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Validity of Medical Record Abstraction and Electronic Health Record-Generated Reports to Assess Performance on
Juell Homco1,2, Hélène Carabin2,3,4,5, Zsolt Nagykaldi6
1Department of Medical Informatics, School of Community Medicine, University of Oklahoma Health Sciences Center, Tulsa.
Insights
Comparing data sources for cardiovascular quality measures revealed discrepancies in performance scores. Validating these measures is crucial for improving primary care outcomes and value-based payment models.
Area of Science:
- Primary Care Research
- Health Services Research
- Quality Improvement Science
Background:
- Cardiovascular disease (CVD) is a leading cause of mortality in the US.
- Accurate performance measurement is essential for improving CVD outcomes in primary care.
- Key quality measures include aspirin use, blood pressure control, and smoking cessation interventions.
Purpose of the Study:
- To compare performance scores derived from medical record abstraction (MRA) and electronic health record (EHR)-generated reports.
- To evaluate the impact of data source discrepancies on cardiovascular quality measure performance.
- To apply Bayesian latent class analysis for misclassification-adjusted performance scores.
Main Methods:
- A cross-sectional study analyzed data from 21 primary care practices.
- Performance scores were calculated for aspirin, blood pressure, and smoking measures using MRA and EHR data.
- Bayesian latent class analysis was used to adjust for potential misclassification errors.
Main Results:
- Observed performance scores varied between MRA and EHR data sources for all measures.
- Misclassification-adjusted scores provided a refined estimate of performance.
- Aspirin measure scores ranged from 74.9% to 76.0%, BP control from 75.1% to 80.6%, and smoking cessation from 75.4% to 85.7%.
Conclusions:
- Different data sources yield different performance score estimates for cardiovascular quality measures.
- Valid performance measurement is critical for value-based care and quality improvement initiatives.
- Further research is needed to understand and reconcile discrepancies between data sources.
Importance:
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).
Objective:
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.
Main Outcomes And Measures:
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.
Results:
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.
Conclusions And Relevance:
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.
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