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Trusted data, incentive-aligned payment methods and seamless system integrations will continue to transform how care is delivered and pave the wave for a more responsive, equitable and genuinely patient-centered healthcare system, said Kevin Ritter, executive vice president for CareInMotion at Altera Digital Health, a health IT company.
This is one of three predictions for health IT in 2026 from Ritter, a digital health professional with more than 20 years of experience spanning electronic health records, population health management, consumer health and data analytics throughout the healthcare industry.
Moving past fragmentation of patient data
In 2026, the healthcare industry will move past its long-tolerated fragmentation of patient information and demand a unified view of the patient, he said.
"FHIR-native architectures will enable organizations to build high-quality data fabrics that reconcile conflicting information and maintain a reliable record of provenance," he explained. "Modern pathways and ingestion engines validate, normalize and align data as it flows, creating clean and trustworthy information that clinicians and operational teams can rely on in real time. With this shift, data becomes more than an asset – it becomes a dependable foundation for safe and timely decision making.
"This reliable data layer aligns directly with new payment models that reward accuracy and completeness," he continued. "As the CMS Innovation Center expands value-based arrangements and commercial plans adopt hybrid-risk strategies, financial performance increasingly depends on data integrity. Quality reporting, risk adjustment, clinical workflows, care coordination and shared savings arrangements all require a consistent and comprehensive patient picture."
At the same time, organizations are replacing years of point-to-point interfaces with platform-based interoperability that allows frictionless integration across electronic health records, analytics platforms, care management tools and AI systems, he added. Taken together, these shifts make trusted data not only possible but essential for clinical excellence and sustainable operations, he said.
Intelligent data management
Ritter also says of 2026 that healthcare is entering an era of intelligent data management where real-time validation, data quality scoring and robust governance are paramount for improved patient outcomes and reduced costs – and for ensuring AI initiatives are trustworthy.
"This year, healthcare will transition from passively storing information to proactively managing it with intelligence and precision," he predicted. "Real-time data validation will become a standard expectation, with modern platforms evaluating every inbound message for structural accuracy, appropriate coding, semantic alignment, identity completeness and verifiable provenance.
"Errors are intercepted at ingestion instead of appearing months later during audits or reporting cycles," he continued. "This shift establishes a new level of trust in the data that drives clinical, operational and financial decisions."
Further, data quality scoring will become an operational tool rather than an IT metric, he added.
"Care teams will use it to prioritize outreach, close care gaps and confidently interpret AI outputs based on the reliability of the underlying data," he said. "Governance rules, terminology mapping and lineage tracking are embedded within the ingestion layer, eliminating manual overhead and improving consistency across systems.
"This integrated approach positions data quality as a frontline responsibility for clinical operations and finance, ultimately enabling better patient outcomes and more dependable AI-driven insights," he added.
The need for AI tools
And finally, Ritter remarked that value-based care is becoming more mainstream, making it crucial for organizations to have AI tools that support personalized pathways and predictive analytics that identify risks before they escalate.
"As value-based care accelerates in 2026, AI will become essential for managing population health at scale," he said. "Predictive models will mature from producing broad risk categories to generating individualized forecasts that anticipate clinical deterioration, medication adherence challenges, avoidable admissions and behavioral barriers.
"These insights draw on unified clinical, claims, social and utilization data, allowing teams to act earlier and with greater accuracy," he continued. "Providers receive concise and relevant summaries while patients benefit from clear, tailored guidance supported by evidence and context."
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Healthcare IT News is a HIMSS Media publication.
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