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BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2015

Open Access 01-01-2016 | Research article

Methods for identifying 30 chronic conditions: application to administrative data

Authors: Marcello Tonelli, Natasha Wiebe, Martin Fortin, Bruce Guthrie, Brenda R Hemmelgarn, Matthew T James, Scott W Klarenbach, Richard Lewanczuk, Braden J Manns, Paul Ronksley, Peter Sargious, Sharon Straus, Hude Quan, For the Alberta Kidney Disease Network

Published in: BMC Medical Informatics and Decision Making | Issue 1/2015

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Abstract

Background

Multimorbidity is common and associated with poor clinical outcomes and high health care costs. Administrative data are a promising tool for studying the epidemiology of multimorbidity. Our goal was to derive and apply a new scheme for using administrative data to identify the presence of chronic conditions and multimorbidity.

Methods

We identified validated algorithms that use ICD-9 CM/ICD-10 data to ascertain the presence or absence of 40 morbidities. Algorithms with both positive predictive value and sensitivity ≥70% were graded as “high validity”; those with positive predictive value ≥70% and sensitivity <70% were graded as “moderate validity”. To show proof of concept, we applied identified algorithms with high to moderate validity to inpatient and outpatient claims and utilization data from 574,409 people residing in Edmonton, Canada during the 2008/2009 fiscal year.

Results

Of the 40 morbidities, we identified 30 that could be identified with high to moderate validity. Approximately one quarter of participants had identified multimorbidity (2 or more conditions), one quarter had a single identified morbidity and the remaining participants were not identified as having any of the 30 morbidities.

Conclusions

We identified a panel of 30 chronic conditions that can be identified from administrative data using validated algorithms, facilitating the study and surveillance of multimorbidity. We encourage other groups to use this scheme, to facilitate comparisons between settings and jurisdictions.
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Metadata
Title
Methods for identifying 30 chronic conditions: application to administrative data
Authors
Marcello Tonelli
Natasha Wiebe
Martin Fortin
Bruce Guthrie
Brenda R Hemmelgarn
Matthew T James
Scott W Klarenbach
Richard Lewanczuk
Braden J Manns
Paul Ronksley
Peter Sargious
Sharon Straus
Hude Quan
For the Alberta Kidney Disease Network
Publication date
01-01-2016
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2015
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-015-0155-5

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