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Validity of physician billing claims to identify deceased organ donors in large healthcare databases
- Source :
- PLoS ONE, PLoS ONE, Vol 8, Iss 8, p e70825 (2013)
- Publication Year :
- 2013
-
Abstract
- 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.
- Subjects :
- Critical Care and Emergency Medicine
Databases, Factual
Policy making
Clinical Research Design
Epidemiology
lcsh:Medicine
030204 cardiovascular system & hematology
computer.software_genre
Health informatics
03 medical and health sciences
Databases
0302 clinical medicine
Procurement
Physicians
Health care
Renal Transplantation
Medicine
Humans
030212 general & internal medicine
lcsh:Science
Policy Making
health care economics and organizations
Multidisciplinary
Database
business.industry
Applied Mathematics
lcsh:R
Reproducibility of Results
Tissue Donors
3. Good health
Transplant Surgery
Nephrology
Computer Science
lcsh:Q
Surgery
business
Information Technology
computer
Delivery of Health Care
Algorithms
Medical Informatics
Mathematics
Research Article
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 8
- Issue :
- 8
- Database :
- OpenAIRE
- Journal :
- PloS one
- Accession number :
- edsair.doi.dedup.....8d3c2d17ad53cad85acc4d75fc26a039