Tools for categorization of diagnostic codes in hospital data: Operationalizing CCSR into a patient data repository

Author:

Malecki Sarah,Loffler Anne,Tamming Daniel,Fralick Michael,Sohail Shahmir,Shi Jiamin,Roberts Surain,Colacci Michael,Razak Fahad,Verma Amol

Abstract

AbstractBackgroundThe Clinical Classification Software refined version (CCSR) is a tool to aggregateInternational Classification of Diseases, 10th Revision, Clinical Modification/Procedure Coding System(ICD-10-CM/PCS) diagnosis codes into clinically meaningful categories. ICD-10-CM/PCS codes are primarily used in the United States and the tool has not been optimized for use with other country-specific ICD-10 coding systems.MethodWe developed an automated procedure for mapping Canadian ICD-10 codes (ICD-10-CA) to CCSR categories using discharge diagnosis data from adult medical hospitalizations at 7 hospitals between Apr 1 2010 and Dec 31 2020, and manually validated the results.ResultsThere were 383,972 Canadian hospital admissions with 5,186 distinct ICD-10 discharge diagnosis codes. Only 46.6% of ICD-10-CA codes could be mapped directly to CCSR categories. Our algorithm improved mapping of hospital codes to CCSR categories to 98.2%. Validation of the algorithm demonstrated a high degree of accuracy with strong interrater agreement (observed proportionate agreement of 0.98). The algorithm was critical for mapping the majority of diagnosis codes associated with heart failure (96.6%), neurocognitive disorders (96.0%), skin and subcutaneous tissue infections (97.2%), and epilepsy (92.5%).ConclusionOur algorithm for operationalizing CCSR into a patient data repository (https://github.com/GEMINI-Medicine/gemini-ccsr) has been validated for use with Canadian ICD-10 codes and may be useful to clinicians and researchers from diverse geographic locations.

Publisher

Cold Spring Harbor Laboratory

Reference17 articles.

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2. (HCUP) AfHRaQHCaUP. Clinical Classifications Software Refined (CCSR) for ICD-10-CM Diagnoses. https://www.hcup-us.ahrq.gov/toolssoftware/ccsr/dxccsr.jsp. Published 2021. Accessed.

3. Milken Institute: CLAUDE LOPEZ P, HYEONGYUL ROH, PHD, AND BRITTNEY BUTLER. How to Identify Health Innovation Gaps? Insights from Data on Diseases’ Costs, Mortality, and Funding. 2020.

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