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Validation of billing code combinations to identify cardiovascular magnetic resonance imaging scans in Ontario, Canada: a retrospective cohort study.

Authors :
Roifman I
Qiu F
Connelly KA
Wright GA
Farkouh M
Jimenez-Juan L
Wijeysundera HC
Source :
BMJ open [BMJ Open] 2018 Oct 08; Vol. 8 (10), pp. e021370. Date of Electronic Publication: 2018 Oct 08.
Publication Year :
2018

Abstract

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.<br />Design: Retrospective cohort study.<br />Setting: Quaternary care academic referral centre in Ontario, Canada.<br />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.<br />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%).<br />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.<br />Competing Interests: Competing interests: None declared.<br /> (© Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Details

Language :
English
ISSN :
2044-6055
Volume :
8
Issue :
10
Database :
MEDLINE
Journal :
BMJ open
Publication Type :
Academic Journal
Accession number :
30297345
Full Text :
https://doi.org/10.1136/bmjopen-2017-021370