Provider Directory: I will destroy your roadmap with Misha Nasrollahzadeh + Grant Veldhuis

Grant Veldhuis (software engineer at Thatch, former Ribbon Health) and Misha Nasrollahzadeh (co-founder and CEO of Joyce Health, formerly Castlight Health and Ribbon Health) have both spent significant stretches of their careers trying to solve this. They walk through what they've learned, where they've hit walls, and what they'd do differently. What we cover - A working definition of Provider Directory: provider identity, location, specialty, phone number, and network status. Everything else: subspecialty inference, cost data, scheduling, is a layer on top. Don’t get it twisted - Then you layer things on top of that working definition: NPPES (National Plan and Provider Enumeration System) gives you specialty. Claims data lets you infer subspecialty. CPT codes have to be translated into human language before care navigation is actually possible. Scheduling (Zocdoc's territory) is hideously complex and you don’t want that smoke - Ways to constrain the problem (and *maybe* justify building in-house): Castlight maintained separate employer-by-employer directories built from claims data. Grant built a localized directory for the University of Michigan's 60,000-person campus. Both found success through scope restriction. Nationwide coverage is usually the enemy of accuracy. - Be suspicious: Someone is going to tell you their data is 99% accurate. Maybe a vendor. Maybe an internal team lead. You need to dig into what that number actually means. One payer's head of provider directory once defended that figure but his definition was *whether or not the fields were populated*. Not whether the phone number actually worked or whether the address was still a functioning practice (The address turned out to be a car wash) - Sharing is NOT caring: why CAQH (Council for Affordable Quality Healthcare) exists but payers don't have a great incentive to improve the underlying data, even when it benefits everyone. - Oblique, non-obvious signals for keeping data fresh: referral coordinators at a value-based primary care group were the best signal Ribbon ever found, because they were calling offices every day and had direct incentive to log corrections. Published research papers are another: "they just published with this institution, so they must still be affiliated." - Network effects and why they're hard: small care navigation companies can be required to contribute edits in exchange for data access. National payers paying orders of magnitude more cannot be asked the same thing. - Build vs. buy, the age-old question: default to buying unless your use case is genuinely outside what vendors have mapped. ACA (Affordable Care Act) individual market plans are one example where standard data quality may not hold. University of Michigan campus resources are another. Brought to you by Basata AI - Basata builds AI agents for specialty practices. They answer phones 24/7, schedule appointments, process referrals and faxes, and take repetitive work off healthcare teams so they can focus on patients. For inquiries about sponsoring the podcast, email [email protected]