI]，0.60-0.81）、非英语首选语言（RR，0.60；95%CI，0.49-0.74）、医疗补助保险（RR，0.64；95%CI，0.57-0.71）和未激活的患者门户（RR，0.85；95%CI，0.80-0.90）。记录在各个诊所之间存在差异。在调整协变量后，可靠性调整后的组内相关系数从 11.0%（95%CI，6.9%-17.1%）降至 5.3%（95%CI，3.2%-8.6%）。
我们发现，有足够的肺癌风险因素记录的比例较低，并且风险因素记录与患者水平因素（如种族、保险状况、语言和患者门户激活）有关。记录风险因素的比例在各个诊所之间存在差异，而我们分析中的因素仅能解释其中的一半左右。
