May 24
2024
Great Expectations: What Health Systems Want from AI Vendors
By Andrew Lockhart, CEO, Fathom.
Imagine this: physicians spend more time with their patients than with their paperwork. Billing is quick and accurate, with minimal denials. Healthcare workers enjoy a positive work/life balance. Thanks to the rapid advancement of AI, this vision of healthcare is becoming increasingly possible.
Health system leaders are already investing toward this ideal state. From roundtable discussions at Healthcare Financial Management Association and Becker’s Healthcare to Zoom chats every week, I’ve connected with many C-suite executives at health systems about their expectations for AI. There is, across the board, a clear set of priorities for the next one to two years. The overarching vision is not just to integrate new technologies but to do so in a way that delivers tangible improvements in workforce experiences and satisfaction, revenues and costs, and patient care outcomes.
Here are a few resounding themes that I’ve heard.
- Proving ROI
Proving ROI on AI investments is crucial: put plainly, you want to ensure you’re getting more than enough bang for your buck. Applications of AI need to map back clearly to measurable cost and revenue impacts. Health system CFOs expect predictable ROI and are screening new technologies closely.
Many AI tools on the administrative side can meet this proof of hard ROI. For example, organizations like ApolloMD have experienced significant improvements in coding efficiency and revenue capture by minimizing coding errors and denials through autonomous coding.
While vendors typically report impressive ROI from their technology, any vendor worth its salt will agree to a proof of concept allowing you to test and validate impact for your organization. For example, an easy way to build confidence in autonomous coding is to compare coding results between your team and the AI system before committing to go-live.
- Increasing end-to-end strategies
Many AI tools have surfaced to address a single use case. However, health system leaders are more interested in comprehensive, integrated solutions across departments. Consider the case of ambient documentation and autonomous coding: ambient documentation works as a medical scribe using AI to document clinician-patient encounters, and then autonomous coding steps in as a medical coder to translate and assign the necessary codes for billing.
These types of end-to-end strategies are more compelling and impactful. Health system CEOs increasingly gravitate toward them to ease administrative burdens, speed up visit-related processes, and enhance patient outcomes. The market is supporting this expectation: Abridge, an ambient documentation platform, recently raised $150 million in funding, and Google Cloud added an autonomous medical coding solution to its marketplace earlier this year. Used in conjunction, these technologies offer more integrated – and more valuable – strategies for health systems.