Scaling Musculoskeletal Care with AI: A Safe and Effective Approach
July 26, 2024
Study Overview
As musculoskeletal (MSK) conditions continue to rise, the demand for physical therapy has outpaced available providers, creating barriers to timely care. This study explores how artificial intelligence (AI) can be integrated into digital care programs (DCPs) to scale MSK treatment effectively and safely.
Using a post hoc analysis of a pre-post cohort study, researchers compared two groups:
- Intervention Group (IG): AI-assisted digital care with an increased physical therapist (PT)-to-patient ratio (1:129).
- Comparison Group (CG): Digital care program without AI assistance (1:57 PT-to-patient ratio).
Key findings include:
- Clinical outcomes remained stable, with no significant differences in pain reduction (64% vs. 63% response rate, p = 0.399) or mental health improvements.
- Higher completion rates in the AI-assisted group (79.9% vs. 70.1%, p < 0.001), suggesting improved adherence.
- Engagement remained consistent, with PT reach-outs increasing in the AI-assisted group.
- High satisfaction scores were maintained across both groups (IG: 8.76/10, CG: 8.60/10, p = 0.021).
- Adverse events were low and comparable, reinforcing the safety of AI-assisted scaling (IG: 0.58%, CG: 0.69%, p = 0.231).
These results indicate that AI-supported workflows can help scale MSK care efficiently without compromising patient safety, clinical effectiveness, or engagement. The study underscores AI’s potential to optimize PT workloads while maintaining high-quality, patient-centered rehabilitation.
