In the lead-up to the healthXchange Revenue Cycle AI, Automation, and Analytics meeting taking place Tuesday, May 21st, we’ve had the great opportunity to sit down with the panelists to learn more about their professional journeys, current priorities, and areas they are looking forward to benchmarking and discussing with peers at the forthcoming event. This terrific interview with Sou Chon Young, Manager of Revenue Cycle Performance Management at Trinity Health, provides an incredible insight into the challenges faced by revenue cycle teams integrating technology, as well as tangible steps that need to be taken to identify and measure return on investment.
Can you provide an overview of your professional journey thus far, including the roles and responsibilities you are undertaking in your current position at Trinity Health?
I’ve been a Revenue Cycle consultant for over 20 years, with an emphasis on adoption, implementation, and use of technology. I’ve also helped design, build, test, and install patient accounting systems which helped me see the revenue cycle not only from a holistic view, but also from a data flow perspective. My passion for technology was fostered through various placements as well as career moves that enabled me to leverage my technical skills and interests.
Right after grad school, I worked for a community hospital as a business analyst for the newly formed PHO. A few of my responsibilities included creating reports to help track and trend financial and utilization reports as well as physician profiling, performing claim audits to ensure appropriate charges were billed, and assisting Information Services in data mining. In my role, I learned how to build reports using a database management system (i.e., Microsoft Access) which later proved to be very beneficial in my career.
My next role was with PricewaterhouseCoopers (PwC) as a consultant in the Revenue Cycle Information Technology group. This is where I started to learn about the different components of the revenue cycle through working on different projects. Having helped implement Patient Accounting systems a few times also helped me learn how different parts of the revenue cycle impact and interact with one another. It was also during this time that HIPAA was enacted, and the transaction code sets and Electronic Data Interchange (EDI) were mandated for the healthcare industry. I believe EDI changed healthcare and the revenue cycle. The industry was required to not only transact electronically, but the industry was now also required to use a ‘standard’ set of code (e.g., claim statuses, CARC, RARC, etc.). EDI, combined with my knowledge in building queries and reports using relational databases, helped expedite the tracking and trending of different metrics and provide access to huge data sets – Big Data. What I previously had to track manually and use crosswalks for the disparate data sets, was now standardized and in electronic form.
After PwC I went to work for a small boutique consulting firm where I built a denial management tool, using a great business intelligence application (let me know if you’re interested and I can put you in touch with them). I did traditional revenue cycle consulting projects and used the software when I could help find opportunities in denial management.
I’ve been a managing consultant for the past decade and am currently employed at Trinity Health on their Performance Management team, which is an internal consulting team. My roles and responsibilities include the typical revenue cycle work: assessments, AR management, project management, optimizing workflows, serving in interim roles, and sometimes we get to collaborate with our Data Analytics team to build dashboards. For example, we built a tracker to monitor and measure vendor performance.
What emerging technology trends do you anticipate either enhancing workflows, or disrupting the revenue cycle entirely?
I wouldn’t call it emerging technology because it’s been in Revenue Cycle for a while now, but I do believe Business Intelligence (BI) tools and Data Analytics (DA) will continue to help enhance workflows. BI and DA can help us see trends, spot anomalies, and help us prioritize and focus on the bigger issues and opportunities – to work smarter, not harder. These tools will help convert data into information and, ultimately, into actionable next steps. What I’ve also been seeing is talent from outside of healthcare, who know how to use BI tools and are strong in data analytics, joining the cause to improve the revenue cycle.
I also believe automation could help enhance the revenue cycle BUT first, we need to ensure the workflow is always the same. Healthcare is complex and not always standard; many workflows that we would like to automate require some manual intervention or human decision-making. Until we can identify those workflows that a machine/bot can follow – automation will not be helpful.
This is where AI comes in. I’m not an expert in AI but if we can have machines learn and self-program how to make decisions based on specific criteria and over time learn exceptions handling, AI will be the next game changer. Not to be cynical, but AI can and will also be used by payers so the benefits may be limited to how quickly providers can compensate for payer rules and regulation changes.
I will add that no matter what the technology is – whether it’s emerging or something that has been around for a while, we first need to understand what the ask is, and what the opportunity is before we know how best to apply any technology. Technology is just a tool – we need to know when and how best to wield it.
When it comes to identifying benchmarks and KPIs to measure the impact of technology, what would your advice be to fellow peers and colleagues in the industry?
Agree with stakeholders on the different measures of success (and don’t have too many), as well as reasonable goals (you can always change the goals over time as you progress and improve – raise the bar).
Agree on how benchmarks are calculated, including what is included and excluded.
Make sure to have a good number of baseline measures so you can compare to post-implementation to demonstrate impact.
Make sure that teams learn, know, and breathe the KPIs so the language is consistent, and everyone is aligned.
Know your data! Beyond knowing your data, you need to be able to convert data into information, and then ultimately into actionable next steps. Translating data into the operational world, and crosswalking operations into data and information is critical. A great data / business analyst is worth their weight in gold!
Make sure to fully leverage the existing tools you already have before running off to the new ‘sexy’ technology / tool.
Do a lot of testing: Get operations involved; they know what scenarios to build for, and what the desired results should be. Ultimately, they will also be owners and responsible for the outcomes, so they should be involved early, and throughout the process.
Thank you so much Sou Chon for these incredibly insightful responses, and for sharing your lessons learned! If you’re looking to hear from leaders in Revenue Cycle that are implementing and tracking the success of new revenue cycle technologies, make sure to join us on May 21st during the Revenue Cycle AI, Automation, and Analytics event.