The Totally Adequate Podcast

Quest Analytics

Initiating conversations on the latest trends, network adequacy and provider data accuracy policy updates, and healthcare provider network management innovations.

  1. 4d ago

    AI Is a How, Not a Why, Rethinking Product Strategy for Health Plans

    About this episode: AI is a tool for reaching a goal, and health plan leaders get the most from it by starting with the problem they need to solve. Chris Lance, Chief Product Officer at Quest Analytics®, and Adam Sullivan, an independent consultant who previously led data science work at Change Healthcare and Labcorp, explain how to tell when AI is the right tool for health plan provider network management.  The conversation gives you a way to sort those goals by what AI actually changes for the business and to spot where it does not belong.  What You'll Learn  A practical way to tell whether AI is the right tool for a given problem  Where AI has opened up work that used to be out of reach for health plan network teams, and where it creates new problems to manage  Why the data underneath an AI feature matters more than the model, and what that means for build versus buy  How to measure whether an AI feature is working six months after launch  When Health Plans Should Use AI  Start with what matters to the business and what it is struggling with, then apply AI to that problem. Chris describes three roles AI can play, which are creating new problems to solve, solving problems that were out of reach, and improving jobs already being done. A rules-based method that returns the exact answer is the better fit for decisions such as care coverage and reimbursement.  Why Data Matters More Than the AI Model  Flawed data produces wrong predictions and decisions that are not good for members. For example, ghost networks show the risk. A network can look adequate on paper while the providers listed in it are not available to members.  Build Versus Buy for Health Plan AI  Chris says the owner of the outcome should decide whether to pursue the work at all, and a viable product that already exists is better bought than rebuilt. Adam adds that being able to build something does not mean a team should. He suggests the strongest AI talent belongs on high-value problems rather than on replacing a software subscription.  How to Measure Whether an AI Feature Is Working  Set a goal and capture a baseline before launch, then measure progress against both. Adam recommends building monitoring in on day one and tracking the value created alongside token spend.  Related Resources  Listen to the previous episode in this series on the data science perspective. Read more on the Quest Analytics blog about ghost networks and the Meet Quinn™ AI assistant.  Guests: Chris Lance, Chief Product Officer, Quest Analytics  Adam Sullivan, Independent Consultant  Moderated by Lucas Voss, Becker's Healthcare  Host: April Beane, VP of Marketing, Quest Analytics®

  2. Aug 19

    Inside the Lab: Data Science at Quest Analytics

    Everyone talks about the importance of clean, accurate provider data, but who's actually doing the work to make that real? In this episode of The Totally Adequate Podcast, host April Beane brings two members of Quest Analytics' data science team out of the lab and onto the mic.  Subhash Seelam and Nebojsa Milosavljevic don't usually show up in marketing materials. They show up in datasets,  identifying anomalies, building models, tracing relationships between providers, facilities, physician groups, and health systems that most people assume are already properly connected. (Spoiler: they're not.)  In this episode, you'll hear about:  What data scientists actually do, and why the role at Quest Analytics is unique  Why the provider data problem is fundamentally a hierarchical one, and what that means for health plans  How experimentation, failure, and unexpected discoveries lead to better models  The principle behind the work: when the foundation isn't solid, everything built on top of it costs more  What the future of provider data looks like, and why the industry is finally starting to converge on the right answer    This episode is a conversation with the people doing work that most health plan professionals never see. Work that determines whether a member can actually find an in-network doctor, whether a compliance calculation is based on accurate data, and whether everything downstream is built on something solid.  "When the foundation isn't solid, everything built on top costs more." — Subhash Seelam    Guests:  Subhash Seelam, Chief Data Officer, Quest Analytics®  Nebojsa Milosavljevic, Data Science Team Lead, Quest Analytics  Host: April Beane, VP Marketing, Quest Analytics

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Initiating conversations on the latest trends, network adequacy and provider data accuracy policy updates, and healthcare provider network management innovations.