Latest / Becker’s Healthcare Podcast / Shannon Cameron on AI, Analytics and the Future of Revenue Cycle Leadership

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Shannon Cameron on AI, Analytics and the Future of Revenue Cycle Leadership · Becker’s Healthcare Podcast

• 0:02
  - There's a small circle of people who truly
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  - Becker's fourteenth annual CEO and CFO roundtable
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  - workforce strategy, and the leadership questions that don't
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  - Join us November second through the fifth in
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  - Chicago.
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  - For the agenda and event details,
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  - visit beckershospitalreview.com
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  - and click on the events tab in the
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  - upper right.
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  - This is Scott Becker with the Becker's Healthcare
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  - Podcast.
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  - I am thrilled today to be joined by
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  - your brilliant leader from the Harvard Faculty Foundation,
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  - the chief operating officer of AFS.
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  - But we're we're visiting today with Shannon Cameron,
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  - who's a fantastic leader and brilliant in the
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  - revenue cycle particularly.
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  - Shannon, could you take a moment and introduce
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  - yourself and tell us a little bit about
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  - your career?
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  - Sure.
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  - My career, started many years ago.
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  - Probably twenty six years ago, I started as
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  - a health care in with a health care
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  - consulting firm
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  - and working in all specialties, and then that
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  - took me over from the professional side over
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  - to the facility side.
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  - And,
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  - through multi large organizations,
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  - I spent several years at TeamHealth,
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  - in invasion and Schumacher,
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  - and then eventually found myself at Harvard Medical
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  - faculty physicians.
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  - And I am the current chief operating officer
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  - of the revenue cycle.
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  - And HMFP, as we refer to internally, is
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  - a large multispecialty
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  - academic physician organization.
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  - And, my, you know, my department supports the
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  - professional revenue cycle across, you know, a highly
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  - complex
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  - environment. We've got, academic and a community sign
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  - that includes numerous clinical departments and specialties. We
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  - have numerous different billing structures and operational workflows.
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  - And, that's pretty much in a nutshell. That
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  - was the quick kind of Reader's Digest version,
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  - but I've been all over revenue cycle from,
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  - the front end to back end collections. And
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  - as I mentioned, as a consultant doing, a
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  - to z gap analysis,
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  - for large organizations that are getting ready to
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  - do due diligence to go to market
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  - or that we're looking to improve their, you
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  - know, the bottom dollar.
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  - Fantastic. And talk about sort of trends that
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  - you're watching
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  - in the revenue cycle area.
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  - What what are you seeing currently? How
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  - much of issues are denials, pre authorizations,
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  - and so forth? What are some of the
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  - key issues that you're really focusing on and
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  - watching?
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  - Well, denials and, of course, prior auths, all
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  - of that is there's been a lot of
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  - activity,
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  - especially this past year in those areas.
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  - But I have four major trends that I've
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  - been keeping my eye on, and that includes,
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  - of course, the rapid movement towards AI and
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  - automation.
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  - I've implemented several automated workflows into our existing,
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  - system that has been quite,
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  - successful for us, but not simply for coding,
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  - but across documentation,
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  - charge capture,
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  - prior auths, denials,
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  - payment posting, and patient access.
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  - The real opportunity is not just reducing labor
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  - as I I think a lot of organizations
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  - are starting to find. It's using technology
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  - to identify the revenue leakages earlier,
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  - instead of being reactive, being more predictive,
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  - and prioritize
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  - our work more intelligently
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  - in reducing the administrative burden for both clinicians
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  - and staff, and then, of course, the overall
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  - patient experience. What is the you know, how
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  - does this improve,
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  - the patient's experience through the whole process?
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  - The next I think the next biggest area,
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  - of course, is the payer complexity.
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  - Of course, that's no secret to anybody in
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  - revenue cycle.
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  - We are seeing more aggressive medical necessity edits,
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  - authorization
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  - requirements,
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  - and now we're seeing this downcoding and administrative
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  - denials
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  - based off of big data, of course. And
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  - revenue cycle leaders have to become much more
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  - proactive in their payer strategies
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  - and use that data to distinguish true operational
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  - problems from inappropriate payer behavior, which, you know,
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  - we we've seen some of that. You know,
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  - we try to partner with those payers, not
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  - payer bashing, but, you know, there's a lot
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  - of there's a lot of stuff going on
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  - that we have to stay in front of.
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  - Another trend that I think, is the pressure
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  - to create enterprise consistency.
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  - You know, while we're
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  - while we are preserving specialty expertise, health systems
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  - are consolidating
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  - platforms and processes.
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  - So standardization is great, but a workflow that
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  - works for primary care may not work for
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  - anesthesia
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  - or emergency medicine or radiology or a surgical
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  - specialty.
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  - So successful centralization requires that thoughtful balance,
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  - between the standardization
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  - and specialty, you know, specific knowledge. So we
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  - have to be really careful with that. You
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  - know, there's been a lot of talk about
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  - governance with AI
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  - and a lot of of of drop you
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  - know, moving systems in together to integrate, but
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  - we have to be very careful that we're
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  - not losing that specific, you know, area that
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  - we need. And then finally, I'm I'm I'm
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  - watching the evolution of the revenue cycle workforce.
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  - You know, I think there was a big
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  - misconception
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  - that everyone was gonna lose their jobs. Yes.
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  - We're reducing certain jobs,
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  - but the the future will require
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  - it will require fewer people performing repetitive transactions.
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  - But more you know, we also need more
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  - people who can interpret the data and manage
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  - those exceptions and improve workflows and collaborate,
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  - you know, with clinical and technology leaders. So
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  - those are the big areas that have really
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  - consumed,
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  - you know, my time over the past couple
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  - of years, and I'm sure, you know, other
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  - leaders as well.
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  - No. Take a moment on the artificial intelligence
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  - side
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  - and and also that last part of the
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  - the the the trends you're talking about. So
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  - we hear more and more of this. Well,
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  - AIs can have a big impact.
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  - It it still requires
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  - really
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  - smart people to
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  - detail and figure out what to do with
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  - the AI, the information that comes out, and
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  - how to follow-up on it and execute it
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  - and so forth
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  - without losing that ability to do rigorous work
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  - and really work through those things. So where
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  - are you seeing AI have a big impact
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  - on the revenue cycle?
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  - And second, a little bit more on that
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  - second trend or the fourth trend or thought
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  - about what does it mean for the workforce
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  - because we're seeing this so much in the
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  - clinical and administrative area
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  - where the predictions that AI would take over
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  - everything
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  - soon to be
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  - quite exaggerated where there's still really a real
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  - very real need
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  - on so many things for a human in
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  - the loop, a person in the loop, a
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  - highly trained professional loop. Talk a little bit
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  - about that.
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  - Absolutely.
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  - And you nailed it. I mean, that's that's
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  - exactly what we're seeing. We've put a lot
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  - of, you know, automation workflows into place,
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  - but you have to have, as I mentioned
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  - earlier, that governance piece of it. Someone has
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  - to be watching.
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  - You know, it's the system is garbage in,
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  - garbage out. You know? I hate that for
• 7:14
  - lack of a better term. But whatever the
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  - system is learning, you know, it has to
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  - be appropriate. And sometimes things,
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  - you cannot let the system and the automation
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  - make,
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  - it it can't make assumptions
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  - that you have to have someone taking a
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  - look at the nuances that are there. I'll
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  - I'll give you an example. We we automated
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  - some some features
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  - with our practice management software, and I'll keep
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  - that I'll keep that off the talk so
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  - I can be anonymous with that. So it
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  - because it's any any, any organization that's using
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  - AI is going to have the same issue.
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  - And what happened was is we automated a
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  - workflow.
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  - And
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  - when we went live with it, we found
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  - out that the system started erroneously adding a
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  - modifier to our anesthesia procedures that it should
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  - not have been. And there was some definite
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  - pay payment
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  - attachments to this modifier it was adding, and
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  - it added it to every single case. We
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  - went through a whole two year testing before
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  - we went live. We went through all scenarios,
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  - and no one, you know, no one could
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  - know that this was gonna happen. And what
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  - should have happened is that we went in
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  - a small piece. A small batch went out
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  - the door. And, you know, before
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  - there's a lot to be learned here, but
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  - at the same time, we should have had
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  - people in place
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  - to look at every single part and piece
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  - that went out on that claim. That's just
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  - one small example.
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  - We we've got a lot of governance areas
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  - of where we are now having special projects
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  - team. So I have a whole new department
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  - that we've created, and their whole job is
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  - is it's it's special projects team, but the
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  - special projects, if you will, they're part of
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  - our a strategy as, you know, strategic plan
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  - of we have new we have new problems
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  - now that we didn't have before, and
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  - it's harder to find those problems sometimes. This
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  - one that I gave you, you know, that
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  - one was pretty obvious, but there are things
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  - that get embedded
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  - and hidden in the system.
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  - And what happens is systems tend to with
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  - especially with AI automation is tends to layer.
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  - It denials is a great example. The it
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  - will layer denial over denial over denial, and
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  - you think you have a denial for one
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  - problem. But then when you open up the
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  - claim and start deep diving into it, we
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  - were finding there were really the root cause
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  - was not even
• 9:21
  - transposing into the system. I don't wanna get
• 9:23
  - too detailed for you and lose everybody there.
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  - But but the end of the day, what
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  - we thought we were getting in a denial
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  - report was not the true denial of what
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  - we should be, you know, acting upon and
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  - creating a a root, you know, root cause
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  - analysis and go back and fix it at
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  - inception instead of that in you know, the
• 9:38
  - definition of insanity
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  - of doing the same things over and over.
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  - A 100%. And and talk about as you
• 9:44
  - get into
• 9:45
  - the latter half of this year, into next
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  - year, what are you most focused on and
• 9:49
  - excited about? What's the most interesting thing you're
• 9:51
  - watching?
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  - I think the most interesting thing that I'm
• 9:55
  - watching, again, is what we can do with
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  - the analytics
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  - because,
• 9:59
  - one of the things that we have been
• 10:01
  - able to do is take the information and
• 10:04
  - learn so much more on a faster, you
• 10:06
  - know, on a faster level. In the past,
• 10:08
  - we would have to take all the payment
• 10:09
  - data, put it into of course, and we
• 10:11
  - would use our Power BI and our Excel
• 10:13
  - tools. And, you know, you can only pivot
• 10:15
  - so far and learn information. Now we can
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  - it it the most exciting piece of it
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  - is,
• 10:21
  - understanding our reimbursement trends and understanding
• 10:25
  - areas where
• 10:26
  - we thought we were being a paid paid
• 10:28
  - appropriately where we weren't. And that's exciting for
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  - me because we were never able to discover
• 10:33
  - that. One area,
• 10:35
  - we found
• 10:36
  - is some of our payers are using,
• 10:38
  - the denial codes. We refer to those as
• 10:41
  - CART codes,
• 10:42
  - c a r c, and those are the
• 10:44
  - why a claim is denied.
• 10:46
  - Well, there's specific areas of that that you
• 10:48
  - can automate, and some of those don't need
• 10:50
  - a human to touch those. Even before AI,
• 10:52
  - you didn't need a human to touch it.
• 10:55
  - And most organizations now put in automation to
• 10:58
  - have those automatically written off. But by doing
• 11:00
  - payer analytics that I couldn't do before, we
• 11:03
  - discovered
• 11:04
  - that some of the payers were using those
• 11:07
  - card codes inappropriately,
• 11:08
  - and they were a 100% denying those instead
• 11:11
  - of taking, like, a contractual allowance is a
• 11:13
  - great example.
• 11:14
  - You know, that's where your fee schedule is.
• 11:16
  - You know how much you're gonna be paid.
• 11:18
  - Let's say your payer is Blue Cross Blue
• 11:20
  - Shield. Blue Cross Blue Shield's gonna pay you
• 11:22
  - $75
• 11:23
  - of your 100% you know, $100 charge. The
• 11:25
  - system automatically will come in and sweep those,
• 11:28
  - adjust you know, contractual adjustments off. Well, we
• 11:31
  - found that some of the payers are inappropriately
• 11:34
  - applying card codes.
• 11:37
  - It's a system issue, but it it's hidden,
• 11:39
  - and it's the the devil's in the detail.
• 11:41
  - If it's automatically written off, no one's going
• 11:43
  - to see that denial, and you've got thousands
• 11:45
  - upon thousands of dollars that are missed that
• 11:47
  - are being inappropriately,
• 11:49
  - assigned to the wrong area. So it's things
• 11:51
  - like that.
• 11:52
  - We are learning so much about what's happening
• 11:55
  - in our own system that we never could
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  - have realized before.
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  - That's literally remarkable.
• 12:01
  - And talk a little bit about you've had
• 12:03
  - this great leadership career,
• 12:05
  - great professional career.
• 12:07
  - What advice would you give to emerging leaders?
• 12:10
  - So emerging leaders,
• 12:12
  - first,
• 12:13
  - learn the business deeply enough that you can
• 12:15
  - connect your strategy
• 12:17
  - to what actually happens at the front line.
• 12:20
  - You know, you learn a lot about, you
• 12:21
  - know, while we're in school or while we
• 12:23
  - go through certification courses or whatever. You learn
• 12:25
  - about the way that the the, you know,
• 12:27
  - the industry is, but you have to learn
• 12:29
  - truly.
• 12:31
  - You know, you've gotta learn deeply enough of
• 12:32
  - what's really going on so you could put
• 12:34
  - that into an effective
• 12:36
  - plan. Leadership is not just setting a direction.
• 12:39
  - It's understanding how that direction affects clinicians, patients,
• 12:43
  - and people doing the work every day. You
• 12:45
  - have to you have to understand everyone's workflow.
• 12:48
  - I'm not saying a leader's supposed to get
• 12:50
  - down into the weeds of doing it, but
• 12:52
  - you need to understand what the roles are.
• 12:54
  - And second, I would say that it's really
• 12:56
  - important to become comfortable leading without direct authority.
• 12:59
  - And what I mean by that is not
• 13:00
  - stepping outside of authority. But in a complex
• 13:03
  - health care organization,
• 13:05
  - many of the people who, you know, whose
• 13:06
  - partnership you need will not report to you.
• 13:09
  - You've got those internal clients, if you will,
• 13:12
  - that you've gotta learn how to make those
• 13:14
  - relationships and understand how their role affects you.
• 13:17
  - And that's one of the things that, you
• 13:18
  - know, I had a leader, a mentor that
• 13:20
  - that taught me that. And I think I
• 13:22
  - would have missed it for a lot of
• 13:23
  - years had that not been pointed out to
• 13:24
  - me because you earn alignment for your credibility
• 13:27
  - and your transparency, your your ability to partner
• 13:30
  - with others, and then, of course, data and
• 13:33
  - genuine understanding of the of everyone's priorities and
• 13:36
  - how they're different.
• 13:37
  - And then I think the the the last
• 13:39
  - thing,
• 13:40
  - and, you know, most importantly,
• 13:43
  - this is a big lesson for me, and
• 13:44
  - it took me a while to get this
• 13:45
  - one, is do not confuse activity with progress.
• 13:48
  - You know, you hear the term
• 13:50
  - work smarter, not harder. You know, you have
• 13:52
  - to establish meaningful measures and be clear about
• 13:55
  - the outcome you're trying to achieve. You gotta
• 13:57
  - understand what is it you're trying to do
• 13:59
  - here and be willing to change course when
• 14:01
  - the data tells you something's not working. You've
• 14:03
  - gotta go back to the table. Don't put
• 14:05
  - a plan in place. I'm not saying to
• 14:07
  - change constantly, but you've gotta measure what you've
• 14:09
  - put into place and make sure that, you
• 14:11
  - know, is it effective? If not, what do
• 14:13
  - you need to tweak with that?
• 14:15
  - And then, of course, with that, you surround
• 14:16
  - yourself with talented people. I have one of
• 14:19
  - the best teams. I'm so proud of my
• 14:21
  - team. I know I can trust them. We
• 14:22
  - have full you know, we have you know,
• 14:25
  - it's it's we've got complete,
• 14:27
  - we all have line of sight with what
• 14:29
  - each person is doing. We lean on each
• 14:31
  - other, and we create an we've created an
• 14:33
  - environment where, you know, we can challenge each
• 14:35
  - other's assumptions without being afraid to speak up,
• 14:38
  - but then also develop those new skills and
• 14:40
  - take ownership of those.
• 14:42
  - And at the end, I guess my final
• 14:43
  - on that is evolving leaders sometimes feel they
• 14:45
  - they have to have every answer, and you're
• 14:47
  - not gonna know every answer. Strong leadership
• 14:50
  - is not about being the smartest person in
• 14:52
  - the room. It's about creating the conditions in
• 14:54
  - which the whole room can succeed together as
• 14:57
  - a team. When you're when you're trying to
• 14:58
  - be successful on your own, it's just never
• 15:00
  - gonna pay out for you.
• 15:02
  - Thank you so much. I I love your
• 15:04
  - point and how almost all of us work
• 15:06
  - in matrix organizations
• 15:08
  - of some sort.
• 15:09
  - In building alliances, partnerships, being reliable to people,
• 15:13
  - knowing who is great to work with,
• 15:16
  - knowing who to help with the problem, whatever
• 15:18
  - it might be is so important a part
• 15:21
  - of success
• 15:22
  - is, you know, like like,
• 15:24
  - one of my roles, I've served in a
• 15:25
  - 1,200 person law firm,
• 15:27
  - And knowing who the right lawyers are to
• 15:29
  - work with either right clients is so so
• 15:32
  - important,
• 15:32
  - and it doesn't come from direct operational responsibility
• 15:35
  - or direct supervision. It's knowing, okay, that person's
• 15:38
  - in that department, but they're great. So I
• 15:39
  - want them working with this with this client
• 15:41
  - or this person
• 15:43
  - is so, so important. And it's it's not
• 15:45
  - on the it's not on the org chart.
• 15:47
  - It's not on the it's not on the
• 15:49
  - typical advice, but it's a really important skill
• 15:51
  - and set in any
• 15:53
  - any
• 15:55
  - significant organization of any size at all. I
• 15:57
  - I think that just is brilliant and and
• 15:59
  - right on, and and I it resonates so
• 16:01
  - well.
• 16:02
  - No. I wanna thank you for joining us
• 16:04
  - today. Just brilliant. What a tremendous professional and
• 16:07
  - leader.
• 16:08
  - Thank you so much for joining us today
• 16:09
  - on the Becker's Healthcare Podcast. What a pleasure
• 16:11
  - to visit with you. Thank you so much.
• 16:13
  - Thank you. I I appreciate it. Thank you.