Electronic Health Reporter

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.

1. 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.

2. 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.

3. Reducing departmental friction

Many C-suite leaders want AI solutions to improve cross-functional teamwork and reduce friction, especially in areas like documentation, coding, and billing, where inconsistencies and errors have repercussions across the organization.

Traditionally, health system departments tend to work in silos with often limited interaction. This can lead to tension, misaligned incentives, and forfeited opportunities for improvement. AI can break down these silos in a few ways. By cutting through backlogs of high-volume tasks, employees gain extra bandwidth to think about their cross-functional interdependencies and to collaborate more closely. And by bringing together disparate systems into a common source of truth, team members in one department, such as finance, can share a unified view of visit volume and financial impact with members of other departments, such as coding and clinical leadership.

4. Optimizing workforce

Perhaps health system leaders’ most significant expectation for AI is to enhance their workforce. This broad theme encompasses alleviating workforce shortages, reducing administrative burdens, increasing staff satisfaction, and ultimately boosting the quality of patient care.

Automation tools address several such problem areas, including the 30% medical coder shortage reported by the American Medical Association and the 45% health worker burnout rate. Many Chief People Officers and Chief Human Resource Officers at leading health systems are taking notice of the opportunity with AI to help solve their workforce challenges and improve their teams’ experiences. At the Mayo Clinic, Sarah Poncelet, executive director of strategy development, shared with Becker’s that health systems “can’t recruit our way out of a workforce shortage.” In her view, “30% of healthcare has the potential for automation, so we really want to … free up our most valuable asset, which is our people, and make sure they’re doing human-related tasks versus things that could be potentially automated.”

The AI advantage

Health system leaders clearly recognize AI’s impact. Through demonstrating ROI, developing end-to-end strategies, enhancing cross-departmental collaboration, and optimizing the workforce, AI vendors can deliver what top systems are hoping to see in the near term.

Overall, my conversations with C-suite leaders have reinforced that organizations are actively working toward a unified vision where healthcare is more focused on patient interaction than paperwork. As health systems increasingly embrace AI, executives ought to screen vendors through the lens of these rising expectations. Working together, they can make the ideal state of healthcare delivery a reality.