The Evaluation of Clinical Classifications Software Using the National Inpatient Sample Database

Area of Science:

• Health Services Research
• Medical Informatics
• Public Health

Background:

• The Clinical Classifications Software (CCS) groups International Classification of Diseases (ICD) codes to analyze healthcare outcomes, costs, and utilization.
• Validating CCS category representation and preventing research gaps necessitates ongoing research into its application.

Purpose of the Study:

• To compare event frequency and ICD code changes in CCS categories between 2015 and 2016.
• To identify CCS categories with significant temporal shifts in data representation.

Main Methods:

• Utilized National Inpatient Sample data for analysis.
• Compared CCS diagnostic categories between the first three quarters of 2015 and 2016.
• Identified categories with over 20% change in event frequency or ICD code composition.

Main Results:

• Out of 285 diagnostic CCS categories, 63 exhibited greater than 20% change.
• Of these, 32 categories showed an increase and 31 showed a decrease in event frequency or code representation.
• Significant temporal variations in CCS category data were observed.

Conclusions:

• The transition from ICD-9 to ICD-10 introduces complexity, impacting CCS category stability.
• Additional studies are required to elucidate the reasons behind observed changes.
• Improved understanding will enhance CCS utility for ICD-10 data and comparability with ICD-9 data.