My doctor spends 5 minutes reading my chart. I just gave her 30 seconds.
We pledged to CMS to Kill the Clipboard. Here's the skill that does it, and why the clipboard isn't actually the problem.
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I walked into a specialist appointment last month and watched my doctor do the thing every specialist does.
She opened my chart. She scrolled. She squinted at a lab from another hospital that had imported as a flat PDF. She tabbed back to the medication list, then to the problem list, then back to the labs. Her hand was already on the keyboard, ready to start typing the visit note, and she still didn’t have the picture she needed. Fifteen minutes on the calendar. Five of them already burned before she said hello.
I had the picture. I’d had it for years. I had twelve years of FHIR observations from five different portals sitting on the Linux box I run Tula on. I had a month of home BP readings from the Omron next to my bed. I had the new statin another doctor had started six weeks ago. I had three questions I’d written down at 2 AM the previous Tuesday. None of it was anywhere she could see it.
That gap is the entire opportunity. This week I started building the skill that closes it. It’s called prep-my-visit, and it’s the natural next step after the CMS pledge we just signed to Kill the Clipboard.
What the data actually says about the chart-review tax
An EHR-log study cited by Ambience Healthcare a few weeks ago put a number on what I was watching that morning. Ambulatory doctors spend roughly 16 minutes per patient encounter inside the EHR, and about a third of that, around 5 minutes, is chart review. Five minutes of hunting through the record before they can be present with the patient in front of them.
That’s the clinician’s tax. It happens because the chart is built for billing, for documentation, for legal defense, for the org chart of the EHR vendor. It is not built for the next thirty seconds of a doctor’s day.
prep-my-visit makes those five minutes thirty seconds.
What the skill does
Forward your calendar invite to Tula. Or let it pick up the Appointment resource Tula already pulls from your portals. Seventy-two hours before the visit, Tula does the assembly work:
It reads everything you’ve authorized it to read across every connected hospital. Conditions, medications, allergies, recent labs, recent imaging, recent procedures, family history. It diffs the current state of your record against the last time you saw this specific provider, so the brief leads with what’s actually new since their last note. It pulls the relevant trends from your wearables and home devices. It reads the journal entries you wrote during the week. It asks you one question over Telegram: what are your top one to three goals for this visit?
Then it produces two pages. Hard limit.
Page one is for the doctor. Three lines at the top, the bottom-line-up-front the experienced clinician reads while still walking into the room. Below that: your goals verbatim, the delta since their last visit with you, the trends that matter for their specialty, the reconciled medication list with the originating prescribers, and a quiet footer with a QR code that links back to the source FHIR data on your own server if she wants to drill in. One page. Eleven point type. No filler.
Page two is for you. Your goals in plain language, the questions you wanted to ask, what numbers the doctor might bring up and what they mean, what to bring, and a note that Tula will pull the new clinical note from the portal after the visit and grade whether your goals got addressed.
Every numeric value in the brief cites a source FHIR resource ID on your VM. The eval spec for the skill enforces zero hallucinations. If a number can’t be traced to a real resource, it doesn’t appear in the brief.
The whole thing runs on the same $30-a-month Linux box that pulls my records. No SaaS. No cloud chart vendor. No third party touches the data.
Why the patient-goals section is at the top, not the bottom
There’s a randomized controlled trial out of Quito, Ecuador with 199 patients on at least one chronic medication. The patients who received help completing a pre-visit form were more than twice as likely as usual-care patients to report achieving everything they wanted during the visit. Goals at the top of a brief are not decorative. They are the highest-leverage three lines on the page.
Every consulting-grade pre-visit summary I’ve ever seen pushes the patient voice into a footer. prep-my-visit puts it second only to the BLUF. The doctor sees what the patient came in for before she sees anything else.
The CMS pledge, and why the clipboard isn’t actually the problem
Two weeks ago, RealActivity submitted four pledges to the CMS Health Tech Ecosystem, the voluntary initiative Amy Gleason has been pushing across the industry. Tula is pledged in Patient Facing Apps under two sub-use cases: Conversational AI Assistants at Launched/GA, and Kill the Clipboard at Pilot/Beta. The Pilot/Beta call was deliberate. CMS itself describes Kill the Clipboard as the visionary criterion, and explicitly invites early adopters to collaborate on the implementation guidelines.
Amy Gleason has been blunt about why this matters to her personally. Quoting her from MeriTalk: “My daughter takes 21 medications, and she has to try to write them all out every single time. She hates that, so I’m trying to kill the clipboard.” Her image of the future is checking into the doctor’s office the way you board a flight. Scan a code. The information moves.
That’s the right starting point. It’s also not the finish line.
The clipboard is the symptom. The actual disease is that patients have never had a way to deliver themselves to their providers. Killing the paper form solves the patient’s hand cramp. It doesn’t solve the doctor’s five-minute chart-review tax. It doesn’t solve the fact that the cardiologist still doesn’t know about the statin the PCP at the other hospital started last month. It doesn’t surface the four nights of bad sleep the patient’s Garmin caught.
prep-my-visit is the bridge. Kill the Clipboard is what you stop doing. The brief is what you start doing instead.
The closed loop that makes this open-source
Here’s the part that no SaaS chart vendor can ship, no matter how much money they raise.
After the visit, Tula pulls the new clinical note from the portal via the same SMART-on-FHIR connection that gave the agent OAuth access in the first place. Then it runs an eval against the brief it generated. Did the doctor address each of the patient’s three goals? Did the flagged items get mentioned in the note? Did the delta land in the assessment?
That feedback loop only works on the patient side of the OAuth boundary. The patient is the one entity in healthcare whose data is allowed to follow them everywhere. The agent sits on the patient’s box, with the patient’s tokens, holding the only complete copy of the record. That’s not a competitive moat. That’s a structural fact about where the patient’s data is allowed to live under the 21st Century Cures Act.
This is why the right place for Kill the Clipboard infrastructure is not a vendor cloud. It’s the patient’s own agent.
What this looks like at scale
Now imagine every patient walking into your service line shows up with one of these. The cardiology fellow on a Tuesday morning gets a one-page brief for every patient on her panel, drawn from the patient’s full longitudinal record, with the patient’s own goals at the top. The fellow’s five minutes of chart review per patient becomes thirty seconds. The visit starts with the patient’s voice, not with the doctor catching up.
That’s the conversation we’re starting with academic medical centers. The personal agent runs on the patient’s box. The hospital-scale governance, identity, audit, and integration layer we’re building at RealActivity is called Aria. The skill is the same. The boundary is the OAuth handshake.
If you run an AMC and you want to be the first one to try this with a cohort, the contact info is in the repo.
A note for builders
This is the first Tula skill we’re publishing with an explicit promise of portability. The SKILL.md, the IPS template files, the clinical guideline reference set, and the Waza eval spec are platform-neutral artifacts. They speak FHIR R4. They speak the International Patient Summary standard. They cite published clinical guidelines by name and date. They don’t depend on the OpenClaw runtime in any way that prevents them from running elsewhere.
What that means concretely: drop the same SKILL.md into a Claude Skill and the skill runs against the same FHIR resources. The same logic wraps cleanly into a Microsoft 365 Copilot agent built in Copilot Studio, the enterprise side of Microsoft’s stack. And the same patterns apply to Microsoft Copilot Health, the consumer version of Copilot that Microsoft launched in March to ingest patient records and wearables and help users prepare for doctor visits, when that surface opens up to third-party skills. The IPS Bundle the skill emits is the same Bundle no matter which runtime generated it. Tula is the reference implementation, not the only implementation.
It also happens to ship with the most comprehensive eval spec we’ve published to date. Twelve enforced criteria covering hallucination, IPS conformance, page-length limits, reading-grade level, citation discipline on every lab suggestion, snippet length, attachment size, and the closed-loop check against the post-visit note. If you’re building agent skills in the healthcare space, the eval discipline is more transferable than the skill code itself. Worth a read regardless of which runtime you’re targeting.
The full spec, SKILL.md, templates, and Waza eval will be in the repo under skills/prep-my-visit/ this week.
What you can do right now
If you want this skill for yourself, star the Tula repo. The build spec is going up in docs/specs/ this week. The SKILL.md, Waza eval spec, and the first three visit-type templates (PCP annual, cardiology follow-up, specialist first visit) will follow. Apache 2.0.
If you’re a clinician reading this: this skill is not anti-doctor. It is the opposite. It is pro-doctor in a way that almost nothing in the AI-in-healthcare conversation has been. Five minutes a patient, twenty patients a day, times every doctor in the country. That’s the prize.
If you’re a patient reading this and you’ve ever sat across from a doctor who clearly hadn’t read your chart: you’re not crazy, and you’re not powerless. The chart was never going to work for you. The brief was always the answer.
If you’re a healthcare AI builder reading this: the eval spec is the part that took the most work and the part you’re most likely to want to copy. Take what’s useful.
Kill the clipboard. Then give your doctor the page your chart should have been.
Paul
prep-my-visit is open-source software for personal health organization and health literacy. It is not a medical device, not FDA-cleared, and not intended to diagnose, treat, cure, or prevent any disease. Talk to your doctor about anything that matters.
Sources & Further Reading
Ambience Healthcare. “Patient Recap” announcement, citing EHR-log study on chart review time.
Cherrington, A., et al. “Improving Preclinic Preparation for Patients with Chronic Conditions in Quito, Ecuador: A Randomized Controlled Trial.” International Journal of Family Medicine.
MeriTalk. “CMS Pushes Modern Tech Tools for Patients, From QR Codes to AI.” September 2025.
Connecting for Better Health. “What to Know About the New CMS Health Tech Ecosystem.”
OpenClaw. Open-source autonomous AI agent runtime.
Paul J. Swider is CEO & Chief AI Officer at RealActivity, a Microsoft Partner specializing in mission-critical AI for healthcare systems. He has 30+ years in healthcare technology, has trained over 3,000 engineers across GE, IDX, and Microsoft, and is the founder of BOSHUG, the Boston Healthcare Cloud & AI Community spanning 50+ countries.