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Validation of billing code combinations to identify cardiovascular magnetic resonance imaging scans in Ontario, Canada: a retrospective cohort study
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6194470/ https://www.ncbi.nlm.nih.gov/pubmed/30297345 http://dx.doi.org/10.1136/bmjopen-2017-021370 |
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author | Roifman, Idan Qiu, Feng Connelly, Kim A Wright, Graham A Farkouh, Michael Jimenez-Juan, Laura Wijeysundera, Harindra C |
author_facet | Roifman, Idan Qiu, Feng Connelly, Kim A Wright, Graham A Farkouh, Michael Jimenez-Juan, Laura Wijeysundera, Harindra C |
author_sort | Roifman, Idan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6194470 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-61944702018-10-24 Validation of billing code combinations to identify cardiovascular magnetic resonance imaging scans in Ontario, Canada: a retrospective cohort study Roifman, Idan Qiu, Feng Connelly, Kim A Wright, Graham A Farkouh, Michael Jimenez-Juan, Laura Wijeysundera, Harindra C BMJ Open Cardiovascular Medicine 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. BMJ Publishing Group 2018-10-08 /pmc/articles/PMC6194470/ /pubmed/30297345 http://dx.doi.org/10.1136/bmjopen-2017-021370 Text en © 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. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Cardiovascular Medicine Roifman, Idan Qiu, Feng Connelly, Kim A Wright, Graham A Farkouh, Michael Jimenez-Juan, Laura Wijeysundera, Harindra C Validation of billing code combinations to identify cardiovascular magnetic resonance imaging scans in Ontario, Canada: a retrospective cohort study |
title | Validation of billing code combinations to identify cardiovascular magnetic resonance imaging scans in Ontario, Canada: a retrospective cohort study |
title_full | Validation of billing code combinations to identify cardiovascular magnetic resonance imaging scans in Ontario, Canada: a retrospective cohort study |
title_fullStr | Validation of billing code combinations to identify cardiovascular magnetic resonance imaging scans in Ontario, Canada: a retrospective cohort study |
title_full_unstemmed | Validation of billing code combinations to identify cardiovascular magnetic resonance imaging scans in Ontario, Canada: a retrospective cohort study |
title_short | Validation of billing code combinations to identify cardiovascular magnetic resonance imaging scans in Ontario, Canada: a retrospective cohort study |
title_sort | validation of billing code combinations to identify cardiovascular magnetic resonance imaging scans in ontario, canada: a retrospective cohort study |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6194470/ https://www.ncbi.nlm.nih.gov/pubmed/30297345 http://dx.doi.org/10.1136/bmjopen-2017-021370 |
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