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Validity of Physician Billing Claims to Identify Deceased Organ Donors in Large Healthcare Databases

OBJECTIVE: We evaluated the validity of physician billing claims to identify deceased organ donors in large provincial healthcare databases. METHODS: We conducted a population-based retrospective validation study of all deceased donors in Ontario, Canada from 2006 to 2011 (n = 988). We included all...

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Autores principales: Li, Alvin Ho-ting, Kim, S. Joseph, Rangrej, Jagadish, Scales, Damon C., Shariff, Salimah, Redelmeier, Donald A., Knoll, Greg, Young, Ann, Garg, Amit X.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3743842/
https://www.ncbi.nlm.nih.gov/pubmed/23967114
http://dx.doi.org/10.1371/journal.pone.0070825
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author Li, Alvin Ho-ting
Kim, S. Joseph
Rangrej, Jagadish
Scales, Damon C.
Shariff, Salimah
Redelmeier, Donald A.
Knoll, Greg
Young, Ann
Garg, Amit X.
author_facet Li, Alvin Ho-ting
Kim, S. Joseph
Rangrej, Jagadish
Scales, Damon C.
Shariff, Salimah
Redelmeier, Donald A.
Knoll, Greg
Young, Ann
Garg, Amit X.
author_sort Li, Alvin Ho-ting
collection PubMed
description OBJECTIVE: We evaluated the validity of physician billing claims to identify deceased organ donors in large provincial healthcare databases. METHODS: We conducted a population-based retrospective validation study of all deceased donors in Ontario, Canada from 2006 to 2011 (n = 988). We included all registered deaths during the same period (n = 458,074). Our main outcome measures included sensitivity, specificity, positive predictive value, and negative predictive value of various algorithms consisting of physician billing claims to identify deceased organ donors and organ-specific donors compared to a reference standard of medical chart abstraction. RESULTS: The best performing algorithm consisted of any one of 10 different physician billing claims. This algorithm had a sensitivity of 75.4% (95% CI: 72.6% to 78.0%) and a positive predictive value of 77.4% (95% CI: 74.7% to 80.0%) for the identification of deceased organ donors. As expected, specificity and negative predictive value were near 100%. The number of organ donors identified by the algorithm each year was similar to the expected value, and this included the pre-validation period (1991 to 2005). Algorithms to identify organ–specific donors performed poorly (e.g. sensitivity ranged from 0% for small intestine to 67% for heart; positive predictive values ranged from 0% for small intestine to 37% for heart). INTERPRETATION: Primary data abstraction to identify deceased organ donors should be used whenever possible, particularly for the detection of organ-specific donations. The limitations of physician billing claims should be considered whenever they are used.
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spelling pubmed-37438422013-08-21 Validity of Physician Billing Claims to Identify Deceased Organ Donors in Large Healthcare Databases Li, Alvin Ho-ting Kim, S. Joseph Rangrej, Jagadish Scales, Damon C. Shariff, Salimah Redelmeier, Donald A. Knoll, Greg Young, Ann Garg, Amit X. PLoS One Research Article OBJECTIVE: We evaluated the validity of physician billing claims to identify deceased organ donors in large provincial healthcare databases. METHODS: We conducted a population-based retrospective validation study of all deceased donors in Ontario, Canada from 2006 to 2011 (n = 988). We included all registered deaths during the same period (n = 458,074). Our main outcome measures included sensitivity, specificity, positive predictive value, and negative predictive value of various algorithms consisting of physician billing claims to identify deceased organ donors and organ-specific donors compared to a reference standard of medical chart abstraction. RESULTS: The best performing algorithm consisted of any one of 10 different physician billing claims. This algorithm had a sensitivity of 75.4% (95% CI: 72.6% to 78.0%) and a positive predictive value of 77.4% (95% CI: 74.7% to 80.0%) for the identification of deceased organ donors. As expected, specificity and negative predictive value were near 100%. The number of organ donors identified by the algorithm each year was similar to the expected value, and this included the pre-validation period (1991 to 2005). Algorithms to identify organ–specific donors performed poorly (e.g. sensitivity ranged from 0% for small intestine to 67% for heart; positive predictive values ranged from 0% for small intestine to 37% for heart). INTERPRETATION: Primary data abstraction to identify deceased organ donors should be used whenever possible, particularly for the detection of organ-specific donations. The limitations of physician billing claims should be considered whenever they are used. Public Library of Science 2013-08-14 /pmc/articles/PMC3743842/ /pubmed/23967114 http://dx.doi.org/10.1371/journal.pone.0070825 Text en © 2013 Li et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Li, Alvin Ho-ting
Kim, S. Joseph
Rangrej, Jagadish
Scales, Damon C.
Shariff, Salimah
Redelmeier, Donald A.
Knoll, Greg
Young, Ann
Garg, Amit X.
Validity of Physician Billing Claims to Identify Deceased Organ Donors in Large Healthcare Databases
title Validity of Physician Billing Claims to Identify Deceased Organ Donors in Large Healthcare Databases
title_full Validity of Physician Billing Claims to Identify Deceased Organ Donors in Large Healthcare Databases
title_fullStr Validity of Physician Billing Claims to Identify Deceased Organ Donors in Large Healthcare Databases
title_full_unstemmed Validity of Physician Billing Claims to Identify Deceased Organ Donors in Large Healthcare Databases
title_short Validity of Physician Billing Claims to Identify Deceased Organ Donors in Large Healthcare Databases
title_sort validity of physician billing claims to identify deceased organ donors in large healthcare databases
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3743842/
https://www.ncbi.nlm.nih.gov/pubmed/23967114
http://dx.doi.org/10.1371/journal.pone.0070825
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