Value-based contracts (VBCs) for specialty therapies and gene-based interventions are no longer pilot projects—they are becoming the default negotiating framework for forward-looking payers and manufacturers. Yet many registry designs still chase traditional clinical endpoints while payers care about something else entirely: whether the therapy reduces total cost of care, improves patient-reported quality of life, and delivers predictable long-term value. The central challenge is how to align registry endpoints with payer outcomes for risk-sharing deals—and doing it well requires a shift from static data collection to dynamic, fit-for-purpose real-world evidence (RWE) infrastructure. Below are the field-tested strategies that will define successful registry deployments in 2026.
Why Payer Outcomes Are Not the Same as Clinical Endpoints
A common mistake is assuming that a registry built for regulatory post-marketing requirements will satisfy payer negotiators. Regulatory endpoints like progression-free survival or biomarker response are necessary but often insufficient. Payers need evidence that links therapy performance to resource utilization, productivity loss, and the patient’s lived experience. In risk-sharing contracts, the trigger for a rebate or performance bonus may depend on hospital readmission rates, adherence trajectories, or ability to delay disease-related complications—none of which are captured neatly in a typical disease registry.
The solution is to co-design the endpoint framework with payer decision-makers before the registry launches. That means mapping every clinical endpoint to its economic and humanistic counterpart. For example, a reduction in hemoglobin A1c becomes more meaningful when paired with a decline in diabetes-related emergency room visits or an improvement in the EQ-5D-5L utility index. This alignment is the backbone of any credible value-based contract.
From Fixed Registry Schema to Adaptive Endpoint Architectures
Traditional registries freeze their case report forms (CRFs) years in advance. But 2026’s health data ecosystem is too fluid for that rigidity. Risk-sharing deals often include milestones that trigger contract renegotiation, based on interim registry analyses. If the registry cannot adapt its endpoint definitions to new clinical knowledge or payer requests, the contract becomes obsolete before its first audit.
Modular CRF Design
Break the registry into core modules (safety, disease status) and optional modules (patient-reported outcomes, health economics, digital sensor data). This allows you to add or remove endpoints without rebuilding the entire database. Modularity also supports multi-indication expansion—a practical advantage when a therapy’s lifecycle extends from one condition to several.
Periodic Endpoint Review Gates
Schedule formal endpoint re-assessment every six to nine months. Invite payer medical directors, health economics leads, and patient advisors to review whether the current measures still reflect the value proposition. This transforms the registry from a passive data repository into a living governance tool for the VBC.
Operationalizing RWE: Interoperability and FHIR-First Data Feeds
The credibility of any registry hinges on data completeness and timeliness. In a value-based contract, missing data is not just a statistical nuisance—it can cause a dispute over whether an outcome was achieved. The 2026 standard is to build registries that ingest data directly from electronic health records (EHRs) and claims systems using HL7 FHIR standards. This reduces manual data entry, minimizes missingness, and allows near-real-time endpoint evaluation.
Adopt OMOP for Cross-Source Harmonization
Payers and health systems are increasingly comfortable with the Observational Medical Outcomes Partnership (OMOP) common data model. Converting registry data to OMOP on the back end simplifies the exchange of summary statistics and enables secondary uses of the evidence. It also makes it easier to benchmark registry outcomes against external synthetic control arms—a feature that many payers now request as part of their risk-sharing deal’s “fairness” clause.
Wearable and Sensor Endpoints: The New Negotiation Frontier
In 2026, functional outcomes from connected devices (step count, sleep quality, heart rate variability) can serve as objective proxies for payer-relevant improvements. For musculoskeletal or cardiovascular therapies, these digital endpoints may be more compelling than a clinician-scored scale. However, you must validate the sensor algorithm against the underlying clinical state and ensure that the device is accessible to all patient groups, including those without smartphone access. Otherwise, the registry biases the contract against underserved populations.
Key Strategies for Selecting the Right Endpoints
When choosing endpoints, apply a four-part test: Is it meaningful to the payer’s financial model? Is it measurable with acceptable accuracy in routine care? Is it unlikely to be gamed or influenced by non-therapy factors? And does it capture the patient’s voice? Use this test during the design phase and revisit it whenever contract performance dips.
- Total cost of care: Include components like inpatient stays, emergency department visits, and outpatient infusions. These are the payer’s most familiar data points.
- Disease-specific outcomes: Choose those that are strongly correlated with long-term resource utilization, not just short-term efficacy. For example, time to first hospitalization is more meaningful than a lab value alone.
- Patient-reported outcomes (PROs): Use condition-specific instruments that the payer understands, such as the PROMIS scales or disease-specific quality-of-life measures. Set thresholds that represent patient-important change, not just statistically significant change.
- Adherence and persistence: For chronic therapies, payer risk is heavily tied to patients staying on treatment. Express adherence as a continuous metric with a clinically justified threshold (e.g., proportion of days covered ≥ 80%).
- Safety signals and discontinuation events: These often trigger contract penalties. Ensure the registry captures adverse events and the reasons for discontinuation—especially when switching occurs due to lack of effectiveness or tolerability.
Addressing Confounding and Real-World Bias in the Registry
Payers are increasingly sophisticated about bias, so a 2026 registry must include a pre-specified analysis plan that documents how confounding will be handled. Propensity score matching, multivariable risk adjustment, and negative control outcomes should be described up front, not after the results are known. Moreover, because the registry is embedded in routine practice, treatment groups may differ in ways that are hard to observe. One way to build confidence is to include a small external comparator from claims data, specifically chosen because it reflects the payer’s real member population rather than a clinical trial cohort.
Handling Missing Data and Loss to Follow-up
Risk-sharing agreements often fail because patients drop out of the registry. The most common culprit is that sites receive no incentive to continue data collection after the treatment episode is over. Build a retention plan that includes patient-facing summaries of their own progress, minimal-burden follow-up modes (text reminders, telemedicine visits), and site performance feedback. In the statistical analysis, use multiple imputation or inverse probability weighting, but be transparent about the assumptions.
Governance That Fosters Payer Trust
For a registry that informs financial settlements, independent governance is non-negotiable. Establish a steering committee with at least one payer representative, one patient advocate, and an independent statistician. The committee should have the authority to review endpoint definitions, approve interim analyses, and arbitrate disputed outcomes. Publishing the registry protocol in a public repository (like ClinicalTrials.gov or a peer-reviewed registry methods journal) also signals accountability.
A word of caution: don’t let the governance committee become a forum for post-hoc contract negotiation. The committee’s job is to interpret the data according to pre-agreed rules, not to re-litigate the contract. Keep the roles separate—the VBC contract is managed by the commercial and alliance teams, while the registry governance body focuses solely on evidence integrity.
Leveraging Synthetic Control Arms and External Benchmarks
In rare disease and gene therapy, randomization to placebo is often impossible. Payers accept this, but they still want a credible counterfactual. Your registry should include a pre-specified synthetic control arm (SCA) built from historical trial data, claims, or other registries. The SCA should be validated against at least one known external outcome before the contract starts. This builds payer confidence that the registry can reliably measure the incremental value of the therapy.
In 2026, several regulatory authorities and HTA bodies have published standards for SCA use in real-world evidence. Align your approach with those frameworks to avoid surprises when the payer’s own health economics team reviews the methodology.
Patient-Centered Endpoints: The Bridge Between Payers and Providers
Ultimately, aligning registry endpoints with payer outcomes requires more than a technical exercise. It requires a shared understanding of what “value” means from the patient perspective. Payers may prioritize cost avoidance, but if the therapy does not meaningfully improve the patient’s ability to work, sleep, or perform daily activities, the long-term savings will not materialize. Include a patient prioritization exercise in the registry design phase. Ask patients which outcomes they would be willing to trade off for a given side effect or cost burden. Their answers often reveal endpoints that payer actuaries never considered—like time to return to work or caregiver burden—and yet these can be the very outcomes that drive contract performance.
Conclusion
Designing a registry for a value-based contract is not an extension of classic clinical registry practice; it is a new discipline that combines epidemiology, health economics, and payer engagement. By starting with payer decision contexts, adopting interoperable data standards, building adaptive endpoint architectures, and governing the evidence with trust in mind, sponsors can create registries that actually survive the scrutiny of risk-sharing negotiations. The 2026 environment rewards those who treat the registry as a dynamic evidence asset—one that aligns the clinical story with the financial and human outcomes that payers are truly paying for.
