Turning the data hospitals already have into the harm they can't otherwise see - in real time, and with the law on their side.
Here is a fact that should be more alarming than it is: for decades, the standard way a hospital learned that it had harmed a patient was to wait for a staff member to fill out a form. Pascal Metrics looked at that arrangement and decided the form was the problem.
The pitch, stripped of jargon, is almost aggressively sensible. A modern hospital generates an enormous exhaust of data - lab values, medication orders, vitals, notes - all sitting inside an electronic health record. Most of it just accumulates. Pascal Metrics runs evidence-based "triggers" and algorithmic logic across that stream to convert it into something a hospital can actually act on: clinically validated adverse-event outcomes. Not a hunch that something went wrong. A record that it did.
The number the company likes to cite is 10x. Multiple studies, plus Pascal's own data, indicate that the trigger method surfaces at least ten times more serious adverse events than the voluntary event-reporting systems hospitals have leaned on for years. If you find that number uncomfortable, you are reacting correctly. It means the industry standard was mostly measuring how often people remembered to report - not how often patients were harmed.
The company is named, with some deliberateness, after Blaise Pascal, the 17th-century mathematician usually credited as the founder of risk management. Pascal worked out probability to help gamblers understand their odds. Pascal Metrics is doing roughly the same math, except the stakes are a patient in a bed rather than a wager on a table. The rebrand is doing real work here: this is a company that thinks harm is a measurable, predictable quantity, not an act of God.
There is also a lawyerly bit of cleverness at the core. Pascal operates as a federally certified Patient Safety Organization - PSO #0047 - which in the United States is a specific legal structure. A PSO is a "safe harbor": hospitals can study their own mistakes inside it without the findings becoming ammunition in a lawsuit. Most people experience that structure as paperwork. Pascal built a real-time analytics engine and a machine-learning pipeline inside it. That is the whole trick, and it is a good one.
You cannot manage what you refuse to measure. Pascal Metrics' entire business is a refusal to stop measuring.
The cloud SaaS core. It ingests real-time EHR and health IT data and converts it, through trigger and algorithmic logic, into validated adverse-event outcomes - with surveillance, reporting, and interactive analytics on top.
The harm-finding engine. Built around the trigger method that consistently identifies roughly 10x more serious adverse events than voluntary event-reporting systems have managed for decades.
Clinical risk analytics and the Risk Trigger Monitor, aimed at flagging emerging clinical risk while there is still time to change the outcome rather than document it.
Consulting anchored by the Team-based Engagement Model, co-developed with the Mayo Clinic - because software finds the harm, but people and culture are what reduce it.
The web-based surveillance and analytics layer that plugs into Epic, Cerner, Meditech and other major EHRs, so the data flows in without a rip-and-replace.
Federally certified Patient Safety Organization status gives clients a non-punitive "safe harbor" - legal protection for the honest study of their own adverse events.
Real-time actionable insight into harm - and the risk that follows.
Before healthcare, Ladner was Chief Information Officer of the U.S. Department of the Treasury, where he ran a $2.6 billion IT organization. Earlier still, he was a general manager at JBoss, the open-source middleware company later acquired by Red Hat. He holds an MBA from Harvard, an MA in theology from Oxford, and a degree in international economics from Georgetown's School of Foreign Service. It is an unusually eclectic résumé for a man who decided the most interesting unsolved problem was whether a hospital can know, in real time, that it just hurt someone.
Illustrative comparison of serious adverse events surfaced. Source: Pascal Metrics and cited studies. The gap is the harm that was always there and simply never got written down.
Pascal Metrics is established, betting that clinical data could stop being a rear-view mirror. At the time, comprehensive inpatient EHR adoption sat around 3.6%.
Backers including Capital Factory and Disruptor Capital come on board; total reported funding across rounds approaches ~$11M.
Pascal becomes, by its account, the first to use real-time EHR data inside a U.S.-certified PSO and to train predictive models on adverse-event outcomes.
The company leans into AI for patient safety and a "CFO-grade business case," refreshing its brand and product lineup around Platform, Safety, Risk, and Strategy.