The study of 200 hospital and health system executives finds that two-thirds report using AI in some revenue cycle capacity, and nearly all of them expect to be using it within three years.
Although the use of AI is becoming more widespread within hospital revenue cycles, its application is often piecemeal, rather than end-to-end, finds new research from Change Healthcare.
The national study of 200 hospital and health system executives finds that two-thirds of them report using AI in some revenue cycle capacity. Nearly all of them expect to be using it within three years.
Some AI revenue cycle applications are more widely used than others: 72% of revenue cycles use AI for eligibility/benefits verification and 64% use it for patient payment estimation.
By 2023, respondents expect prior authorization (68%) and payment amount/timing estimation (62%) to emerge as leading applications for AI.
When asked about how AI improved their revenue cycle operations, the most cited improvements were driving patient and payer payments (83%) and improving cash flow (80%).
Related: 3 Reasons an AI Beta Test is Good for Revenue Cycle
Despite the improvements and promise of AI, respondents also cited a number of barriers to fully integrating the technology. The top barrier is budget concerns followed by:
- Liability, risk, and privacy concerns (56%)
- Staffing (50%)
- Lack of trust in the information provided (45%)
- Infrastructure challenges (43%)
The research also found that revenue cycle leaders (89%) report using AI much more than those in IT (63%) and non-technical executive roles (48%).
In addition, those in RCM roles (78%) are satisfied with their current use of AI, compared to just 46% of IT leaders and 25% of non-technical executive and financial respondents.
Similarly, 86% of those in RCM roles see value in using AI in RCM compared to 52% of IT and 44% of executive and financial decision makers.
Alexandra Wilson Pecci is an editor for HealthLeaders.
