The Execution Gap

Peter Saah, Podero Health

Healthcare quality gap closure doesn’t fail because plans lack data—it fails because execution breaks down after gaps are identified. The Execution Gap is an operator-led podcast focused on HEDIS, Medicare Stars, and healthcare quality operations. Hosted by Peter Saah, a healthcare quality leader with experience across UnitedHealthcare, Optum, Centene, and Molina, this podcast breaks down where gap closure actually fails in real-world environments. Each episode explores the operational challenges behind chart retrieval, clinical abstraction, member outreach, and workflow coordination—and wha

  1. -2 J

    Season 1 Ep6 | You Don't Have a Retrieval Problem. You Have an Abstraction Problem

    The care happened. The physician documented it. The chart was retrieved. The evidence existed. And the measure still stayed open. That is not a retrieval failure. That is an abstraction failure. And it is one of the least measured — but most financially consequential — problems in payer quality operations today. In Episode 6 of The Execution Podcast, Peter Saah breaks down exactly where abstraction fails, why your vendor's sub-one-percent error rate doesn't tell you what you think it does, why AI-assisted abstraction shifts the judgment layer without eliminating it, and what the plans managing abstraction well actually do differently. This episode is for health plan quality directors, VPs of operations, and HEDIS program leads who want to understand why Stars performance keeps coming in below forecast — and why the answer may not be in their retrieval rate at all. --- WHAT YOU'LL LEARN IN THIS EPISODE: → Why most Stars misses are not missing care — they are wrong interpretation of care that was already documented and retrieved → Why vendor-reported sub-1% error rates measure internal consistency — not whether the shared interpretation logic is correct against the measure specification → Why AI-assisted abstraction (NLP, evidence extraction) shifts the judgment layer without eliminating it — and the three failure modes that remain in the human decision layer on top of AI output → The seven ways abstraction fails in real HEDIS production environments — from clinical misinterpretation and specification misapplication to the silent failure that leaves no trace in the system → Why COL-E has five different lookback windows by procedure type — and why misclassifying CT colonography and optical colonoscopy is a material error, not a cosmetic one → The three root causes behind all seven failure modes: interpretation variance, specification complexity, and unmeasured human adjudication accuracy → The financial calculation that connects abstraction error rates to Stars measure weighting — and why the same error rate on a high-weight measure costs materially more than on a lower-weight one → Why Q4 abstraction accuracy is systematically lower than Q2 — and why most plans don't staff for it → Four specific operational practices that separate plans managing abstraction from plans assuming it works ABOUT THE EXECUTION PODCAST: The Execution Podcast is hosted by Peter Saah, DBA, MBA, CPHQ — CEO and Co-Founder of Podero Health. Each episode covers the operational realities of HEDIS performance, Stars strategy, and quality data execution for health plan leaders. No fluff. No vendor pitch. Just what's actually happening in quality operations — and what to do about it. New episodes drop regularly on Spotify and YouTube. --- PODERO HEALTH: Podero Health helps health plans validate and close care gaps at the data layer — ensuring that chart retrieval, EMR feeds, lab feeds, and CCD data actually satisfy HEDIS measure specifications, not just land in a system. Request a demo or pilot: https://poderohealth.com/Contact Connect with Peter Saah on LinkedIn: https://www.linkedin.com/in/dr-peter-saah-dba-cphq-0b50a572/ Website: poderohealth.com --- © Podero Health. All rights reserved.

    19 min

  2. 14 MAI

    Season 1 Ep5 | When Manual and Digital Collide: The Reconciliation Problem Nobody Budgets For

    Most health plans are running two data programs simultaneously right now — chart retrieval for hybrid measures still in traditional reporting, and ECDS digital feeds for measures like COL-E, CCS-E, CIS-E, and IMA-E that have already transitioned. Two vendor relationships. Two sets of timelines. One member population sitting in the middle. Nobody's budgeted for what happens when they disagree. In Episode 5, Peter Saah breaks down the reconciliation problem — the governance gap that lives between your vendor programs, shows up in nobody's SOW, and quietly leaks Stars performance in a way that no vendor report will ever surface for you.  In this episode: → Why reconciliation is a governance problem, not a technology fix — and what that distinction means for how you solve it → The unresolved member: a specific population every plan has and almost none have a protocol for → Why your Stars forecast for MY2026 may be built on historical data that was never accurate — and why that error runs in two directions simultaneously → The retrospective attribution analysis that tells you how reliable your closure rates actually are → What the ECDS transition to MY2029 means for reconciliation complexity over the next three measurement years → Three things that actually fix the problem — structurally, not just operationally   If you're running both chart retrieval and digital feeds and you've never formally answered the question "what happens when they conflict on the same member" — this episode is for you.   Built for health plan quality directors, VPs of operations, and HEDIS program leads. Note: Now — some of you are thinking: isn’t this what my HEDIS analytics engineer handles? Or isn’t this what my HEDIS engine is supposed to catch? Fair question. And the honest answer is: partly. Your HEDIS engine — is exceptionally good at one thing: applying NCQA measure logic to data that has already been ingested and normalized. It will tell you whether the data in the system satisfies the measure. What it cannot tell you is which data to trust when your chart retrieval program and your digital feed disagree about whether an encounter happened — before that data enters the engine. That decision happens in abstraction, governed by whatever source hierarchy protocol you have documented. The engine executes the logic. It doesn’t make the call. And your analytics engineer validates the output of the engine — they don’t sit upstream resolving source conflicts in real time for individual members during production. That’s the gap. That’s what nobody has formally built a workflow for. ---   Learn more about Podero Health: https://poderohealth.com/Contact Request a demo or pilot: poderohealth.com/demo Connect with Peter Saah: https://www.linkedin.com/in/dr-peter-saah-dba-cphq-0b50a572/   ---   EPISODE TAGS HEDIS, Stars Ratings, Medicare Advantage, Health Plan, Care Gaps, Quality Improvement, ECDS, Data Collection, Abstraction, Managed Care, Health Tech ---  ©2026 Podero Health. All rights reserved.

    29 min

  3. 8 MAI

    Season 1 Ep4 | The Data Feed Delusion: Why Digital Collection Fails Silently Where Chart Retrieval Fails Loudly

    Following on Episode 3's look at late-year chart retrieval, this episode challenges the assumption that digital data collection solves the underlying problem. [Name] breaks down the three failure modes that make digital feeds dangerous precisely because they're invisible: the completeness illusion, sequencing latency, and source conflicts that documented protocols often can't actually resolve under audit scrutiny. Includes a direct look at where NCQA's Data Aggregator Validation program ends — and where your abstraction logic has to begin. Topics covered: Why digital data collection fails silently where chart retrieval fails loudlyWhere NCQA's Data Aggregator Validation (DAV) program ends and measure-level completeness beginsThe completeness illusion: how a DAV-validated CCD can still be measure-incompleteFeed sequencing latency and its real impact on outreach accuracySource conflicts: why documented protocols often don't survive auditor scrutinyWhat measure-level validation actually means versus format-level validationWhy members who need both digital and manual retrieval are the ones most plans miss systematically Request a demo or pilot: https://poderohealth.com/Contact?intent=pilot Connect: https://www.linkedin.com/in/dr-peter-saah-dba-cphq-0b50a572/ ________________________________________________________ © 2026 Podero Health. All rights reserved.

    27 min

  4. 24 AVR.

    Season 1 Ep3 | Your Retrieval Report Is Lying to You

    A retrieved chart isn't a closed gap. It's raw material. And raw material that arrives too late doesn't become finished product — it becomes write-off. Peter walks through exactly how late-year retrieval silently degrades abstraction quality, burns outreach budget on already-closed gaps, and creates submission risk that doesn't show up until it's too late to fix. Plus the Biased Rate designation — what it is, what it costs, and why it's hiding in plain sight in the Star Ratings Technical Notes. Bring your Q4 retrieval data to Podero Health and we'll show you your yield number — probably for the first time. Demo, pilot, or yield rate analysis: https://poderohealth.com/Contact?intent=pilot

    19 min
  5. Season 1. Ep2 | Why Provider Outreach Fails to Close Gaps - Even when You Do It Right

    21 AVR.

    Season 1. Ep2 | Why Provider Outreach Fails to Close Gaps - Even when You Do It Right

    Provider outreach isn’t failing—it’s being used at the wrong point in the process. In this episode, we break down why outreach volume stays high while gap closure remains low. The issue isn’t effort. It’s premature outreach execution—requests triggered before gaps are validated and without control over what happens next. We cover: Why outreach activity ≠ gap closureHow unvalidated gaps create duplicate and unnecessary requestsWhat happens when outreach operates without visibility into retrieval and abstractionWhy providers aren’t the primary constraintYou’ll also learn what controlled execution looks like—where outreach declines as closure increases—versus uncontrolled environments where outreach stays high and outcomes stall. Visit Podero Health to see the graphical breakdown of controlled vs uncontrolled upstream execution - https://poderohealth.com/insights/why-provider-outreach-does-not-close-gaps Outreach doesn’t drive closure. Execution control does.

    18 min
  6. Season 1. Ep 1 | Why Healthcare Quality Gap Closure Fails on Execution — Not Insight

    20 AVR.

    Season 1. Ep 1 | Why Healthcare Quality Gap Closure Fails on Execution — Not Insight

    Healthcare quality gap closure doesn’t fail because plans lack data—it fails because execution breaks down after gaps are identified. In this episode, we unpack where things actually go wrong across retrieval, abstraction, and outreach, and why fragmented workflows prevent real closure at scale. Want to talk to our team at Podero, visit: www.poderohealth.com

    16 min
  7. Season 0: Medicare Stars Foundations - CAHPS & STARS Strategy: Driving Excellence in Health Plans

    27/05/2023

    Season 0: Medicare Stars Foundations - CAHPS & STARS Strategy: Driving Excellence in Health Plans

    Season 0: Medicare Stars Foundations This episode is part of the original Medicare Stars Podcast archive.The show has since evolved into The Execution Gap, focused on healthcare quality execution and gap closure at scale. _________________________________________________________ In this episode, we shine a spotlight on two essential components of healthcare quality measurement and improvement: the Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey and the Centers for Medicare and Medicaid Services (CMS) Star Ratings. Join us as we uncover the intricacies of these programs and their role in driving excellence in health plans. The CAHPS survey serves as a vital tool for capturing patient experiences and perceptions of care across multiple dimensions. CMS Star Ratings, on the other hand, provide a comprehensive assessment of health plan performance, guiding consumers in making informed decisions. Together, these initiatives play a significant role in quality improvement, accountability, and enhancing member satisfaction. In this episode, Jessica Asefa, a healthcare leader, provides effective strategies for maximizing performance in CAHPS and CMS Star Ratings. Throughout the episode, we discuss practical strategies for health plans to optimize their performance in CAHPS and CMS Star Ratings. From enhancing patient engagement and communication to implementing evidence-based interventions and care coordination initiatives, our guest shares valuable insights on how to drive continuous improvement and achieve high ratings. Whether you are a healthcare executive, a quality professional, or a provider directly involved in patient care, this episode is a must-listen for anyone seeking to elevate their health plan's performance and deliver exceptional care experiences.

    30 min
  8. Season 0: Medicare Stars Foundations - Healthcare Without Walls: Harnessing the Power of Data to Address Health Equity

    27/05/2023

    Season 0: Medicare Stars Foundations - Healthcare Without Walls: Harnessing the Power of Data to Address Health Equity

    Season 0: Medicare Stars Foundations This episode is part of the original Medicare Stars Podcast archive.The show has since evolved into The Execution Gap, focused on healthcare quality execution and gap closure at scale. _________________________________________________________ In this episode, we delve into the profound significance of data in addressing health equity, and how it can be a catalyst for transformative change. Health equity remains a critical challenge in our society, with disparities in access to healthcare and health outcomes persisting across diverse populations. The key to tackling these disparities lies in understanding the root causes and implementing targeted interventions. Join us as we explore the role of data in this process and uncover its power to drive meaningful progress in achieving health equity. Our esteemed Carissa Stajnrah, share her perspectives on the importance of data in addressing health disparities. We dive into the nuances of collecting, analyzing, and interpreting data to identify and address inequities at individual, community, and systemic levels. Throughout the episode, we explore the ways in which data can reveal patterns and insights, uncovering disparities related to race, ethnicity, socioeconomic status, geography, and other determinants of health. Carissa also highlight the significance of community engagement and partnership in leveraging data for health equity.

    22 min
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À propos

Healthcare quality gap closure doesn’t fail because plans lack data—it fails because execution breaks down after gaps are identified. The Execution Gap is an operator-led podcast focused on HEDIS, Medicare Stars, and healthcare quality operations. Hosted by Peter Saah, a healthcare quality leader with experience across UnitedHealthcare, Optum, Centene, and Molina, this podcast breaks down where gap closure actually fails in real-world environments. Each episode explores the operational challenges behind chart retrieval, clinical abstraction, member outreach, and workflow coordination—and wha

Informations

  • Création
    Peter Saah, Podero Health
  • Années d’activité
    2023 - 2026
  • Épisodes
    18
  • Classification
    Tous publics
  • Copyright
    © Peter Saah, Podero Health
  • Site web de l’émission
    The Execution Gap

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