Healthcare technology trends to watch

The top healthcare technology trends in 2026 are not experiments anymore. AI has moved into clinical and operational workflows, interoperability standards have become mandatory, and care now extends well beyond the clinic through telehealth and connected devices. This guide covers each trend and what it means for the teams building healthcare software today.

By Kanika Mathur, Head of Service Delivery

Reviewed by Resourcifi healthcare engineeringPublished Feb 19, 2026Updated Feb 19, 20269 min read

Engineering

Key takeaways

The short version

AI is moving into real workflows, from predictive analytics and clinical decision support to agentic systems that help coordinate care and handle prior authorizations. Rock Health put AI-enabled companies at 37% of 2024 US digital health funding.
Interoperability is now enforced. FHIR-based APIs, USCDI+, SMART on FHIR, and TEFCA are the backbone of data exchange, so new systems must speak them.
Care has spread beyond the clinic. Telehealth, hybrid models, and asynchronous virtual care are permanent, supported by secure apps and remote monitoring.
Wearables and the Internet of Medical Things are becoming clinically relevant, feeding continuous patient data into care and population-health models.
For builders, the implications are clear: design for interoperability and privacy from day one, and treat AI and connected data as core architecture from the start.

The trends at a glance

The dominant healthcare technology trends are AI moving into clinical and operational workflows, interoperability becoming mandatory through FHIR-based standards, the permanent shift to telehealth and hybrid care, the rise of wearables and the Internet of Medical Things, and unified data platforms that combine records, claims, and device data for prediction. The common thread is that these are no longer experiments; they are becoming the expected baseline for new healthcare software.

The trends and why they matter
Trend	What is happening	Why it matters
AI and agentic automation	AI in decision support, revenue cycle, and care coordination	Cuts admin load and supports clinicians
Interoperability and FHIR	FHIR R4/R5, USCDI+, SMART on FHIR, TEFCA enforced	Data must flow between systems by default
Telehealth and hybrid care	Virtual, asynchronous, and remote-monitored care	Care extends beyond the clinic, permanently
Wearables and IoMT	Connected devices feeding clinical workflows	Continuous data beyond point-in-time readings
Unified data platforms	EHR, claims, and device data combined	Powers predictive and population health

AI and automation

AI in healthcare has moved from promise to practical use across both clinical and operational settings: predictive analytics and risk stratification, clinical decision support, medical imaging, and heavy use in the revenue cycle and administrative workflows. The money is following the work. Rock Health reports that US digital health startups raised 10.1 billion dollars across 497 deals in 2024, and that AI-enabled companies took 37% of that total across 191 deals, the largest single slice of the year. The newer frontier is agentic AI, autonomous systems that coordinate care across specialists, manage complex insurance authorizations, and pre-screen patients, with a human in the loop for safety. The constant is that AI now augments staff on real work rather than sitting in a lab.

Interoperability and FHIR

Interoperability has shifted from a goal to a requirement. The installed base is already there: ONC reports that as of 2021, 96% of US non-federal acute care hospitals and 78% of office-based physicians had adopted a certified electronic health record, so the systems new software must talk to are nearly universal. FHIR, the HL7 standard for exchanging healthcare data, in its R4 and R5 versions, together with USCDI+, SMART on FHIR, and the TEFCA framework, now forms the backbone of national data exchange in the US. Adoption is following: by 2024, 70% of US hospitals had enabled patient access through apps built to FHIR specifications, according to an ONC ASTP data brief. For anyone building healthcare software, FHIR-based APIs and standards compliance are the entry ticket to integrating with electronic health records and the wider health system.

Telehealth, wearables, and connected care

Care has permanently expanded beyond the clinic. The CDC National Center for Health Statistics found that 80.0% of US office-based physicians used telemedicine in 2024. That is down from a pandemic peak of 86.5% in 2021, but it sits far above the 15.4% recorded in 2019, so the practice has settled in well above where it started. Telehealth has matured into hybrid models that mix in-person visits, video, and asynchronous care where patients submit symptoms and photos and clinicians respond on their own schedule. Wearables and the Internet of Medical Things, connected sensors and devices, now feed continuous data into clinical workflows and population-health models, supported by secure apps and remote monitoring. The result is a more continuous, data-rich picture of each patient.

What it means for builders

For teams building healthcare software, these trends set the design baseline. Build for interoperability from day one with FHIR-based APIs, design for privacy and HIPAA-grade security throughout rather than bolting it on, and treat AI and connected-device data as core architecture from the start. Plan for integration with EHRs and the data exchange frameworks, and keep a human in the loop wherever AI touches clinical decisions. Getting these foundations right is what separates a demo from a system a health provider will actually adopt.

That is how we approach healthcare builds; see our healthcare industry work and healthcare AI development.

Frequently asked

Healthcare technology questions

What are the biggest healthcare technology trends?

The leading trends are AI moving into clinical and operational workflows, interoperability becoming mandatory through FHIR-based standards, the permanent shift to telehealth and hybrid care, the rise of wearables and the Internet of Medical Things, and unified data platforms that combine electronic health records, claims, and device data to power prediction. The common theme is that these are now the expected baseline for new healthcare software rather than experiments.

How is AI being used in healthcare?

AI is used across clinical and operational healthcare in predictive analytics and patient risk stratification, clinical decision support, medical imaging, and heavily in the revenue cycle and administrative workflows. A newer frontier is agentic AI, autonomous systems that help coordinate care across specialists, manage insurance authorizations, and pre-screen patients, always with a human in the loop for safety. In practice AI now augments clinicians and staff on real work rather than replacing them.

What is FHIR and why does interoperability matter?

FHIR, Fast Healthcare Interoperability Resources, is the HL7 standard for exchanging healthcare data through modern APIs, used in its R4 and R5 versions. Interoperability matters because health data has to flow safely between electronic health records, providers, and apps to support coordinated care, and in the US standards such as FHIR, USCDI+, SMART on FHIR, and the TEFCA framework have moved into enforcement. For builders, FHIR-based APIs are now the entry ticket to integrating with the health system.

What is the Internet of Medical Things (IoMT)?

The Internet of Medical Things is the ecosystem of connected medical devices, sensors, and wearables that collect and share health data with apps and clinical systems. It ranges from consumer wearables that track heart rate and activity to clinical-grade remote monitors. IoMT matters because it provides continuous, real-world patient data rather than occasional point-in-time readings, feeding remote monitoring, alerts, and population-health models, provided the data is secured and integrated properly.

What is agentic AI in healthcare?

Agentic AI refers to AI systems that can act with a degree of autonomy to complete multi-step tasks, rather than just answering a single prompt. In healthcare that means systems that can help coordinate care across specialists, manage complex insurance authorizations, and pre-screen patients before a visit, taking actions across systems while keeping a human in the loop for clinical safety. It is an emerging trend that builds on RPA and AI to automate whole workflows, not just steps.

What do these trends mean for healthcare software?

They set the design baseline. New healthcare software should be built for interoperability from day one with FHIR-based APIs, designed for privacy and HIPAA-grade security throughout, and architected to treat AI and connected-device data as core rather than add-ons. It should plan for integration with electronic health records and data exchange frameworks, and keep a human in the loop wherever AI touches clinical decisions. Getting these foundations right is what makes a system providers will actually adopt.

Kanika Mathur

Head of Service Delivery, Resourcifi

I am Kanika Mathur, Head of Service Delivery at Resourcifi. I lead delivery on healthcare software builds, where interoperability, privacy, and now AI shape every architecture decision. The trends and implications in this guide are the ones our healthcare engineers design around on real client systems, refined across hundreds of projects since 2017.

Resourcifi on LinkedIn →

Sources

HL7, FHIR (the standard for healthcare data exchange, R4 and R5).
US ONC, TEFCA and USCDI (national interoperability framework).
US ONC, National Trends in Hospital and Physician Adoption of EHRs (96% of non-federal acute care hospitals and 78% of office-based physicians, 2021).
US ONC ASTP, Health IT-Enabled Patient Engagement Capabilities Among US Hospitals, Data Brief 79 (70% of hospitals enabled FHIR app access in 2024).
CDC NCHS, Telemedicine Use Among Office-based Physicians in 2021 and 2024 (80.0% in 2024, 86.5% in 2021, 15.4% in 2019).
Rock Health, 2024 year-end digital health funding overview (10.1 billion dollars across 497 deals, AI-enabled at 37%).