Optimizing Resident Charge Capture with Disappearing Help Text in Note Templates

Area of Science:

• Medical Informatics
• Healthcare Administration
• Clinical Documentation

Background:

• Accurate coding for evaluation and management (E/M) services is crucial for healthcare reimbursement and quality assessment.
• Medical residents often face challenges in selecting the correct Current Procedural Terminology (CPT) codes for E/M services.
• Standardized note templates are widely used in clinical settings to streamline documentation processes.

Purpose of the Study:

• To assess the effectiveness of integrated disappearing help text in a standardized note template for improving resident CPT code selection for E/M services.
• To reduce the frequency of CPT code modifications made by attending physicians, serving as a proxy for resident coding accuracy.

Main Methods:

• A disappearing help text summarizing E/M coding requirements was embedded into a standardized note template for pediatric urgent care residents.
• An intervention group (PGY 1 residents) used the template with help text, while a control group (PGY 2-3 residents) used an identical template without help text.
• The primary outcome measured was the incidence of CPT code changes by attending physicians, analyzed using logistic regression.

Main Results:

• Residents using the help text demonstrated a significantly lower rate of CPT code changes by attending physicians (22.1% vs. 30.6%).
• This reduction in CPT code adjustments was consistent across different training levels (PGY 1 and PGY 2-3).
• Multivariable analysis confirmed that the use of help text was independently associated with a substantial decrease in CPT code modification (OR = 0.28).

Conclusions:

• The implementation of disappearing help text within resident note templates is a promising strategy for enhancing E/M coding accuracy.
• This intervention led to a significant reduction in the need for attending physician CPT code adjustments, indicating improved resident performance.
• The findings suggest broader applicability of such assistive text features for improving clinical documentation and coding in various healthcare settings.