Entropic Measures of Complexity in a New Medical Coding System

Background: Transitioning from an old medical coding system to a new one can be challenging, especially when thetwo coding systems are significantly different. The US experienced such a transition in 2015. Objective: This research aims to introduce entropic measures to help users prepare for the migration to a newmedical coding system by identifying and focusing preparation initiatives on clinical concepts with morelikelihood of adoption challenges. Methods: Two entropic measures of coding complexity are introduced. The first measure is a function of thevariation in the alphabets of new codes. The second measure is based on the possible number of validrepresentations of an old code. Results: A demonstration of how to implement the proposed techniques is carried out using the 2015 mappingsbetween ICD-9-CM and ICD-10-CM/PCS. The significance of the resulting entropic measures is discussed inthe context of clinical concepts that were likely to pose challenges regarding documentation, coding errors,and longitudinal data comparisons. Conclusion: The proposed entropic techniques are suitable to assess the complexity between any two medical coding systems where mappings or crosswalks exist. The more the entropy, the more likelihood of adoptionchallenges. Users can utilize the suggested techniques as a guide to prioritize training efforts to improve documentation and increase the chances of accurate coding, code validity, and longitudinal data comparisons.