Studies show that healthcare continues to generate nearly 30% of the world’s data, yet over 60% of executives cite siloed systems as a top obstacle to coordinated care, and almost 80% of that data remains unstructured and inaccessible.
Value-based care models, in which nearly 40% of Medicare payments depend on outcomes, demand more than simple data exchange to hit quality targets and manage costs. Embedding decision-ready intelligence directly into workflows to surface the right insight to the right provider at exactly the right time is now vital for delivering on the promise of better care at lower cost.
The limits of basic interoperability
Standards like HL7 and FHIR have advanced technical data exchange, yet they often deliver raw “data dumps” that overwhelm users. Up to 72% of decision-support alerts are overridden when they lack context or relevance which contributes to alert fatigue among clinicians. Despite 70% of hospitals exchanging data, only 42% of clinicians actually use that information at the point of care.
Clinicians bounce between multiple portals such as EHRs, payer sites and lab systems to manually reconcile records, duplicate documentation, and wrestle with inconsistent code sets. Beyond slowing workflows, this friction also delays critical interventions, increases operational costs, and exacerbates provider burnout. In a landscape where nearly 80% of data remains unstructured, simple interoperability risks becoming an exercise in box-checking rather than a catalyst for smarter collaboration.
The imperative of intelligent collaboration in value-based care
Under value-based care, success hinges on aligning quality outcomes with financial incentives. According to the Health Care Payment Learning & Action Network’s 2022 report, roughly 46% of Medicare fee-for-service payments flowed through alternative payment models in 2021—programs that link reimbursement to performance metrics such as readmission rates, patient satisfaction, and chronic disease management. To thrive in this environment, organizations need:
- Embedded guidance that surfaces care-gap notifications and coding prompts at the moment of documentation.
- Risk stratification flags that identify high-risk patients before their conditions deteriorate.
- Coverage-specific recommendations to avoid claim denials and promote appropriate utilization.
Intelligent collaboration goes beyond sharing data. It changes raw information into context-aware insights that support timely, coordinated decisions across the entire care continuum.
From raw data to proactive guidance
A simple four-step workflow converts scattered data feeds into actionable insights:
1: AI-driven ingestion: Capture EHR, claims, and lab data streams in real time, regardless of source or format.
2: Harmonization and normalization: Standardize disparate code sets (ICD-10, SNOMED, CPT) and resolve patient identities to establish a trusted single source of truth.
3: Contextual layering: Use advanced analytics to filter low-value noise and surface only care-gap, risk-stratification, and documentation alerts within clinician workflows.
4: Workflow embedding: Integrate insights directly into the tools clinicians and payers rely on, ensuring proactive guidance appears exactly when and where decisions are made.
This end-to-end approach converts passive data exchange into proactive, decision-ready recommendations, driving higher adoption and more meaningful collaboration.
Illustrative use cases: Intelligence in action
Real-world implementations demonstrate how contextualized insights reshape payer–provider interactions:
Health plans examine claims and EHR data to locate each patient’s care gaps. Clinicians see these gaps in the chart and schedule preventive screenings or follow-up visits during documentation.
Coverage-specific recommendations
Prior-authorization alerts and benefit summaries pop up in the EHR. They guide clinicians to choose treatments that match each patient’s insurance plan, reduce denials, and speed access to covered services.
Chart requests take only minutes. The system delivers signed Continuity of Care Documents to the EHR. Manual faxes and phone tag become relics of the past.
Preemptive documentation flags
Coding prompts appear days before scheduled visits when providers miss critical chronic-care codes. Early alerts lower audit risk and ensure proper reimbursement.
Each of these examples illustrates how turning raw data into actionable intelligence minimizes manual steps, reduces errors, and fosters deeper collaboration.
Data access vs. data activation
Presenting disparate data sets in a portal is no longer sufficient. True transformation requires activation: embedding context-aware guidance at the moment of decision.
| Data Access | Data Activation |
| Logging into multiple, disconnected portals | In-chart care-gap notifications |
| Manual reconciliation of claims and notes | Real-time risk-stratification flags |
| Separate billing and clinical systems | HCC coding prompts integrated in charge capture |
| Reactive outreach strategies | Automated AI-driven voice and SMS patient engagement |
Activation helps teams to act decisively by reducing no-shows, avoiding emergent episodes, and closing documentation gaps before they occur.
Impact on care quality, operational efficiency, and shared value
Embedding decision-ready insights yields measurable benefits across the care continuum:
- Clinical outcomes: A kidney-care program saw 19% fewer adjusted admissions for stage 4 CKD among Medicare Advantage patients versus traditional Medicare peers, underscoring the power of proactive intervention.
- Provider efficiency: At Yale School of Medicine, badge-based single sign-on shaved 6–20 minutes off daily login routines. Voice-recognition scribing cut documentation time by 50%, saving over eight hours of after-hours charting weekly and reducing click fatigue.
- Financial performance: Integrating HCC coding prompts into charge-capture workflows boosted coding accuracy by 18%. This uplift enabled ACOs to recapture millions in risk-adjusted payments, aligning incentives between payers and providers.
Taken together, these gains boost care quality and ease clinician burnout. They also optimize operations and foster shared value across the healthcare ecosystem.
Bringing it all together
In today’s value-based landscape, basic interoperability is no longer enough. Healthcare organizations must embed contextualized, decision-ready intelligence directly into clinical and administrative workflows to create smarter collaboration and measurable impact.
Introducing the Veradigm Network—a unified platform that ingests, harmonizes, and contextualizes data from EHRs, payer claims feeds, and life-science sources. With real-time alerts, advanced analytics, and secure automation woven into every decision point, the Veradigm Network turns fragmented data into actionable insights.
Experience “Transforming healthcare, insightfully®” first-hand. Schedule a free demo today to learn how contextualized intelligence can power smarter collaboration, better outcomes, and sustainable value.