Perceptions of Portuguese medical coders on the transition to ICD-10-CM/PCS: A national survey

Health Inf Manag. 2023 Jul 18:18333583231180294. doi: 10.1177/18333583231180294. Online ahead of print.

Abstract

Background: In Portugal, trained physicians undertake the clinical coding process, which serves as the basis for hospital reimbursement systems. In 2017, the classification version used for coding of diagnoses and procedures for hospital morbidity changed from the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS).

Objective: To assess the perceptions of medical coders on the transition of the clinical coding process from ICD-9-CM to ICD-10-CM/PCS in terms of its impact on data quality, as well as the major differences, advantages, and problems they faced.

Method: We conducted an observational study using a web-based survey submitted to medical coders in Portugal. Survey questions were based on a literature review and from previous focus group studies.

Results: A total of 103 responses were obtained from medical coders with experience in the two versions of the classification system (i.e. ICD-9-CM and ICD-10-CM/PCS). Of these, 82 (79.6%) medical coders preferred the latest version and 76 (73.8%) considered that ICD-10-CM/PCS guaranteed higher quality of the coded data. However, more than half of the respondents (N = 61; 59.2%) believed that more time for the coding process for each episode was needed.

Conclusion: Quality of clinical coded data is one of the major priorities that must be ensured. According to the medical coders, the use of ICD-10-CM/PCS appeared to achieve higher quality coded data, but also increased the effort.

Implications: According to medical coders, the change off classification systems should improve the quality of coded data. Nevertheless, the extra time invested in this process might also pose a problem in the future.

Keywords: International Classification of Diseases; classification; clinical coding; data accuracy; diagnosis related groups; health information management.