Reduction of Electronic Medical Record Documentation Time and Burden Using an Artificial Intelligence Scribe Tool in...

With an aging population in the United States, the demand for joint arthroplasty procedures continues to rise. As patient volumes increase in arthroplasty clinics, the documentation burden for each clinic day also grows, creating a demand for tools that can help alleviate this workload. Artificial intelligence (AI)-powered tools, such as automated charting assistants, may enhance provider efficiency by reducing documentation time. This study evaluates whether implementing an AI scribe in an orthopaedic clinic decreases documentation time for providers.

A retrospective, nonexperimental analysis was conducted after the adoption of a commercially available Health Insurance Portability and Accountability Act (HIPAA)-compliant AI scribe software tool. Active electronic medical record time per clinic day was measured for a team comprising one orthopaedic surgeon, one physician associate, and one orthopaedic surgery fellow. Resident physicians were excluded because of frequent rotation changes.

Before AI implementation, providers saw an average of 38.7 patients (±2.2) over 34 clinic days, compared with 39.9 patients (±2.3) over 27 clinic days after implementation (P = 0.043). Total active EMR time per clinic day significantly decreased by 26.1% after implementation (after: 339.1 ± 78.7 vs. before: 458.8 ± 95.6 minutes; P < 0.0001). Average EMR time per patient decreased by 35.3% (after: 7.7 ± 2.9 vs. before: 11.9 ± 2.5 minutes; P < 0.0001). Total EMR time per clinic day (P = 0.0046) and per patient (P = 0.0002) demonstrated a significant, continual decline throughout the postimplementation period.

The use of an AI-powered scribing assistant markedly reduced documentation time in an orthopaedic clinic, enhancing provider efficiency. These findings suggest a promising strategy for alleviating documentation burden, potentially improving clinic workflow as patient volume increases. Larger, multicenter studies are needed to confirm these benefits and explore long-term effects on provider workload and patient care.