Evaluation of breast cancer coding quality and its influence on diagnosis-related groupings: a cross-sectional study

Key Points

• The research aims to assess the quality of breast cancer coding and its effects on diagnosis-related groupings.
• Conducted a cross-sectional evaluation of coding practices in breast cancer cases.
• Analyzed factors contributing to coding errors, such as coder experience and documentation practices.
• Identified independent predictors of coding errors including length of hospital stay and number of diagnoses.
• Identified key contributors to coding errors related to coders' knowledge and practices.
• Found that non-standard documentation and clinician diagnostic errors significantly affect coding quality.
• Demonstrated that coders' experience and the number of diagnoses are independent predictors of errors.

Abstract