๐๐๐ง๐ฉ 1 โ ๐๐๐ ๐ฝ๐ง๐ค๐ ๐๐ฃ ๐๐๐ค๐ฃ๐ค๐ข๐๐๐จ ๐ค๐ ๐๐ค๐ฅ๐ช๐ก๐๐ฉ๐๐ค๐ฃ ๐๐๐๐ก๐ฉ๐ (๐๐ฃ๐ ๐๐๐ฎ ๐พ๐๐๐จ๐๐ฃ๐ ๐ฟ๐๐ข๐๐ฃ๐ ๐๐๐จ ๐๐๐ ๐ฉ๐ค ๐๐๐ง๐๐๐ฃ ๐๐ง๐ค๐จ๐๐ค๐ฃ)
For more than a decade, population health management has been the rallying cry of U.S. healthcare. Health plans, providers, and consultants promised that better care coordination, care gap closure, and value-based care programs would finally bend the cost curve. Billions of dollars were poured into care management platforms, member engagement apps, and utilization management programs.
And yet, the numbers tell a different story:
โข Administrative costs for commercial health plans remain in the 12โ15% range, while traditional Medicare runs at ~2%.
โข Medical Loss Ratios (MLR) in Medicare Advantage and Medicaid managed care continue to fluctuate under pressure, forcing payers to chase Stars Ratings, Quality Bonus Payments (QBP), and risk adjustment revenue just to maintain margins.
The uncomfortable truth: what weโve called โpopulation health economicsโ has really been demand-side economics in disguise.
๐๐๐ฎ ๐ฟ๐๐ข๐๐ฃ๐โ๐๐๐๐ ๐๐๐๐ฃ๐ ๐๐ฃ๐ ๐๐๐๐ก๐จ
Demand-side economics in healthcare looks like this:
โข Waiting for claims data (180-day lag) to identify risk.
โข Suppressing demand with narrow networks and high deductibles.
โข Rationing utilization through prior authorization and denials.
โข Obsessing over gap closure as the pathway to quality scores.
This creates an illusion of control but it doesnโt scale. Instead, it produces margin erosion:
โข Every care gap closed reopens again next year.
โข Utilization suppression backfires as members delay care and return sicker, costlier, and angrier.
โข Care management programs collapse under workforce strain, with case managers overloaded and burnout rising.
โข Tech point-solutions fail to bend MLR because they werenโt designed for systemic economics.
The result? Payers are stuck on a treadmill. Margins erode, member experience suffers, and executives keep paying consultants for strategies that only rearrange demand-side data.
๐ ๐ฃ๐ผ๐น๐ฎ๐ฟ๐ถ๐๐ถ๐ป๐ด ๐๐๐ ๐ก๐ฒ๐ฐ๐ฒ๐๐๐ฎ๐ฟ๐ ๐ฃ๐ผ๐ถ๐ป๐
Hereโs where this gets uncomfortable for many in the industry:
If youโve been relying on claims-driven insights, retrospective care gap closure, or point-solution โengagement tools,โ you havenโt been doing population health economics. ๐ฬฒ๐ฬฒ๐ฬฒโฬฒ๐ฬฒ๐ฬฒโฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒโฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒโฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒโฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒโฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ๐ฬฒ.ฬฒ
That accounting has delivered no lasting margin stability, no reduction in avoidable utilization, and no real progress toward equity.
Medicare Advantage margins are under pressure not because CMS made the Stars cut harder, but because Stars themselves were never the real lever of population health economics.
Plans spent a decade engineering โgap-chasingโ and quality performance infrastructure, only to discover that when CMS adjusted the scoring curve, the entire house of cards collapsed. Billions in admin and vendor spend, yet no durable economics.
This is the core failure of demand-side thinking: building systems to optimize scores instead of creating new inputs. When the scoring rubric shifts, demand-side economics implodes. Supply-side economics doesnโt depend on CMS formulas it generates continuous, member-driven risk data that stabilizes MLR whether Stars are up, down, or rewritten.
Health plans were never built as supply-side engines.
โข They donโt deliver care โ they administer access.
โข They donโt generate new inputs โ they ration existing ones.
โข They donโt create visibility โ they price networks and report lagging claims.
Thatโs why supply-side economics has escaped them. It never fit their operating model. Instead, they built a decade of infrastructure around demand-side levers: utilization controls, Stars gap-chasing, risk adjustment coding.
And when CMS shifted the Star Ratings curve, the whole faรงade cracked. Billions in administrative spend collapsed into a hamster wheel that never produced durable economics.
But hereโs the real pivot: supply-side economics doesnโt ignore CMS rubrics. It renders them irrelevant as constraints because when you generate a continuous supply of member-driven risk data, you always have the inputs to dominate any scoring system Washington creates, today or tomorrow.
Thatโs the difference: demand-side plans try to โgameโ CMS rules. Supply-side plans set themselves up to win no matter how the rules change.
Demand-side tools donโt solve the problem they only document it.
๐ง๐ต๐ฒ ๐ฆ๐ต๐ถ๐ณ๐ ๐๐ต๐ฒ๐ฎ๐ฑ
If the last decade of โpopulation health managementโ has proven anything, itโs this:
โข You canโt close your way to profitability.
โข You canโt suppress your way to sustainability.
โข And you canโt consult your way into new data supply.
The broken economics of population health is the failure to recognize that no amount of demand-side tinkering can stabilize payer margins. Whatโs needed is a supply-side engine a scalable, continuous stream of real-time risk data that creates new inputs into the system.
Part 1 of 10.
