Hospitals plan for EHR downtime and ransomware. Almost nobody plans for the day their revenue cycle AI stops working, or keeps running and gets worse without anyone noticing. Here's how leading health systems decide which AI tools need a continuity plan, who gets to pull the kill switch, and what to keep in reserve.

The January 1, 2027 electronic prior authorization deadline is close. See where payers and EHRs stand and what revenue cycle leaders should do now.

Health systems are debating whether to tell patients when AI is involved in their care. Meanwhile, automated and AI voice calls about appointments, estimates, and balances are scaling fast. Here's what federal rules already require, where the gaps are, and how revenue cycle leaders can set a disclosure policy before a patient complaint sets it for them.

Medicaid work requirements start January 1, and most of the people who lose coverage will still qualify for it. They'll lose it to paperwork. At the same time, the retroactive coverage window your financial counselors rely on shrinks from three months to one. Here's what changes and what revenue cycle teams should do before New Year's.

Health systems are building AI portfolios like a maze: one defensible decision at a time, with nobody checking whether the pieces agree. Here's what that costs, and the two-week exercise that surfaces it.

The AHA said this week that hospitals cannot afford to defend themselves against attackers using AI. Two AI companies immediately offered to help pay for it. Meanwhile a phishing campaign is wearing MyChart's name, and a new executive order exposed how little hospitals know about their own equipment. Here is what all of it does to your cash.

I made a pile of predictions about revenue cycle in 2030. Here's an honest scorecard against 2026 reality, including the two I got badly wrong.

Almost every headline about the new physician survey led with burnout. I read the whole thing twice, and burnout is not what these doctors are telling us. They are telling us they cannot give their patients the care they know how to give.

A Jefferson Health employee turned two weeks of work into four hours for $75 in AI tokens. Great trade, once. The trouble is that nobody has solved forecasting token spend, only 18% of the health systems scaling AI hardest can measure what it's returning, and most of that consumption isn't landing in revenue cycle expense at all. Which means your cost to collect is understated and you don't know by how much.

Twenty-one health systems have named a chief AI officer. The healthcare jobs with the highest share of remote postings are coding specialist, utilization review nurse, care navigator, and Epic clinical analyst. Those are the same four jobs on every automation slide in America. We are building the 2030 org chart from the top down and the bottom out, and nobody is paying for the part in the middle.

Providers pulled roughly $15 billion out of No Surprises Act arbitration last year, up from $4.1 billion the year before, and they're winning 87 percent of determinations. I've been chewing on that win rate all week, because a number that high in an adversarial process isn't a competitive advantage. It's a signal the process is mispriced, and mispricings in healthcare payment don't last.

Most of the coverage of the 2027 Medicare rule stopped at the rate cut. Further in, past the tables, Medicare stops proposing things and starts asking questions. One of them: if technology does part of the work of a primary care visit, how much should the visit be worth? Nobody has asked that in a payment rule before, and it will matter more to your revenue cycle than the rate cut will.

While hospital strategic plans debate AI pilots, private equity signed a $12 billion revenue cycle deal, Ascension bought 300 surgery centers, and investors stopped counting AI as a differentiator. The capital already voted on what 2030 looks like.

Six hundred and two hospitals are already running a combined $10 billion deficit, and that's before a single federal cut has landed. I read the full report, the appendices too, so you don't have to. Here's what's advocacy framing versus hard CMS data, and the three things your board needs to hear before this shows up as next quarter's bad news.

34 AI healthcare laws passed in 21 states in 2025 alone. Here's what CFOs and RCM leaders actually need to do about the patchwork, before Washington ever weighs in.

I forecast the future of the revenue cycle from a travel company — no hospital in sight. That's not as strange as it sounds. The reason I can see where RCM is headed has little to do with being in healthcare and everything to do with no longer being buried alive in it. A piece about altitude, thinking time, and the industry that quietly steals both from the leaders who need them most.

Every hospital is fighting the same fire right now: denials, rework, coding, labor cost. Good. But there's a second fire in the building, and almost nobody is pointing a hose at it. Operational efficiency and structural revenue loss are two different problems, and you can't automate your way out of the second one.

We keep looking for someone to blame for rising healthcare costs, and we keep hoping AI will rescue us. After most of a career in the revenue cycle, I think both instincts are getting in the way of the work that actually moves the number. Here is why.

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Automation doesn't shrink your revenue cycle team; it changes what they have to be good at. Here is why AI is creating more work, not less, and what hospital CFOs should do about it before 2030.