Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data
University of Alberta · University of Calgary · +3 more institutions
Abstract
Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define Charlson and Elixhauser comorbidities in administrative data and assess the performance of the resulting algorithms.
ICD-10 coding algorithms were developed by "translation" of the ICD-9-CM codes constituting Deyo's (for Charlson comorbidities) and Elixhauser's coding algorithms and by physicians' assessment of the face-validity of selected ICD-10 codes. The process of carefully developing ICD-10 algorithms also produced modified and enhanced ICD-9-CM coding algorithms for the Charlson and Elixhauser comorbidities. We then used data on in-patients aged 18 years and older in ICD-9-CM and ICD-10 administrative hospital discharge data from a Canadian health region to assess the comorbidity frequencies and mortality prediction achieved by the original ICD-9-CM algorithms, the enhanced ICD-9-CM algorithms, and the new ICD-10 coding algorithms.
Citation impact
- FWCI
- 57.46
- Percentile
- 100%
- References
- 16
Authors
10- HQHude QuanCorresponding
University of Alberta, University of Calgary
- VSVijaya Sundararajan
Services Australia
- PHPatricia Halfon
Institute of Social and Preventive Medicine, University of Lausanne
- AFAndrew FongCorresponding
University of Alberta, University of Calgary
- BBBernard Burnand
Institute of Social and Preventive Medicine, University of Lausanne
Topics & keywords
- ICD-10
- Algorithm
- Medicine
- Coding (social sciences)
- Diagnosis code
- Comorbidity
- Current Procedural Terminology
- Data mining
- Good health and well-being