Do We Have Enough Information? How ICD-10-AM Activity Codes Measure UP

Abstract

This research explored the usage of activity codes introduced into the International Statistical Classification of Diseases and Related Health Problems, Tenth revision, Australian Modification (ICD-10-AM) Third Edition and examined the data quality of activity coding, explicitly, completeness and specificity. Injury separations for years 2001/02 to 2005/06 specifying a ‘true injury’ were extracted for descriptive analyses. Part A investigated the usage of activity codes and compared the usage of the 236 activity codes available in the Activity block (U50-U73) present in the ICD-10-AM Third Edition against the 16 codes present in the second edition. Part B examined the level of completeness of external cause coding and the degree of activity coding specificity in the 2005/06 dataset. It was found that the additional activity codes were used extensively with only 46 codes seldom assigned. Codes present in the second edition were extensively used in the third and fourth editions and the new additional activity codes represent 10% of all activity codes assigned per year. All five datasets demonstrated high levels of completeness, recording completeness levels greater than 97%, where missing activity codes attributed to the majority of missing codes. Fourteen out of the 24 activity categories demonstrated a strong reliance on non-specific codes and Team ball sports and Wheeled non-motor sports illustrated that activity codes assigned lacked detail in the code. Clinicians and coders need to acknowledge the importance of quality clinical documentation for research and policy-making purposes so that circumstances surrounding injury events can be coded to the highest level of specificity to improve injury prevention and control activities. Missing activity codes and the abundance of non-specific coding hinders the usefulness of the data.

Keywords

Clinical Coding International Classification of Diseases ICD-10-AM Hospital Administration Data Data Quality Morbidity

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