Department of Medical Informatics, School of Community Medicine, University of Oklahoma Health Sciences Center, Tulsa.
Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City.
JAMA Netw Open. 2020 Jul 1;3(7):e209411. doi: 10.1001/jamanetworkopen.2020.9411.
Cardiovascular disease is the leading cause of death in the United States. To improve cardiovascular outcomes, primary care must have valid methods of assessing performance on cardiovascular clinical quality measures, including aspirin use (aspirin measure), blood pressure control (BP measure), and smoking cessation counseling and intervention (smoking measure).
To compare observed performance scores measured using 2 imperfect reference standard data sources (medical record abstraction [MRA] and electronic health record [EHR]-generated reports) with misclassification-adjusted performance scores obtained using bayesian latent class analysis.
DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used a subset of the 2016 aspirin, BP, and smoking performance data from the Healthy Hearts for Oklahoma Project. Each clinical quality measure was calculated for a subset of a practice's patient population who can benefit from recommended care (ie, the eligible population). A random sample of 380 eligible patients were included for the aspirin measure; 126, for the BP measure; and 115, for the smoking measure. Data were collected from 21 primary care practices belonging to a single large health care system from January 1 to December 31, 2018, and analyzed from February 21 to April 17, 2019.
The main outcomes include performance scores for the aspirin, BP, and smoking measures using imperfect MRA and EHRs and estimated through bayesian latent class models.
A total of 621 eligible patients were included in the analysis. Based on MRA and EHR data, observed aspirin performance scores were 76.0% (95% bayesian credible interval [BCI], 71.5%-80.1%) and 74.9% (95% BCI, 70.4%-79.1%), respectively; observed BP performance scores, 80.6% (95% BCI, 73.2%-86.9%) and 75.1% (95% BCI, 67.2%-82.1%), respectively; and observed smoking performance scores, 85.7% (95% BCI, 78.6%-91.2%) and 75.4% (95% BCI, 67.0%-82.6%), respectively. Misclassification-adjusted estimates were 74.9% (95% BCI, 70.5%-79.1%) for the aspirin performance score, 75.0% (95% BCI, 66.6%-82.5%) for the BP performance score, and 83.0% (95% BCI, 74.4%-89.8%) for the smoking performance score.
Ensuring valid performance measurement is critical for value-based payment models and quality improvement activities in primary care. This study found that extracting information for the same individuals using different data sources generated different performance score estimates. Further research is required to identify the sources of these differences.
心血管疾病是美国的主要死因。为了改善心血管结果，初级保健必须有有效的方法来评估心血管临床质量措施的表现，包括使用阿司匹林（阿司匹林措施）、控制血压（BP 措施）和戒烟咨询和干预（吸烟措施）。
将使用 2 种不完美参考标准数据源（病历摘录 [MRA]和电子健康记录 [EHR]生成的报告）测量的观察绩效得分与使用贝叶斯潜在类别分析获得的经分类调整的绩效得分进行比较。
设计、设置和参与者：这项横断面研究使用了 2016 年俄克拉荷马州健康心脏项目中阿司匹林、BP 和吸烟表现数据的一个子集。每个临床质量措施都针对可从推荐护理中受益的实践患者人群（即合格人群）的一部分进行计算。阿司匹林措施纳入了 380 名合格患者的随机样本；BP 措施纳入了 126 名合格患者；吸烟措施纳入了 115 名合格患者。数据于 2018 年 1 月 1 日至 12 月 31 日从属于一个单一大型医疗保健系统的 21 个初级保健实践中收集，并于 2019 年 2 月 21 日至 4 月 17 日进行分析。
主要结果包括使用不完美的 MRA 和 EHR 以及通过贝叶斯潜在类别模型估计的阿司匹林、BP 和吸烟措施的表现得分。
共纳入 621 名合格患者进行分析。根据 MRA 和 EHR 数据，观察到的阿司匹林表现得分分别为 76.0%（95%贝叶斯可信区间 [BCI]，71.5%-80.1%）和 74.9%（95%BCI，70.4%-79.1%）；观察到的 BP 表现得分分别为 80.6%（95%BCI，73.2%-86.9%）和 75.1%（95%BCI，67.2%-82.1%）；观察到的吸烟表现得分分别为 85.7%（95%BCI，78.6%-91.2%）和 75.4%（95%BCI，67.0%-82.6%）。阿司匹林表现得分的经分类调整估计值为 74.9%（95%BCI，70.5%-79.1%），BP 表现得分的经分类调整估计值为 75.0%（95%BCI，66.6%-82.5%），吸烟表现得分的经分类调整估计值为 83.0%（95%BCI，74.4%-89.8%）。
确保有效的绩效衡量对于初级保健中的基于价值的支付模式和质量改进活动至关重要。本研究发现，使用不同数据源为同一人群提取信息会产生不同的绩效得分估计。需要进一步研究以确定这些差异的来源。
