Validation of billing code combinations to identify cardiovascular magnetic resonance imaging scans in Ontario,
Idan Roifman1,2,3, Feng Qiu3, Kim A Connelly1,4
1Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.
Insights
Researchers identified an optimal billing code combination to accurately identify patients who received cardiovascular magnetic resonance (CMR) imaging in Ontario administrative data. This facilitates large-scale population studies using this gold-standard heart function assessment tool.
Area of Science:
- Cardiology
- Medical Imaging
- Health Informatics
Background:
- Cardiovascular magnetic resonance (CMR) imaging is the gold-standard for assessing heart function.
- Lack of specific billing codes in administrative databases hinders large-scale 'big data' CMR studies.
- Accurate identification of CMR patients in administrative data is crucial for research.
Purpose of the Study:
- To identify the optimal billing code combination for detecting patients who underwent CMR.
- To enable robust population-based cardiovascular magnetic resonance studies using administrative data in Ontario.
Main Methods:
- Retrospective cohort study at a quaternary care academic referral center in Ontario, Canada.
- Tested all billing code combinations to identify the optimal one for determining CMR receipt.
- Gold standard: List of cardiothoracic magnetic resonance scans (2014-2016) verified by chart audit.
Main Results:
- The study analyzed 2339 thoracic MRIs; 2139 (91.5%) were CMRs.
- The optimal billing code combination achieved 95.3% accuracy.
- High sensitivity (97.4%) and positive predictive value (96.9%) were observed for CMR identification.
Conclusions:
- This study is the first to validate accurate identification of CMR using administrative data.
- The identified billing code combination enhances the feasibility of future population-based CMR research.
- Improved data identification will support more comprehensive studies on cardiovascular magnetic resonance.
Objectives:
Cardiovascular magnetic resonance (CMR) imaging is the gold-standard test for the assessment of heart function. Despite its importance, many jurisdictions lack specific billing codes that can be used to identify patient receipt of CMR in administrative databases, limiting the ability to perform 'big data' CMR studies. Our objective was to identify the optimal billing code combination to identify patients who underwent CMR using administrative data in Ontario.
Design:
Retrospective cohort study.
Setting:
Quaternary care academic referral centre in Ontario, Canada.
Participants:
We tested all billing code combinations in order to identify the optimal one to determine receipt of CMR. The reference gold standard was a list of all cardiothoracic magnetic resonance scans performed at Sunnybrook Health Sciences Centre between 1 January 2014 and 31 December 2016, verified by chart audit. We assessed the diagnostic performance (accuracy, sensitivity, specificity, positive predictive value and negative predictive value) for all code combinations.
Results:
Our gold-standard cohort consisted of 2339 thoracic MRIs that were performed at Sunnybrook Health Sciences Centre from 1 January 2014 to 31 December 2016. Of these, 2139 (91.5%) were CMRs and 200 (8.5%) were chest MRIs. We identified the most accurate billing combination for the determination of patient receipt of CMR. This combination resulted in an accuracy of 95.3% (95% CI 94.4% to 96.2%), sensitivity of 97.4% (95% CI 96.6% to 98.1%), specificity of 86.4% (95% CI 83.1% to 89.6%), positive predictive value of 96.9% (95% CI 96.1% to 97.6%) and negative predictive value of 88.4% (95% CI 85.4% to 91.5%).
Conclusions:
Our study is the first to verify the ability to accurately identify patient receipt of CMR using administrative data, facilitating more robust population-based CMR studies in the future.
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