2026 Health IT Trends: What the Industry Is Building Toward Now

  By Vanessa Candelora , Management & Operations Lead, Payer, Provider & Technology 

Over the past several years, the healthcare information technology (health IT) industry has made visible progress on foundational capabilities. Application programming interfaces (APIs) are standing up, standards adoption has accelerated, and participation in national exchange efforts has expanded, often in response to policy mandates and regulatory timelines. These advances have created a baseline level of technical readiness across much of the ecosystem.

As industry moves into 2026, however, the center of gravity is shifting. Attention is increasingly focused on whether these capabilities can support sustainable business models, reduce operational burden, and function reliably within real-world workflows. Market pressures, workforce constraints, access challenges, and rising expectations around automation are converging with policy requirements, forcing organizations to confront gaps that technical connectivity alone cannot resolve.

The trends expected to shape 2026 reflect this convergence. They span infrastructure maturation, care delivery, pharmacy business-model pressures, outcomes-based reimbursement experimentation, prior authorization execution, and a more realistic approach to artificial intelligence (AI). Taken together, they point to an industry less focused on proving that something is possible and more so on determining what can be scaled, governed, and sustained.

1. Interoperability Shifts From “Can We Exchange?” to “Can We Use It?”

Federal policy is increasingly explicit that interoperability success is not measured by the existence of APIs or exchange pathways but whether data are usable in practice to achieve desired outcomes.

Centers for Medicare and Medicaid Service’s (CMS) Health Technology Ecosystem Interoperability Framework positions interoperability to reduce burden and improve outcomes, not as an end in itself. The framework emphasizes ensuring existing standards and exchange mechanisms work consistently across organizations and workflows and introduces the concept of CMS-aligned networks to encourage voluntary alignment on shared expectations for usability and implementation.

This framing is reinforced throughout the CMS Interoperability and Prior Authorization Final Rule (CMS-0057-F), which repeatedly ties API adoption to burden reduction, timeliness, and actionable data exchange rather than technical compliance. The rule makes clear that access to data alone is insufficient if those data cannot be used effectively at the point of care or within administrative processes. This will be increasingly important as we look to further empower patients with cost and quality transparency, wherein the value will depend not just on disclosure but also delivering information in timely, comprehensible formats that directly support real-world decision making by patients, providers, and plans alike.

Industry responses to the CMS/Assistant Secretary for Technology Policy (ASTP) Health Technology Ecosystem Request for Information (RFI) echo this message. The American Health Information Management Association’s RFI feedback identifies data quality issues, inconsistencies, a lack of standardization, and governance challenges as the primary barriers to interoperability value. Respondents note that variability in implementation and incomplete data undermine trust and limit downstream use, even when data are technically available.

Measurement and quality organizations, including the National Committee for Quality Assurance, have similarly emphasized that inconsistent and incomplete data limit the effectiveness of digital quality measurement and automation efforts. The message is consistent across stakeholders: The interoperability challenge has shifted from transport to fitness for use.

Ultimately, this shift signals that the industry’s real opportunity lies in transforming interoperable data into dependable, high-quality inputs that unlock automation, improve decision-making, and create measurable value across clinical, operational, and analytic workflows—turning compliance investments into competitive advantage.

2. FHIR, a Global Foundational Interoperability Layer

Health Level 7’s Fast Healthcare Interoperability Resources (FHIR®) has long been perceived as “new” or “emerging,” but much has changed since the 2011 initial draft and today's globally adopted standard. FHIR is now widely viewed as the foundation for clinical healthcare data exchange. Its role has been further solidified through federal policy, including the 21st Century Cures Act requirements, which position FHIR as a core mechanism for modern, API-based interoperability.

This maturity matters because the industry’s next phase of innovation depends on deterministic, standards-based data exchange. Health IT interoperability requires precise, unambiguous representations of clinical data. While artificial intelligence is increasingly being used to analyze and summarize information, it cannot replace the need for structured, standardized data. AI is probabilistic by design; it generates “best guess” outputs rather than guaranteed truth. FHIR provides the schema, constraints, and shared semantics that establish the “ground truth” on which AI systems depend to function safely.

CMS interoperability strategy documents reinforce this reality not by introducing new FHIR mandates but by signaling that scalable interoperability, automation, and responsible use of advanced analytics all depend on consistent, high-quality standard FHIR data exchange. In this context, the industry cannot leapfrog FHIR with AI. Instead, FHIR serves as the prerequisite layer, enabling more advanced capabilities to be deployed with greater confidence, control, and impact.

At the same time, industry experience is revealing that FHIR adoption alone does not guarantee usability. Partial implementations, inconsistent profiling, and variable data quality continue to limit the value of FHIR-based exchange in operational workflows.

Market momentum is moving away from document-centric exchange toward API-first architectures that more closely resemble modern internet patterns. This shift enables real-time and near real-time interactions, but also raises expectations around performance, completeness, and reliability.

In 2026, the focus will increasingly be on FHIR operationalization: How well FHIR implementations support real workflows, how consistently data are populated, and how effectively FHIR-based data can be used across organizational boundaries. As FHIR enables interoperability and drives toward the vision of a modern digital healthcare system, shortcomings in strategic implementation and governance become more visible and consequential.

3. Pharmacy Advanced Practice: Transforming Pharmacy Business Models

Brick-and-mortar pharmacies are at a crossroads. While on one hand many states have expanded the pharmacist's scope of licensure to allow more clinical services to be delivered by pharmacists, in parallel, brick-and-mortar pharmacies are closing at an alarming rate, particularly in rural and underserved communities. This exposes a core disconnect: Pharmacists could play a significantly larger role in care delivery, but business models that rely primarily on prescription fulfillment are increasingly unsustainable.

The Pharmacy Interoperability Whitepaper we wrote under the National Council for Prescription Drug Programs (NCPDP) Foundation grant underscores that pharmacy-delivered clinical services are often documented in siloed systems or unstructured formats that are disconnected from provider electronic health records, payer workflows, and quality programs. This fragmentation limits visibility into pharmacist contributions and makes integration of these services to care coordination, referrals, and longitudinal records difficult.

We recently played a significant role in the writing of a whitepaper on advanced pharmacy practice in scaling pharmacy-delivered clinical services making clear that interoperability is not just a technical requirement but business model enabler. To move beyond pilots, pharmacy services must be documented consistently, exchanged using standards, and embedded into payer and provider workflows in ways that support attribution, measurement, and reimbursement. Without interoperable infrastructure, expanded clinical services remain difficult to operationalize and even harder to sustain.

This challenge intersects directly with rural healthcare. As CMS begins deployment of $50 billion through the Rural Health Transformation program this year, pharmacy interoperability becomes a critical lever for preserving access in communities where pharmacy closures risk further widening care gaps.

Aligning data exchange standards like NCPDP SCRIPT and FHIR is central to this shift. Improved interoperability between pharmacies and clinicians within provider practices or the hospital setting would make pharmacist-delivered services more visible, enable documentation, and provide a more accurate picture of a patient’s history. It would also allow pharmacies to demonstrate greater value locally within communities beyond dispensing and operate at the top of their license. Without it, the expanded scope of practice will remain underutilized and pharmacy closures will continue to erode access rather than extend it.

4. Outcomes-Based Reimbursement Through Chronic Care

After years of mixed results from broad value-based care (VBC) initiatives, policymakers and industry are taking a more cautious, targeted approach. Rather than pursuing system-wide transformation, newer models are focusing on narrower use cases with clearer attribution, defined populations, and measurable outcomes. Interestingly, Healthcare IT Today asked industry leaders whether the lack of progress in VBC was a policy or technology issue, and the results were mixed, with respondents also rightly noting that operational considerations are also at play.

Regardless of industry opinion on what has held VBC back, chronic care has emerged as a practical testing ground for this more targeted focus. Programs such as the CMS ACCESS Model avoid the language of “value-based care” altogether, instead emphasizing outcomes-based reimbursement tied to specific chronic conditions. This distinction matters. ACCESS reflects an effort to apply value-based principles without reopening the broader and often contentious VBC debate.

These models depend heavily on the ability to integrate administrative and clinical data over time to support longitudinal measurement, attribution, and performance assessment. Persistent challenges remain, including data fragmentation, inconsistent timeliness, and misalignment between clinical workflows and reporting requirements. Experience has shown that automation alone does not solve these issues without operational alignment, strong governance, and shared definitions.

Artificial intelligence is increasingly discussed as a potential enabler in chronic care, particularly for earlier detection, risk stratification, and population-level analysis. In this context, AI could help make outcomes-based reimbursement more operationally feasible by identifying at-risk patients earlier, supporting care gap closure, and monitoring trends over time. However, these benefits are only achievable when AI is grounded in interoperable, high-quality data; embedded in workflows that support timely intervention; and reported to reimbursement models to incorporate these advances.

In 2026, progress in outcomes-based reimbursement is expected to remain incremental and program specific. Rather than a wholesale return to value-based care, the industry is likely to see continued experimentation in targeted models that test whether better data, finer tooling, and clearer accountability can finally translate preventive care and outcomes-based concepts into sustainable, scalable practice.

5. Prior Authorization: CMS-0057 Execution & Finally Tackling Pharmacy PA?

Prior authorization remains one of the most operationally significant use cases for interoperability. CMS-0057 is no longer new, but 2026 marks a transition from planning and implementation to execution and accountability.

While affected payers must begin annual reporting to CMS on patient access API data requests starting January 1, 2026, the major compliance deadline is fast approaching on January 1, 2027, when payers are required to fully implement additional requirements, including provider access APIs and payer-to-payer APIs. By this 2027 deadline, payers must also meet expectations around the scope and timeliness of payer-to-payer data exchange, including sharing up to five years of patient data with patient permission.

These requirements are already creating divergence across organizations. Deciding how much to invest and what to implement can be complicated. Some are leveraging APIs to reduce manual work and improve turnaround times, taking advantage of the opportunity to align their enterprise-wide goals with the spirit of the regulation to empower patients, reduce burden, increase efficiency, and lower costs. Others are implementing the minimum required functionality without a meaningful workflow change. These differences will become increasingly visible as reporting and enforcement mature.

Excluded from this rule, prior authorization for drugs remains a significant pain point. While many states have had requirements for years, federal agencies have indicated that it is likely to receive increased attention. The industry is moving toward adopting the same goals (electronic, fast, transparent) for prescription drugs. Existing industry efforts leveraging NCPDP SCRIPT and HL7 FHIR standards provide a foundation, but adoption and impact remain uneven.

6. Artificial Intelligence: From Hype to Governed, Practical Use

This list wouldn’t be complete without addressing Artificial Intelligence (AI), still the most discussed technology in healthcare. What has changed is the tone. AI is moving from marketing hype to operational deployment. The conversation is no longer about potential. It is about implementation.

AI performance is constrained by the same factors that limit interoperability: data quality, consistency, and governance. Incomplete or poorly structured data weaken model performance and increase risk, including flawed insights, misinterpretation of clinical evidence, and missed patient populations. As AI tools move closer to clinical workflows, the need for guardrails becomes more urgent. Clear use-case definitions, human oversight, performance monitoring, and defined accountability structures are not optional.

In the near term, adoption will continue in lower-risk areas such as documentation support, administrative automation, and operational analytics. More complex clinical applications, particularly predictive and preventative models, introduce a different challenge: Sustainability.

Early detection and intervention models show promise in improving outcomes and reducing downstream costs. However, unless payers explicitly incorporate these preventative AI tools into reimbursement structures, they will remain small-scale, grant-funded, or limited to large integrated systems such as the Mayo Clinic. Operationalizing provider AI requires financial alignment. If payment models do not support proactive, AI-enabled intervention, the tools will not scale broadly across the delivery system.

This is the payer side of AI adoption. It is not just about approving technology. It is about embedding preventative intelligence into payment design so that providers can sustainably deploy it.

AI does not stand apart from the broader 2026 trends. Its impact depends on the maturity of interoperability, standards implementation, data governance, and reimbursement alignment across the healthcare system.

Looking Ahead

The defining challenge of 2026 is not the absence of standards or policy direction but the expectation that existing capabilities deliver measurable operational value. Compliance remains necessary, but it is increasingly perceived as the floor rather than the ceiling.

Organizations that can translate interoperability investments into usable workflows, reduced burden, and responsible automation will be better positioned to reduce costs and increase revenue at scale. Technical capability alone is no longer sufficient.

If your organization is navigating implementation hurdles, reassessing strategy, or identifying new opportunities tied to interoperability, automation, or data governance, we welcome the conversation. We would value the chance to learn more about the challenges or opportunities you are facing and explore whether we can help.

Connect with us to set up an exploratory discussion.