Provider Data Dorks

"My provider never got credentialed." Melissa Hinckley has heard that complaint for most of her career. Then she checks, and the provider has been credentialed since before she even entered healthcare. The real break is usually somewhere else, like a practitioner's NPI that was never linked to the tax ID on the contract. It still gets filed under credentialing, and so do the regulations written to fix it.

Melissa started in the Harvard Pilgrim call center taking member calls and has since run provider enrollment, credentialing, network adequacy and directory work at Harvard Pilgrim, Oscar Health, Mass General Brigham Health Plan and Point32Health, with a stint in fraud investigations along the way. In this conversation with Nick Helfrich and Mitch Gorodokin, she breaks down the provider enrollment lifecycle, the one question she trains every team to ask, and why regulators, payers and providers need to get in the same room to untangle provider data.

In this episode:

• Why every single thing a health plan does needs provider data, even HR

• How contracting, credentialing and enrollment combine into the provider enrollment lifecycle

• The question to ask when a provider says "credentialing": are they ready to bill?

• The ideal data hierarchy, from contract to tax ID to billing NPI to location

• Why one-to-many relationships make provider data so hard to model

• Death by a thousand attestations, and her case for spreadsheets for now

• How state-mandated CVOs add cost for anyone living near a state border

• Revalidation, ownership disclosures and the scramble at Medicaid plans

• Why health plans ask providers for 500 pieces of information

Subscribe to Provider Data Dorks for the people fixing healthcare's hardest data problem. New episodes weekly on YouTube, Spotify, and Apple Podcasts.

Timestamps:

00:00 Intro

01:00 Welcome Melissa Hinckley

03:02 From the call center to network operations

05:15 Using this podcast to train her team

05:57 Every single thing needs provider data

07:24 The provider enrollment lifecycle

09:11 Why credentialing gets slandered

09:50 Ask if they're ready to bill

14:58 Explaining provider data to her niece

17:08 The template that checks every step

22:51 The ideal data hierarchy

28:56 One provider, many roles, many entities

33:32 Why plans ask for 500 pieces of information

37:22 Death by a thousand attestations

38:01 Spreadsheets vs. portals

45:44 One doctor, two CVOs

55:56 Why regulators don't talk to each other

01:00:00 Ownership forms and the eight Rachel Sullivans

01:02:51 Revalidation is a hot topic

01:07:35 Lightning round

Every health plan knows its provider directory is wrong. Sury Agarwal has handed plans accurate, up-to-date corrections, complete with discrepancies and confidence scores, and heard that it was exactly what they needed. Then nothing changed. In one case his team found a doctor who died in December with more than 150 claims still coming in through May.

Sury is CEO and co-founder of Candor Health, an AI-native provider data platform that monitors more than 120,000 sources to track where doctors actually practice and take appointments. Before Candor, he was VP of Engineering and part of the founding team at Moat, which Oracle acquired for $850 million. In this conversation with Nick Helfrich and Mitch Gorodokin, Sury walks through the four generations of directory fixes, why accurate data alone doesn't move the needle, and what it takes to fix the problem at the source.

In this episode:

• Why "people make better decisions with more data" is the worst advice he's gotten

• The four generations of directory accuracy, and why the first three missed

• Why attestation is easy to audit and still isn't accurate

• The doctor still billing five months after he died

• Why plans can't act on corrections, from network adequacy to rosters that overwrite the fix

• Mopping the floor versus fixing the broken pipe

• Why payers and providers are both incentivized to keep networks bloated

• Moving from delegated to direct credentialing

• What Uber can teach healthcare about certainty

Subscribe to Provider Data Dorks for the people fixing healthcare's hardest data problem. New episodes weekly on YouTube, Spotify, and Apple Podcasts.

Timestamps:

00:00 Intro

03:27 What ad tech taught him about provider data

07:53 The four generations of directory accuracy

11:26 Why provider attestation fails

14:06 Why aggregating public registries fell short

15:47 Why claims data isn't the answer

17:03 150 claims after death

19:30 Why health plans can't act on accurate data

25:45 Fixing the problem at the source

28:28 Why nobody wants a smaller network

30:12 What separates plans with clean data

32:58 Why accuracy needs infrastructure

39:34 Where a health plan should start

40:29 Lightning round

44:01 Uber and the case for certainty

Anshul Rathi joined Oscar Health as one of its earliest employees and inherited a single spreadsheet. Every network was rented. He built the first system himself, one spreadsheet into fifteen spreadsheets talking to each other, and then it broke. He walked into the executive team and asked for engineering resources. What came back was a five-year roadmap and a $50 million price tag to build it in house.

So he looked at every vendor on the market and found the same thing everywhere: point solutions that didn't talk to each other, each one fixing a single symptom. Six years later Oscar had gone from two states to twenty, more than 40,000 providers credentialed, over 100 delegated hospitals. Somewhere in there he picked up the nickname the one man credentialing army, and the conclusion that the industry had misdiagnosed itself.

His reframe: provider data isn't a data problem. It's a trust problem wearing a data costume. Every health plan, every hospital, every state has its own version of "trust me," none of them talk to each other, and all of them still want a screenshot.

Nick Helfrich and Mitchell Gorodokin break their own rule and spend an episode on CertifyOS: the diary he filled with twelve pages about how the system should work while he had Covid in India, the battle that went all the way to a national plan's chief legal officer over whether a screenshot was ever legally required, why he walked away from the payer enrollment business and the revenue that came with it, and why he thinks a company like his shouldn't need to exist in the end state.

In this episode:

• One spreadsheet to twenty states, and the moment the buy-versus-build math stopped working

• Why the Federated States of America means fifty different healthcare ecosystems

• The accidental entrepreneur: a diary, a wife who told him to brush up his coding, and fifteen days

• Everyone says trust me, and everyone wants screenshots. How they got one plan to accept JSON instead

• Dorks vs. posers: swap "provider data" for "supply chain" and does the pitch still hold?

• What actually separates agentic AI from a bulk trigger pipeline with better copywriting

• Two models pointed at each other, and a hallucination rate that drops from 3-4% to 0.09%

• Why credentialing and payer enrollment keep getting conflated, and what breaks when they do

• Why the point solution era is ending, and what disintegrates a system of record

• The airport with no TSA, and what shared credentialing is actually trying to be

• Why 70% accuracy is the industry's gold standard, and why nobody should be celebrating that

• The dork litmus test: remove the word AI from your pitch deck. Does the plan still buy it?

Subscribe to Provider Data Dorks for the people fixing healthcare's hardest data problem. New episodes weekly on YouTube, Spotify, and Apple Podcasts.

Timestamps:

00:00 Intro

03:48 It's a trust problem wearing a data costume

05:16 The accidental entrepreneur: a diary, Covid, and fifteen days

08:56 Everyone says trust me, and everyone wants a screenshot

12:15 Dorks vs. posers: who actually has the scars

16:08 Agentic AI, or a bulk pipeline with better copywriting

19:24 Why the point solution era is ending

38:41 An airport with no TSA

40:57 Why he says CertifyOS shouldn't exist

55:03 Remove the word AI from your pitch deck

A health plan's claims kept getting denied. Everyone assumed the new claim system was the culprit, so that is where they looked. Melissa Goshorn's team found it somewhere else entirely, in the provider data feeding that system and the transformations it went through on the way in. Denials dropped 97%. As she puts it: nobody had any idea it was a provider data problem. They were not even considering that system at all.

Melissa is president of DocMe Health, the health division of digital services firm DocMe360, where the model is to sit inside a health plan's systems and files rather than hand over a three month assessment and leave. She started out in senior living, moved on to healthcare nonprofits working alongside some of the country's most prominent cardiologists, made a stop at a technology startup, and spent close to a decade supporting CAQH and its suite of provider data solutions. In this conversation with Nick Helfrich and Mitch Gorodokin, she argues that provider data is the red headed stepchild of healthcare data, and also the thing every other system is anchored on.

In this episode:

• The 97% denial reduction, and why nobody on that project suspected provider data until they were in the files

• Source of truth versus system of record, and the field level governance most organizations never put in place

• Why a phone number is never just a phone number: appointments, claims and prior auth each need a different one

• The one large plan she knows of with a genuinely clean directory, and the single rule that got it there

• Why "carrot or stick" is the wrong frame for getting providers to attest, and what she says instead

• Medicare Plan Finder, and the moment plans start treating provider data as a sales problem

• What happens when a FHIR based directory API gets transformed into a flat file on a batch job, and how many vendors a single member complaint now has to travel through

• Why most directory regulation only binds Medicare and Medicaid, leaving the commercial book as the Wild West

• How a plan that treats data as its differentiator organizes itself differently, right down to who is allowed to keep a spreadsheet

• Why the existence of an entire directory accuracy industry makes her sad, and how it connects to what health insurance costs

Subscribe to Provider Data Dorks for the people fixing healthcare's hardest data problem. New episodes weekly on YouTube, Spotify, and Apple Podcasts.

Timestamps:

00:00 Intro

01:33 Welcome to Provider Data Dorks

02:39 Meet Melissa Goshorn

04:31 Why she's allergic to the words strategy firm

06:27 How they cut claim denials by 97%

07:35 Source of truth, the most overused term in the industry

09:29 Why nobody gets down to one system

10:27 A phone number is never just a phone number

12:23 Governance at the field level

14:13 Putting your thumb on hard ROI

16:35 Which data points cause the most rejected claims

17:49 The one plan with a genuinely clean directory

20:18 What everyone else is doing instead

24:02 Walking through an engagement

26:47 Getting called in for the fire drill

28:35 If you know one health plan, you know one health plan

30:21 Paper, fax machines, and a state's largest payer

31:38 The FHIR API that became a flat file on a batch job

34:06 The Real Health Providers Act

35:20 Vendor fatigue and consolidation

41:53 Health plans are data-first organizations

45:28 The CFO conversation and the multi-year payback

49:39 Why adequacy is the wrong bar

50:36 The three million dollar filter

54:36 Is regulatory pressure actually moving the industry

1:00:35 Drawing the whole ecosystem on a whiteboard

1:04:05 Attacking the problem together

1:06:21 The unsung provider data point

1:08:31 Best or worst advice

Over 60 million Americans live with a mental health condition, and about six in ten can’t get consistent access to care. Visar Tasimi’s team gets someone into behavioral health care in an average of four days. He’ll tell you supply is only part of the problem. The bigger part is data.

Visar is Senior Vice President of Provider Success and Market Operations at Lucet, where he oversees a network of roughly 60,000 behavioral health providers. Behavioral health breaks the usual assumptions: it is not uncommon for one provider to work for three or four different companies, which multiplies the same record three or four times over and makes all of it harder to keep accurate. In this conversation with Nick Helfrich and Mitch Gorodokin, Visar walks through NavConnect, the work of finding out when a provider is actually free, and the single fix he’d want the whole industry to adopt.

In this episode:

• Why one behavioral health provider working for four companies quadruples the data problem
• What a ghost network actually is, and why it’s almost never malicious
• The four-day speed-to-care number, and what it takes to hit it
• The number one filter members search on when choosing a therapist
• Therapeutic alliance: getting someone into care versus keeping them there
• Why telehealth solved geography and not matching
• Shared credentialing, and the single source of truth he’d build with a magic wand
• The advice his grandmother still calls to check he’s following

Subscribe to Provider Data Dorks for the people fixing healthcare’s hardest data problem. New episodes weekly on YouTube, Spotify, and Apple Podcasts.

Timestamps:

00:00 Intro

03:58 The through line from finance to dental to behavioral health

07:16 What makes finding a behavioral health provider so hard

09:20 Telehealth solved geography, not matching

10:27 One provider, four companies, four times the data

13:54 NavConnect, and finding out when someone is actually free

15:24 The four-day speed-to-care number

17:18 Why licensing letters change from state to state

21:10 The magic bullet he doesn’t have yet

23:55 Therapeutic alliance, and the filter members search first

25:01 Where cash pay fits in

27:57 What a ghost network actually is

32:53 Who is really responsible for accurate data

38:53 Behavioral health and chronic disease

42:17 Closing the loop back to the PCP

45:15 Shared credentialing and a single source of truth

49:06 Nobody went to school to maintain 20 directories

52:30 His honest advice for health plans

1:02:11 Lightning round

1:03:24 His grandmother’s advice

Starting in 2028, every health plan will have to confirm that every doctor in its directory is actually there, every ninety days. Nick Bernold thinks the goal is right and the mechanics are close to impossible. Ten to fifteen payers calling the same practice, reading sixty names down the phone to an office that's booked from opening to closing. His words for what happens next: the practices hang up. He's already testing the workaround, and the week before this recording one of his AI voice agents called a doctor's office and got an AI receptionist.

Nick is chief product officer at J2 Health, where he was the first hire in January 2022 and has built the company's provider network analytics and led product ever since. He came to J2 after three years designing network analytics and strategy products at Oscar Health, and started his career in finance at Bridgewater Associates. He holds a B.A. from Dartmouth and finished law school at Yale, where he was headed for tax law before healthcare pulled him back.

In this episode:

• Why network adequacy turned out to be an ops problem before it was a data problem, and what he got wrong walking in with a "data brain"

• The gray areas: PDFs from the early 2000s that practitioners will tell you are not remotely how the rules actually work

• Why 20 to 40% of doctors listed as in-network have no appointment available inside a two to three month window

• The counterintuitive trade-off where tighter time and distance standards hand more leverage, and higher premiums, to consolidated provider groups

• What the Real Health Providers Act gets right, and the 90-day verification requirement he doesn't think anyone can operationalize

• Secret shopper calls run by AI voice agents, including the one that reached an AI receptionist on the other end

• The two directory use cases regulators keep collapsing into one: the existing patient checking coverage and the new patient trying to get in the door

• The 1997 cap on CMS-funded residency slots he believes sits upstream of the entire access problem

• His one recommendation for network leaders before 2028: consolidate to a single internal source of truth

Subscribe to Provider Data Dorks for the people fixing healthcare's hardest data problem. New episodes weekly on YouTube, Spotify, and Apple Podcasts.

Eric Galvin has run health plans as both CFO and CEO. At one of them, the directory data was bad enough that regulators raised concerns about whether consumers could actually find care. He says so plainly here, then describes what he found when he went looking: a scary place, with all kinds of scary reasons the data is the way it is, most of them things the industry did to itself.

Eric spent nine years at ConnectiCare as CFO and then CEO, served as EVP and chief growth and medical cost officer at EmblemHealth, ran PopHealthCare and Emcara Health as CEO, and was most recently CFO of Geisinger Health Plan. Across thirty years on both the payer and the provider side, his conclusion is that the provider data problem survives for human reasons more than technical ones. It comes down to trust, and to the fact that the people senior enough to fix it are often the least free to describe it out loud. In this conversation with Nick Helfrich and Mitch Gorodokin, his prescription for the whole system comes down to one word: simplify.

In this episode:

Why well-intentioned incentive design, from stars ratings to quality metrics, can degrade the patient experience it was built to improve

Why stripping out administrative waste still would not make healthcare affordable

The "bill without a price" problem: healthcare's strangest economic quirk

"Manage yourself out of a job": his advice to provider data directors seeking executive buy-in

Why he thinks a clearinghouse model, similar to credit reporting, could fix provider data industry-wide

What racing sports cars and his eye doctor reveal about the consumer data layer healthcare is missing

The colleague with a cancer diagnosis who could barely navigate the system she had worked in her entire career

Subscribe to Provider Data Dorks for the people fixing healthcare's hardest data problem. New episodes weekly on YouTube, Spotify, and Apple Podcasts.

Every health-tech company promises AI will make you healthier. Dr. Ankoor Shah says that's not what the technology is actually being built to do. A pediatrician who co-led Washington DC's COVID-19 response and now serves as VP of Clinical Excellence at Included Health, Shah delivers two on-record hot takes: that healthcare technology has historically widened disparities rather than closed them, and that today's AI is funded to optimize the revenue cycle, not patient outcomes.

From there, Nick and Mitchell get into the part that actually decides your care: how you find a doctor who's safe, and why the system makes that so hard. Shah explains why the biggest quality gains come from moving people out of the bottom quartile, how doctors with sanctions slip across state lines undetected, and why he himself has no real incentive to keep his data accurate across a dozen health plans.

It's a clear-eyed look at where provider data, quality, and AI actually intersect, from someone who has practiced, run public health, and now builds.

In this episode:

Why Shah says healthcare AI isn't built to make patients healthier

The "history of technology widening disparities" argument, from telehealth to wearables

How Included Health quantifies provider quality at the individual NPI level

Why moving patients out of the bottom quartile beats chasing top-tier docs

How sanctioned providers stay in-network across states

The credentialing burden that leaves directory data permanently stale

Why aligning the member's "mind, body, and wallet" is the real unlock

Subscribe to Provider Data Dorks on YouTube, Spotify, and Apple Podcasts.

Most health plans manage the invisible backbone of healthcare, provider data, across disconnected systems, spreadsheets, and vendors that don't talk to each other. One bad record cascades downstream into claims, payments, and patients who can't find a doctor. So why do so many plans still try to build their own fix?

Sam Deshpande spent 17 years at Capital One in risk and credit, then ran risk, technology, and information at Humana as chief risk officer and later CIO. That makes him the rare leader who has sat on both sides of every buy-vs-build, business-vs-IT fight. In this episode he gives Nick and Mitch a clear rule for what to build, what to buy, and why provider data is the textbook case for buying: complicated, universal, and ruinous to get wrong.

Highlights:

Why he calls the business-IT divide "two separate nations," and how good leaders close the border

The three questions he asks about any product before the demo matters

His rule of thumb: if it's complicated and everyone uses it, buy it

Why "transformational" is overused, and the only two things that earn the word

How he'd fix provider data from a clean slate as a health plan CEO: decide, declare, design

Where AI genuinely moves provider data, and where teams are kidding themselves

The $60 shovel story that reframed how he buys AI tools

New episodes of Provider Data Dorks every week. Subscribe on YouTube, Spotify, and Apple. Hosted by Nick Helfrich and Mitch Gorodokin.

Finding an in-network doctor shouldn't take twenty phone calls. But provider directories (the invisible backbone of healthcare) are wrong so often that the best payers in the country top out at 70% accuracy, and the worst sit at 30%.

Most people assume that gap is a mystery. Ron Urwongse proved it's measurable.

Ron is the co-founder of Defacto Health and former innovation and strategy lead at CAQH. When CMS mandated that insurers publish their provider directory data through public APIs, he did something almost nobody else did: he read them. All 150 of them. By aggregating those feeds and scoring where payers agree and disagree, Defacto turned one of healthcare's messiest problems into something you can actually put a number on.

In this conversation with hosts Nick Helfrich and Mitch Gorodokin, Ron breaks down why cleaning data upstream beats patching it downstream, why "single source of truth" might not save us, and the surprisingly human reasons good directories go bad.

Why payer directory accuracy ranges from 30% to 70% and what separates the two

How consensus scoring across 150 payers reveals which addresses are actually right

The dropdown-menu mistake quietly generating thousands of directory errors

Why health systems often hold better data than the payers publishing it

What the No Surprises Act, MA Plan Finder, and Real Health Providers Act mean for you

How Defacto audits insurers using nothing but the data those insurers publish

Ron's rule for building anything that lasts: fall in love with the problem

Subscribe to Provider Data Dorks for the people fixing healthcare's hardest data problem. New episodes weekly on YouTube, Spotify, and Apple Podcasts.