Value-Based Care (VBC) is no longer simply a shift away from fee-for-service. For health plans, the strategic challenge is turning complex provider contracts, fragmented clinical information, and performance incentives into sustainable financial and clinical outcomes.
The next phase of Value-Based Care will be won on execution
The economics of U.S. healthcare make efficient, accountable care increasingly important. According to the Centers for Medicare & Medicaid Services (CMS), national health expenditures reached $5.3 trillion in 2024, growing 7.2% year over year and representing 18% of U.S. gross domestic product. Private health insurance spending grew 8.8% to approximately $1.64 trillion. These figures highlight the scale of the spending challenge facing the healthcare system
The shift toward value-oriented payment models is a substantial strategy to address this problem. KFF reports that 35.2 million people (55% of eligible Medicare beneficiaries) were enrolled in Medicare Advantage in 2026. Separately, CMS' Medicare Shared Savings Program (MSSP) reported 476 accountable care organizations (ACOs) engaged in 2024, with 75% earning shared savings and total earned performance payments of $4.10 billion.
These figures demonstrate the scale of value-based arrangements and performance-based financial incentives. That said, results can be mixed for any given contract, payer, or provider organization.
Thus health plan executives’ most important VBC question is how to make arrangements work consistently across provider networks, populations, products, and markets. This operational challenge requires understanding contract economics, validating clinical and claims data, monitoring provider performance, identifying exceptions, and connecting insights to action.
The next phase of Value-Based Care will depend not just on adopting new payment models, but on building the intelligence and operational discipline required to manage them.
1. Contract complexity is becoming a strategic performance issue
Value-based contracts can differ significantly in their financial and operational design. Depending on the arrangement, they may include shared savings, shared losses, quality incentives, total-cost-of-care benchmarks, risk corridors, attribution rules, and performance thresholds.
Managing these terms across multiple provider groups creates a challenge that extends well beyond contract negotiation.
Consider a health plan working with several provider organizations. One contract may make shared-savings payments contingent on quality performance, while another uses a different benchmark methodology or attribution period. The plan must translate each agreement into operational rules, connect those rules to the right population, monitor results, and calculate settlements accurately.
When contract interpretation and execution rely on spreadsheets, manual reviews, and disconnected systems, the risk of inconsistent calculations and delayed reconciliation increases.
The impact can extend across finance, claims operations, provider relations, network management, and clinical programs. Teams may spend substantial effort resolving discrepancies rather than identifying opportunities to improve performance.
For executives, this creates four priorities:
- Contract visibility: Understand critical obligations, financial terms, exclusions, and performance requirements across the portfolio.
- Consistent execution: Translate contract language into traceable rules and workflows.
- Financial control: Validate that calculations, adjustments, and settlements reflect the applicable terms.
- Performance transparency: Connect contract requirements to quality, cost, utilization, and provider-level outcomes.
The objective is not merely to digitize agreements. It is to make contract economics actionable throughout the life of the arrangement.
2. Clinical data quality is central to financial and regulatory integrity
Value-based care depends on an accurate understanding of member health, provider activity, and the services delivered. Yet relevant information is often distributed across claims, electronic health records, clinical documents, provider systems, and administrative databases.
These sources do not always tell the same story. Diagnoses may be documented differently, records may be incomplete, and clinical evidence may not be readily available when performance or payment decisions are made. This matters for quality measurement, care-gap identification, risk adjustment, utilization analysis, and provider performance evaluation.
Federal oversight illustrates why documentation quality must be treated as a financial and compliance priority. In a 2024 report, the HHS Office of Inspector General examined Medicare Advantage diagnoses reported through health risk assessments (HRAs) and HRA-linked chart reviews that did not appear in other service records for the same beneficiaries in 2022. The OIG estimated that these diagnoses generated $7.5 billion in risk-adjusted payments for 2023, involving 1.7 million beneficiaries. The agency raised concerns that some diagnoses could be inaccurate and lead to improper payments or could indicate that beneficiaries were not receiving follow-up care for serious, reported conditions.
This finding does not mean that all these payments were improper. It does demonstrate the importance of validating diagnoses against supporting documentation and appropriate care evidence.
For payer executives, the lesson extends beyond risk adjustment: data that enters a financial or clinical workflow must be sufficiently reliable for the decision it supports.
A more disciplined approach combines:
- Automated identification of missing, inconsistent, or potentially unsupported information.
- Validation of clinical evidence against relevant documentation and applicable requirements.
- Traceability from the source record to the resulting measure, calculation, or decision.
- Clear processes for investigating exceptions and correcting underlying data.
- Monitoring of data completeness and reliability across providers and populations.
Clinical data intelligence means understanding what the data supports, not simply collecting more of it.
3. The opportunity is to connect cost, quality, and population health
Value-based care cannot be managed effectively through financial metrics alone. Lower spending does not necessarily indicate better care, just as higher quality scores do not automatically demonstrate improved financial performance.
Payers need to understand the relationship between utilization, clinical outcomes, member complexity, provider performance, and contractual incentives.
CMS's performance-year 2024 MSSP results offer a useful illustration of the connection between quality and operational performance. Among ACOs reporting through the CMS Web Interface, the mean percentage of beneficiaries with adequately controlled high blood pressure increased from 77.80% in 2023 to 79.49% in 2024. The mean percentage of beneficiaries with poor haemoglobin A1c control declined from 9.84% to 9.44%.
These are specific program-level measures, not proof that every ACO improved or that every payer will achieve similar results. They nevertheless illustrate why VBC performance requires the ability to measure clinical outcomes alongside financial results.
For health plans, a connected performance model should address five dimensions.
- Medical cost and utilization: Identify changes in service utilization, avoidable variation, and opportunities to improve care coordination. Interpret these patterns alongside clinical context rather than treating lower utilization as an outcome in itself.
- Quality and clinical outcomes: Monitor relevant quality measures, validate supporting evidence, and identify gaps requiring provider or care-team intervention.
- Risk and population understanding: Improve the reliability of member health information used to understand clinical complexity, expected care needs, and risk-adjusted performance.
- Provider performance: Compare provider organizations using consistent definitions, relevant benchmarks, and contract-specific requirements. Identify where performance differences warrant investigation or targeted support.
- Contract and payment integrity: Validate financial calculations and reconcile them against the terms, evidence, and performance conditions applicable to each arrangement.
The opportunity is to bring these dimensions together so leaders can understand not just what changed, but why it changed and what action is justified.
4. Risk adjustment requires both completeness and clinical defensibility
Risk adjustment is an important component of many payer payment models. In Medicare Advantage, CMS adjusts payments based in part on beneficiary health status, recognizing that individuals with greater healthcare needs may require more resources.
Accurate risk adjustment depends on diagnoses that are supported by appropriate documentation and comply with applicable requirements. Incomplete clinical information can obscure member complexity, while unsupported diagnoses can create compliance and financial exposure.
This makes risk adjustment more than a coding or documentation exercise. It requires a reliable process connecting clinical evidence, diagnosis validation, coding workflows, and audit readiness.
Health plans should be able to identify whether relevant clinical evidence is available, distinguish documented conditions from information requiring further validation, and maintain an auditable trail for material decisions.
The same discipline supports broader VBC operations. Reliable clinical context helps plans interpret population needs, evaluate performance fairly, and identify where care coordination or provider engagement may be appropriate.
The executive goal is a process that improves completeness without compromising accuracy or documentation integrity.
5. Automation must improve decisions, not just accelerate tasks
Automation can reduce manual work across contract review, claims analysis, clinical-data validation, quality reporting, and reconciliation. But automating a flawed process can reproduce inconsistencies faster rather than eliminate them.
As per CAQH, U.S. healthcare could save a further $21B annually by fully automating manual and partially automated administrative transactions.
Health plans should prioritize automation where it improves control, consistency, and decision quality.
- Automate repeatable work. Apply technology to structured extraction, routine validation, reconciliation, and reporting where requirements are clear and outcomes can be tested.
- Use intelligence to identify exceptions. Flag conflicting contract terms, missing evidence, inconsistent provider information, unexpected payment patterns, and performance deviations that merit review.
- Connect findings to action. Route validated insights to the appropriate finance, claims, clinical, network, compliance, or provider-relations workflow.
- Preserve traceability and oversight. Maintain the evidence, rules, and decision history needed to explain important financial and clinical actions.
This approach is particularly important when using AI. Technology should help teams identify relevant information and prioritize work, while appropriate human oversight remains in place for ambiguous contract language, clinical judgment, and decisions with material compliance or financial implications.
The right measure of automation is not the number of tasks automated. It is whether the process becomes more accurate, timely, consistent, and accountable.
6. Digital quality measurement makes data readiness more important
The move toward digital quality measurement reinforces the need for better information management.
In its performance-year 2024 MSSP results, CMS reported increased adoption of all-payer digital quality measures (including electronic clinical quality measures and MIPS clinical quality measures) compared with 2023. CMS has encouraged ACOs to move toward digital reporting that leverages electronically stored and transmitted health information, interoperability, and more efficient reporting processes.
For health plans, digital measurement is not simply a reporting-system upgrade. It places greater emphasis on whether the underlying clinical information can be accessed, interpreted, validated, and used consistently.
A digital measure is only as dependable as the information and logic used to calculate it. Missing records, inconsistent clinical concepts, and weak evidence trails can undermine the reliability of reported results.
Payers should therefore assess their readiness across several areas:
- Availability and interoperability of relevant clinical information.
- Data completeness and consistency across sources.
- Reliable mapping of clinical concepts to applicable measure requirements.
- Validation and traceability of measure inputs.
- Ability to investigate exceptions and correct underlying data issues.
Building this foundation can support more reliable quality reporting while reducing avoidable manual effort. It also creates reusable capabilities for other VBC workflows that depend on trustworthy clinical information.
7. A practical executive roadmap for better VBC performance
Health plans do not need to transform every contract and workflow at once. A phased approach can help establish measurable improvements while limiting implementation risk.
Step 1: Establish the baseline
Assess contract complexity, manual processing effort, reconciliation timelines, data completeness, quality-measure reliability, and visibility into provider performance.
Establish current performance levels before setting improvement targets.
Step 2: Prioritize high-impact use cases
Identify the workflows with the clearest business rationale, such as contract reconciliation, documentation validation, quality-data completeness, or provider-performance monitoring.
Prioritize opportunities based on expected impact, feasibility, data readiness, and regulatory or financial importance.
Step 3: Connect the relevant information
Link contract terms to the relevant claims, provider, member, clinical, and performance information. Establish ownership, validation standards, and procedures for resolving discrepancies.
Step 4: Embed intelligence in operational workflows
Make validated insights available to the teams responsible for acting on them. Define exception-handling procedures, escalation paths, audit trails, and accountability for decisions.
Step 5: Measure results and expand selectively
Track outcomes using measures such as:
- Contract reconciliation cycle time.
- Accuracy of contract calculations and settlements.
- Administrative effort per contract or reconciliation.
- Completeness of supporting clinical documentation.
- Reliability and timeliness of quality reporting.
- Resolution rates for identified data and payment exceptions.
- Provider-level performance against relevant benchmarks.
The specific measures and targets should reflect the plan's business model and baseline. Financial or clinical improvements should be attributed to a technology implementation only when the evidence supports that conclusion.
How clinical data intelligence can support the next phase of VBC
The challenges facing value-based care are interconnected. Contract economics depend on consistent interpretation and execution. Payment attribution depends on reliable rules and supporting evidence. Quality measurement depends on usable clinical information. Provider performance management depends on connecting results to the right populations, relationships, and interventions.
Managing these activities in isolation limits visibility and can create additional work for already stretched teams.
HiLabs' MCheck Value-Based Care portfolio, powered by our VC³ intelligence layer, is positioned to help health plans address these challenges through capabilities spanning contract economics, member attribution, care optimization, and regulatory readiness.
We help unlock the broader opportunity to connect information that has traditionally been managed in silos, identify exceptions earlier, and help operational teams make more consistent, traceable decisions. Payer leaders can then build a connected operating model that makes contract obligations, clinical evidence, financial outcomes, and performance measures easier to understand and act upon.
Conclusion: Make VBC performance measurable, not merely manageable
Value-based care has reached a scale where the ability to manage contracts, data, quality, and financial performance is a strategic capability for health plans.
The evidence shows both opportunity and responsibility. CMS's MSSP results demonstrate that shared-savings payments and measurable quality outcomes are achievable at scale. Federal oversight of Medicare Advantage risk adjustment underscores the importance of reliable clinical documentation and defensible payment decisions. Rising national healthcare expenditures reinforce the need for disciplined management of cost and care delivery.
No single technology or workflow will solve every challenge. But health plans can strengthen their position by connecting contract intelligence, clinical data quality, payment attribution, and performance management within a coherent operating model.
The future of value-based care will not be defined solely by how many contracts a health plan sign. It will be defined by how reliably those contracts translate into better decisions, defensible financial performance, and improved outcomes for the populations they serve.
Sources
- CMS — National Health Expenditure Data, NHE Fact Sheet: 2024 healthcare spending and expenditure growth
- KFF — Medicare Advantage in 2026: Enrollment Update and Key Trends: 2026 enrollment and market data
- CMS — Medicare Shared Savings Program Performance Year 2024 Financial and Quality Results
- CMS — Performance Year 2024 Financial and Quality Results Fact Sheet: Program quality results and digital measurement
- HHS Office of Inspector General — Medicare Advantage: Questionable Use of Health Risk Assessments Continues To Drive Up Payments to Plans by Billions: 2024 oversight report
- Health Affairs — Medicare ACOs in 2024: Increased Participation and Evolving Policy Impacts: Analysis of MSSP performance
This article is for informational purposes and does not constitute legal, clinical, or financial advice. Program results vary by payer, provider arrangement, population, and performance year.
