Quantifying surgical complexity through textual descriptions of current procedural terminology codes

Area of Science:

• Health Services Research
• Medical Informatics
• Surgical Outcomes

Background:

• Accurate quantification of surgical procedure complexity is crucial for patient bedside evaluation and risk-adjusted quality assessment of healthcare providers.
• Current methods for assessing procedural complexity often rely on general coding system information or reimbursement-focused factors, lacking granularity.
• Existing metrics like procedure time or broad anatomical classifications provide limited insight into the nuanced difficulty of surgical interventions.

Purpose of the Study:

• To develop and validate a novel approach for estimating individual surgical procedural complexity.
• To overcome the limitations of current methods by leveraging detailed textual descriptions within Current Procedural Terminology (CPT) codes.
• To demonstrate the potential of a text-based complexity score to enhance surgical risk adjustment and healthcare quality assessment.

Main Methods:

• Utilized textual descriptions associated with Current Procedural Terminology (CPT) codes to derive a fine-grained measure of procedural complexity.
• Developed a novel text-based scoring system to quantify the complexity of individual surgical procedures.
• Compared the performance of the text-based complexity score against existing estimates in assessing procedural complexity.

Main Results:

• The novel text-based approach provides a superior assessment of surgical procedural complexity compared to currently used estimates.
• The developed text-based complexity score significantly improves surgical risk adjustment.
• The enhanced risk adjustment remains effective even after accounting for a wide range of patient-specific factors.

Conclusions:

• A text-based analysis of CPT codes offers a more granular and accurate method for quantifying surgical procedural complexity.
• This novel approach has the potential to significantly improve the accuracy of surgical risk adjustment models.
• The findings indicate a promising avenue for enhancing the quality assessment of surgical care providers and outcomes.