Matthew Gullicksrud

The Hard Part Was Already Built

Matthew Gullicksrud — Sat, 17 Oct 2026 00:00:00 GMT

When I joined, the hardest part of the platform was already built. It turned out not to be the hard part.

In 2015, an industry forecast projected that 105 million Americans would be covered by Accountable Care Organizations by 2020.¹ By mid-2019 the real number was about 44 million.² That’s real growth, but less than half of what the industry was betting on. I was one of the people responsible for making that bet pay off.

The bet

In 2014, healthcare went all-in on “population health.” The Affordable Care Act gave rise to Accountable Care Organizations (ACOs), and the logic was simple: find the people who are about to get sick, intervene early, and keep them healthy. Prevention is cheaper than treatment. Those savings were supposed to let health systems stop getting paid per visit and start taking financial responsibility for the health of a whole population.

Every major health IT vendor had a population health platform. I was brought in to deliver one.

My seat

I ran customer success for one of the largest private health information exchanges in the country: a data network connecting more than 300 care settings across a major US health system. When our platform won their population health business, my job was to build the strategy to implement and operationalize it, sell that plan, and then deliver it. In other words: turn what had been promised into the ROI it was sold on. You could argue we won because the data connections were already in place. I can’t say for sure.

Three pillars

The platform rested on three pillars: data, registries, and interventions.

Registries were the differentiator: the logic that scans a population and flags who needs attention. They were built before I arrived, on years of research by leading academics and clinicians. Everyone believed that was the hard part, and it was done.

Where it broke

Two problems showed up. Ten years later, they still do.

First, the data. Registries need clean, complete, consistent inputs. Healthcare data in 2014 was none of those things. Systems didn’t talk to each other, the same patient looked different in every source, and fixing it was bigger and more expensive than anyone had budgeted. It was solvable, but costly.

Second, the intervention. Even with a perfect list, someone has to get that insight to the right clinician, at the right moment, inside a workflow they already use. Then that clinician has to reach a patient who has to change their behavior. Every handoff is friction, and every handoff is a person. That turned out to be the real product, and it’s the part software couldn’t deliver on its own.

AI can widen the funnel. Getting someone to act is still change management.

Ten years later

Here’s my provocation: data access and normalization is solved. Not today, but I’d bet within 5–10 years. AI is compressing years of interface and cleanup work into something much closer to months.

The intervention problem is different. I don’t believe AI closes that loop. Better lists don’t create trust, time, or a relationship between a care team and a patient who, I believe, wants to be healthier. AI can widen the funnel. Getting someone to act is still change management. I’d love to be proven wrong.

Same play, different industry

I work in permitting and development now, and I see the same three pillars. The data is application, parcel, and plan data. The registry is the code logic that decides what a project needs. The intervention is an applicant, reviewer, or inspector doing the next right thing at the right moment.

The way I frame it: technology works when the right data reaches the right hands, in the right place, at the right time. When modernization stalls, it’s rarely because the tool can’t do the job. It’s because the workflow never changed around it.

Where have you seen the last mile, not the technology, decide whether a modernization worked?

Leavitt Partners projection, December 2015, reported by Healthcare Innovation. ↩
Duke-Margolis Center for Health Policy, New research shows impact of recent policies on ACO growth, 2019. ↩

Views are my own and do not represent any current or previous employer.

Is the City the Primary Care Physician?

Matthew Gullicksrud — Sat, 10 Oct 2026 00:00:00 GMT

What if a city treated every property like a patient? Someone would need to know its history, coordinate the specialists, track what still needs attention, and make sure the work doesn’t fall through the cracks.

I spent my first career in health IT, working on the technology and information exchanges needed to coordinate care across organizations. Now, in city permitting, I see a familiar challenge: having the information is one thing; getting the right people to act on it in unison is another. The deeper I go, the more convinced I am that the two are climbing the same curve, and permitting is behind. That’s good news, because we get to see what’s coming.

The analogy isn’t perfect, but in a city, should that be the City’s job?

Every property in a growing city needs care. That means holding the chart, knowing the history, sending the case to the right specialists, and making sure the plan actually gets followed.

The same curve

Both fields have moved through the same four stages:

Paper. Paper charts and film X-rays. Paper plan sets, light tables, and printed zoning maps.
Digitized. Electronic health records. Electronic plan review and desktop GIS.
Connected. Health information exchanges and interoperability standards. Open data APIs, layered web maps, and records organized around the parcel.
Assisted. Clinical decision support, AI-assisted imaging reads, and ambient scribes. AI pre-screening of applications, automated code checks, and 3D site analysis.

Each stage was unlocked by something computers suddenly made cheap: storage, then networks, then rendering, then machine learning. The clearest parallel is mapping. Maps are to permitting what imaging is to healthcare. Film became digital imaging, which became AI-assisted reads. Paper zoning maps became desktop GIS, which became web maps and 3D models that can check a site before a person ever opens the file.

What pushed each field forward

Early in my health IT career, I worked on a project to digitize paper medical charts. As consultants on-site, our office was the room where those charts had been stored, right next to the hospital morgue. Years later, when I started working in permitting, I heard a familiar story: paper plan rolls were no longer being passed around, and the space once used to store them had been repurposed.

In 2008, 9% of US hospitals had even a basic electronic health record. By 2024, 99% had a certified one.¹ That didn’t happen on its own. The HITECH Act in 2009 paid providers to adopt.

Permitting’s push came eleven years later, and it wasn’t a law. In a survey of more than 1,150 code officials in spring 2020, 40% said they couldn’t do electronic plan review, and 30% said they couldn’t do any part of permitting remotely.² Then the counters closed, and the work had to keep moving.

Where it stalls

Here’s what healthcare learned the hard way: digitizing is not transforming. In the early EHR years, clinicians were clicking through digital copies of paper forms to check a compliance box. The records were electronic, but the care was the same.

Healthcare’s next challenge was changing the incentives around care. The Affordable Care Act established Medicare’s Shared Savings Program, encouraging accountable care organizations to coordinate care while improving quality and controlling costs. The lesson wasn’t that coordination suddenly became possible; it was that technology alone wasn’t enough. The operating model and incentives had to support it.

Permitting got its HITECH moment. It never got its ACA. (Should it? That’s a question I’ll explore.) A lot of electronic plan review today is still a PDF of a paper process.

The City as PCP

A good primary care physician doesn’t do the surgery, run the labs, or fill the prescription. They own the chart, triage, refer, and make sure the loop gets closed.

For a property, the City can play a similar coordinating role: helping applicants and reviewers work from the right information, making handoffs visible, and identifying unresolved issues. That doesn’t mean one office controls every decision. It means the process should make responsibility and next steps clear. Map that onto a property:

The patient is the property.
The PCP is the City’s permitting and development office: intake, triage, coordination.
The chart is the property record: every permit, inspection, and violation.
The specialists are fire, transportation, water and utilities, historic preservation, and environmental review.
Referrals are plans routed to agency reviewers.
Labs and imaging are inspections, surveys, soils reports, and GIS layers.
Prescriptions are the approved plans and conditions of approval.
Physical therapy is code enforcement: corrective work that rehabilitates a property over time.
Care gaps are expired permits, open violations, and work that was never finalized.

One word matters here: coordinator, not gatekeeper. Healthcare tried the gatekeeper version in the 1990s, and patients resented a PCP who felt like a toll booth. The value of the role is that one party sees the whole patient and makes sure nothing falls through the cracks between specialists. It isn’t about controlling access.

Coordinator, not gatekeeper.

And every permit is a visit. Add the visits up and you get population health. For a city, that’s housing that gets built, infrastructure that keeps up, and growth that makes a place thrive instead of just getting bigger.

Stage four is already here

AI-assisted permit pre-screening is already being tested in practice. Seattle recently published results from a 2025 pilot that used AI to pre-screen residential permit applications. Completeness checks were 87% accurate and compliance checks were 92%.³ The more important finding was the caution: accuracy alone isn’t enough. A tool saves a full review cycle only if it catches every correction a reviewer would flag, and the city concluded its own codes need simplifying for automation to pay off.

Healthcare learned the same lesson with clinical decision support. Alerts only helped when they fired inside the workflow, at the moment of decision, in front of the person who could act. Fire them anywhere else and they’re noise.

That’s the framework I keep coming back to: Right Data, Right Place, Right Time, Right Hands. The tools are advancing, but the operating model still needs work, and that’s what the PCP role provides.

The decade we don’t have to repeat

Healthcare has shown that digitizing records is only the beginning. Better outcomes also depend on coordination, incentives, and getting information to the people who can act on it.

Permitting doesn’t need to repeat every lesson the hard way. And because property decisions affect the people and places around them, the case for coordination may be even stronger.

If the City is the PCP, which handoff breaks down most often in our cities, and what information would help the next person make a better decision?

ONC, National Trends in Hospital and Physician Adoption of Electronic Health Records. The 2008 figure is basic EHR; the 2024 figure is certified EHR. ↩
International Code Council, survey of code officials, March 22 – April 1, 2020. ↩
City of Seattle, Can AI speed construction permitting in Seattle?, Building Connections, June 2026. ↩