The Execution Gap
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.
24 episodios
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