On May 21, Becker’s Hospital Review hosted a webinar, Employing a Digital Workforce to Transform the Revenue Cycle, sponsored by Olive: a technology company who delivers an AI workforce to healthcare organizations. The webinar was led by Susan Whitecotton, Vice President of Patient Financial Services at MedStar Health, and Braden Lambros, Executive Director of AI Transformation at Olive.
During the session, MedStar shared their story of employing Olive’s digital workforce. Both speakers gave their perspectives and insights on:
- How AI can address hospital’s biggest challenges
- The differentiators of an AI workforce
- Effective ways to lead an AI transformation program within your organization
- How to navigate the vendor selection process
- The outcomes of hiring an AI workforce
Here are the top five questions answered during the webinar.
How do I determine if AI and automation is right for my organization?
A host of internal challenges, industry challenges and pressing needs are constantly putting pressure on hospitals to do more with less, all while improving performance. For MedStar, those challenges led the organization to pursue cutting edge technologies to support their revenue cycle transformation. Like many health systems, some specific issues the organization faced included:
- Separate financial systems versus their clinicals
- Registration accuracy
- Staffing / Turnover / Training
- Frequent payor changes that have led to financial performance issues
- Pressing needs that bubbled back up to the revenue cycle
As the team at MedStar investigated solutions, AI and automation emerged as an ideal fit to concur many of the repetitive, rule-based and error prone processes that were driving critical revenue cycle functions.
What is an AI workforce?
An AI workforce is enabled by combining automation and artificial intelligence technologies in tandem to automate error prone, inefficient tasks. To understand how an AI workforce works, it’s often easiest to think of the technology as a ‘digital employee’ that uses AI skills to imitate a human employee. Robotic Process Automation handles many of the tasks that hands would tackle, logging into and out of systems and entering data manually. Computer Vision is leveraged as the eyes, reading, scanning and recognizing critical items on a page — transcribing documents and images that are critical to standard business processes in a health system. While Machine Learning is defined as a digital employee’s ability to make contextual decisions about and within processes, truly mimicking human decision making.
How should I go about leading an AI and automation initiative within my hospital?
According to Susan, pulling together the right people, having the right conversations and aligning on the right execution model are essential for leading a successful program. She advised those considering leading their own AI initiative to:
- Get the right stakeholders involved early
- Have a project champion
- Create a staffing augmentation strategy and communication plan
- Call on internal teams to contribute to the discovery process
- Lean into an agile execution model
What criteria should I consider when seeking an AI and automation partner?
When engaging in vendor partnership selection, Susan advised beginning with the end in mind. By doing proper research and understanding her KPIs before seeking a vendor, MedStar was aligned on critical indicators of success and set clear expectations on how success would be measured. By conducting site visits and reference calls with other health systems already benefiting from AI and automation, the team was able to validate their vendor criteria.
Vendors were evaluated on the following criteria:
- Had a process and approach to achieve required results
- Had deep experience in the revenue cycle (someone who spoke a hospital’s language)
- Had an understanding of healthcare’s unique security challenges
- Would go beyond being a vendor; they would be a true partner
“We went through a formal selection process and found that Olive not only brought the revenue cycle expertise, but more importantly, they brought innovation and talent with an enthusiastic team that blended very well with our culture. This was very important to introduce change and deliver a successful outcome,” Susan said.
How do I determine where to begin?
As a vendor partner, Olive often is asked, “Where do I get started?”. It can seem daunting, and that’s where you should rely on your vendor to guide you. Braden explained prioritization should be aligned with processes that will deliver quick wins with big impacts. By tackling those challenges first, your organization can build quick success, establish internal buy-in needed across teams to continue to tackle more complex process challenges. It’s best to start by listing business process that are repetitive, high-volume, rule-based and often prone to human error.
Ideal candidates for automation will meet each of those criteria. Your vendor will then determine which automations can be built and deployed quickly (30-60-90 days from the time work begins) and support your team in defining prioritization against business results, such as increased efficiency or accuracy.
What outcomes are expected when hiring an AI workforce?
Strategically planned programs with thorough scoping, strong communication (internal and external) and clear key performance indicators, organizations produce quick wins that demonstrate immediate process improvements, along with long-term economic impacts that help achieve desired financial results.
For Susan and her team, in six months since initial go-live, Olive’s AI workforce has:
- Logged 1,300 hours of productive work
- Completed more than 23 million actions
- Delivered cost savings of more than 50 percent compared to prior processes.
Two other quick wins for MedStar were in the Electronic Insurance Eligibility Verification process and ERA remittance posting. In Eligibility Verification, Olive was live in 22 days, and now completes the process 5 to 7 times faster than a human employee could. And in ERA remittance posting, Olive has taken over 90% of the process, allowing staff to shift focus to other important tasks. Hiring an AI workforce also allowed previously untouched work to be addressed. In patient status transfers, limited resources meant Susan’s team was only able to manage inpatient to outpatient charge capture corrections (leaving outpatient to inpatient unaddressed). Olive now runs both processes (more than 1,100 charge corrections per day), giving the organization the opportunity to realize more revenue.
“[Employing an AI workforce] has been an exciting journey thus far. Our team has been excited to learn new things and we’re really looking forward to seeing a significant impact in the long run,” said Susan.
With many phases of their revenue cycle transformation still to come, MedStar’s digital workforce and the process efficiencies and financial impacts that come with it has just begun.
Want to learn more about how Olive is transforming this health system with AI? Catch the entire webinar here.