Everyone Agrees Value-Based Care Is the Destination. Almost No One Agrees on How to Get the Data Ready.
Value-based care has been the stated direction of healthcare reimbursement for over a decade, across both the U.S. and Latin America. Health systems, insurers, and regulators all describe the same intention: pay for outcomes, not volume. Align incentives around quality and cost, not the number of services delivered. And yet, for most organizations, the shift remains more aspirational than operational — not because anyone disagrees with the goal, but because the underlying data infrastructure most institutions run on was never built to support it.
That’s the real story behind the slow pace of value-based care adoption. It isn’t a strategy problem. It’s a plumbing problem.
Why Fee-for-Service Infrastructure Can’t Just Be Repurposed
Most hospital and insurer data systems were designed to answer a fee-for-service question: what services were delivered, and what do they cost? Value-based payment asks a fundamentally different question: what outcome was achieved, relative to what a comparable patient’s outcome should have cost and looked like? Answering that second question requires infrastructure the first question never needed.
A few structural gaps show up consistently in organizations trying to make this transition:
Disconnected systems and databases. Clinical data, administrative data, and financial data typically live in separate systems that weren’t built to be queried together. Under fee-for-service, that’s inconvenient. Under value-based payment, it’s disqualifying — you can’t align cost with outcome if the systems that hold cost and the systems that hold outcome don’t talk to each other.
No unified, standardized view of a patient population. Value-based contracts are built around defined populations and comparable case cohorts. Without a standardized way to group patients into genuinely comparable categories, “outcome relative to expectation” has no consistent baseline to be measured against.
Manual, slow decision-making processes. Fee-for-service operations can tolerate retrospective reporting because the payment doesn’t depend on the outcome. Value-based arrangements can’t — they require the ability to see how a population is trending against cost and quality targets while there’s still time to intervene, not months after a contract period closes.
Difficulty aligning cost with quality of care. Perhaps the most fundamental gap: most institutions can report cost, and most can report quality metrics, but relatively few can connect the two at the level of granularity a value-based contract actually requires — by case type, by cohort, by provider. Hosdatia was built specifically to close this gap for hospitals and clinics, connecting operational and financial data into one case-mix-based view.
What Readiness Actually Looks Like
Organizations that have successfully made this transition tend to share a common pattern, regardless of whether they’re a hospital network or a payer: they didn’t wait for a perfect, purpose-built system. They built a standardized layer on top of the clinical, administrative, and financial data they already had, using case-mix classification as the connective tissue between cost and outcome.
That approach reshapes the transition around three shifts:
- From institution-centered to population-centered. Rather than managing performance one department or one encounter at a time, value-based readiness means being able to see and manage outcomes across a defined population — the actual unit that value-based contracts are built around. This is the same shift documented in Avedian’s Apross case study, where a health system moved from institution-centered to population-centered care using DRG-based intelligence.
- From reactive spending to proactive management. Instead of discovering cost and quality performance after a contract period ends, readiness means having visibility into how a population is trending in time to act — identifying and addressing drivers of cost or quality risk before they show up in a settlement. On the payer side, Insuria applies this same proactive model to risk and cost management across a member population.
- From fragmented data to integrated intelligence. The technical core of this shift is connecting clinical, administrative, and financial data into a single, standardized view — not replacing the underlying systems, but layering a common analytical structure across them so cost and outcome can finally be compared on the same terms.
Why Case-Mix Standardization Is the Foundation, Not a Feature
It’s worth being specific about why case-mix classification, rather than a generic analytics dashboard, is the piece that makes this work. Value-based contracts are only meaningful if “expected outcome” and “expected cost” mean something specific and comparable across cases. A generic dashboard can show trends. A standardized case-mix framework can define what a given patient population should reasonably cost and achieve — which is the actual reference point a value-based contract is measured against. This is the foundation of Avedian’s proprietary DRG engine, which standardizes inpatient care, outpatient care, and population health on one common, objective language.
Without that standardization, organizations attempting value-based arrangements are negotiating and managing contracts against a moving, subjective baseline. With it, cost, risk, and complexity become objective, comparable inputs that both a hospital and an insurer can agree on, which is what makes a value-based contract enforceable and sustainable in the first place, rather than a source of ongoing dispute.
A Shared Challenge Across the U.S. and LATAM
The specifics of payment reform differ significantly between the U.S. and Latin American healthcare markets — different regulatory environments, different payer structures, different timelines for adoption. But the underlying data challenge is strikingly similar in both regions: institutions have the raw data needed to support value-based arrangements, but not the standardized structure to make that data usable for outcome-based contracting. That convergence is part of why lessons from value-based care implementations in one region are increasingly relevant to health systems and insurers in the other. Compass Decision Support’s qualification on Mayo Clinic Platform is one example of this convergence — a solution proven across Latin American hospital networks now entering the U.S. market.
What Hospital and Insurer Leaders Should Be Evaluating Now
For health system and insurer executives assessing their readiness for outcome-based payment models, the diagnostic question isn’t “do we support value-based care as a strategy.” Almost everyone does. It’s narrower and more concrete: can our organization currently produce a standardized, case-mix-adjusted view of cost and outcome for a defined patient population, in time to manage performance rather than just report on it afterward?
For most organizations today, the honest answer is not yet and that gap, more than any policy or contracting hurdle, is what’s determining which institutions are actually ready to operate under value-based payment models and which are still preparing to fully take part.
