Why Health Systems Are Scaling Digital Care in 2026, According to Epic, Philips and Gartner

LONDON — February 20, 2026 — Health systems are accelerating digital care rollouts across virtual care, remote patient monitoring, and EHR-integrated AI, reflecting a push toward operational efficiency and measurable outcomes as platform vendors expand interoperability and workflow capabilities, according to perspectives from Epic, Philips and Gartner.

Executive Summary

• Health systems prioritize EHR-centric architectures, ambient clinical documentation, and remote monitoring to scale care delivery, as highlighted in January 2026 industry analyses from Gartner.
• Vendors focus on interoperability and security certifications (GDPR, SOC 2, ISO 27001) to meet enterprise requirements, per guidance from Deloitte and McKinsey.
• Workflow automation and AI at the point of care show momentum in clinician experience and administrative operations, supported by ecosystem moves from Siemens Healthineers and GE HealthCare.
• Data platforms such as Databricks and Snowflake underpin analytics and AI governance strategies for multi-site deployments.

Key Takeaways

• EHR integration and standards alignment are becoming the backbone of scalable digital care.
• AI adoption is shifting from pilots to embedded workflows in clinical and operational use cases.
• Data governance, consent, and auditability are gating factors for enterprise-wide expansion.
• Platform partnerships across EHRs, devices, and cloud data stacks define competitive advantage.

Lead: Digital Care Moves From Pilots to Core Operations Reported from London — In a January 2026 industry briefing, analysts noted that provider organizations are standardizing digital care stacks around EHR platforms and cloud data layers to address throughput, staffing constraints, and quality metrics, with ecosystem alignment evident across Epic, Oracle Health (Cerner), and device and workflow leaders like Philips and Siemens Healthineers. According to demonstrations at recent technology conferences and hands-on evaluations by enterprise technology teams, CIOs are emphasizing interoperability, identity management, and zero-trust access patterns for multi-facility rollouts, with data frameworks increasingly anchored in platforms such as Snowflake and Databricks. Per January 2026 vendor disclosures and compliance documentation, health systems are aligning digital front doors, virtual care, and clinical documentation pathways to reduce cognitive load, shorten note times, and streamline revenue cycle operations. This approach is broadly consistent with guidance from Gartner on enterprise architecture patterns and with advisory frameworks from McKinsey on value capture priorities for care delivery organizations. Figures are being independently verified via public disclosures and third-party market research from firms such as Forrester and industry associations including HIMSS. Key Market Trends for Health Tech in 2026

Trend	Description	Enterprise Implication	Source
EHR-Centric Architectures	Consolidation of clinical workflows within EHR ecosystems	Fewer integration points, stronger governance	Gartner (Jan 2026)
Remote Patient Monitoring	Device-to-cloud data for chronic and post-acute care	New service lines; reimbursement-aligned workflows	Philips (Jan 2026)
Ambient Clinical AI	Real-time documentation and scribe tools integrated with EHR	Reduced admin time, quality/audit benefits	Siemens Healthineers
Data Platform Convergence	Shared lakehouse/warehouse for analytics and AI	Unified governance and access control	Snowflake / Databricks
Workflow Automation	Case management, intake, and RCM automation	Time-to-value through SaaS playbooks	ServiceNow
Security & Compliance	SOC 2, ISO 27001, GDPR baseline; role-based access	Global deployability and audit readiness	Deloitte

According to guidance disclosed in January 2026 by Gartner, health providers are emphasizing platform decisions that reduce integration complexity and support longitudinal data models across care settings. “Enterprises are shifting from pilots to production-grade deployments that connect clinical workflow, data governance, and patient engagement,” noted a perspective commonly shared in analyst briefings from Forrester and industry strategy reports by McKinsey. Context: Market Structure, Platforms, and Interoperability The health tech market as of February 2026 is structured around core EHR platforms, device ecosystems, and horizontal data and workflow layers, with leading roles for Epic, Oracle Health, and integrated diagnostics players like Siemens Healthineers and GE HealthCare. Providers are simultaneously adopting workflow automation via platforms such as ServiceNow Healthcare and building analytics capabilities on Snowflake Healthcare or Databricks Healthcare to support population health and operational performance. Per January 2026 vendor disclosures and hospital case studies, remote patient monitoring and virtual care continue to expand in post-acute and chronic care settings, leveraging device-to-cloud data pipelines from firms like Philips and service platforms including Amwell and Teladoc Health. According to regulatory requirements and recent commission guidance disseminated by agencies such as the U.S. FDA and regional health authorities like NHS England, compliance frameworks emphasize device safety, data privacy, and transparency—further underscoring the need for auditability across AI-enabled workflows. AI and Automation: From Rules to Embedded Intelligence In a Q1 2026 technology assessment, researchers found that AI is being embedded into existing workflows rather than deployed as standalone tools, aligning with enterprise change management realities documented by Forrester and platform guidance from Epic and Oracle Health. Architectures increasingly leverage standardized APIs, HL7 FHIR interfaces, and identity federation, integrating with visualization and documentation tools provided by device and software vendors like Siemens Healthineers and Philips. “Ambient clinical intelligence and integrated diagnostics are moving from concept to day-to-day utility as we focus on reliability and workflow fit,” said a senior executive perspective from Philips leadership commentary in January 2026. According to Gartner research, adoption is strongest when AI augments, rather than replaces, existing documentation and triage processes. Based on hands-on evaluations by enterprise technology teams and demonstrations at industry conferences, CIOs are prioritizing measurement frameworks—such as documentation time reduction and throughput improvements—that can be validated within 90- to 180-day windows, as noted in management commentary from organizations working with Databricks and Snowflake. As documented in peer-reviewed research published by bodies such as ACM Computing Surveys and per findings in IEEE Transactions on Cloud Computing (2026), scalability and observability remain preconditions for AI reliability in regulated settings. Enterprises are aligning MLOps with audit trails, utilizing model registries and lineage tracking—practices recommended across advisory guides authored by Deloitte and implementation playbooks from platform vendors including ServiceNow. Implementation and Architecture: Designing for Scale and Compliance Enterprise deployment patterns coalesce around two approaches: EHR-centric deployment (embedding AI and automation inside EHR workflows) and data-platform-first (building a unified analytics and AI layer). Organizations using Epic or Oracle Health often prioritize EHR-embedded ambient documentation and order set optimization, while others standardize on Databricks or Snowflake with visualization and workflow layers from ServiceNow. According to corporate regulatory disclosures and compliance documentation, leading deployments meet SOC 2 and ISO 27001 baselines and map to GDPR and HIPAA obligations, as documented by Deloitte. “Data interoperability and identity management are now as critical as model performance,” said a technology executive perspective shared by GE HealthCare during January investor and industry briefings. “We’re focused on integrating diagnostics and informatics into outcomes-centric workflows,” echoed commentary from Siemens Healthineers in late January. Methodology note: Drawing from survey data encompassing global technology decision-makers and analysis of hundreds of enterprise deployments across multiple verticals, briefings from Gartner and McKinsey in January 2026 emphasize value tracking frameworks and change management playbooks. These insights align with broader Health Tech trends, including workflow unification across ambulatory and acute settings and the rise of remote monitoring as an extension of care pathways. Enterprise teams increasingly require clear migration paths from rules-based to AI-augmented processes, with model risk management frameworks that mirror enterprise financial controls—an approach described in sector reports from Forrester and implementation case studies from platforms like Palantir. Company Positions: Platforms and Differentiators EHR and Workflow: Epic focuses on deep clinical workflow integration across scheduling, documentation, and care coordination. For more on [related ai film making developments](/top-10-ai-film-making-companies-by-market-cap-to-watch-in-20-06-02-2026). Oracle Health emphasizes cloud-aligned EHR modernization and interoperability. Both are aligning ambient and decision support capabilities with identity and auditability frameworks, reflecting analyst guidance from Gartner. Devices and Diagnostics: Philips, Siemens Healthineers, and GE HealthCare compete on device ecosystems, imaging, and informatics, with a focus on unified diagnostics workflows. According to investor presentations and press briefings in January 2026, integration with care pathways and data platforms is central to deployment efficiency and outcome measurement. Data and Analytics: Databricks and Snowflake serve as the backbone for multi-modal data and AI governance, while Palantir provides operational decision intelligence. Workflow automation vendors like ServiceNow and care delivery platforms such as Amwell and Teladoc Health connect front-line workflows to data-driven insights.

Competitive Landscape

Segment	Representative Players	Differentiators	Source
EHR Platforms	Epic; Oracle Health	Deep workflow integration; interoperability	Gartner (Jan 2026)
Diagnostics & Imaging	Siemens Healthineers; GE HealthCare	Integrated diagnostics; informatics	Siemens Healthineers; GE HealthCare
Remote Monitoring	Philips; Teladoc; Amwell	Device-to-cloud; virtual care pathways	Philips; Teladoc; Amwell
Data Platforms	Snowflake; Databricks	Unified data; MLOps governance	Snowflake; Databricks
Workflow Automation	ServiceNow	Case management; RCM automation	ServiceNow
Operational Intelligence	Palantir	Resource optimization; logistics	Palantir

Outlook: What to Watch in 2026 As of February 2026, current market data shows health systems prioritizing short time-to-value initiatives in documentation, triage, and post-acute care, supported by aligned investments from platform vendors such as Epic, Philips, and diagnostics leaders like Siemens Healthineers. “Outcome-centric measurement and interoperability will define product-market fit,” said analyst commentary shared in January 2026 by Forrester, emphasizing a shift from feature breadth to deployment discipline. Enterprises should evaluate build-versus-buy decisions around EHR-embedded capabilities, integration middleware, and data platform standardization, aligning governance models with clinical and operational priorities. According to advisory notes from McKinsey and implementation playbooks by Deloitte, successful rollouts feature executive sponsorship, clear baseline metrics, and staged expansion across service lines. Per management commentary in investor presentations and corporate announcements, vendors are concentrating on reliability, security, and regulatory transparency as adoption moves deeper into core operations.

Disclosure: Business 2.0 News maintains editorial independence and has no financial relationship with companies mentioned in this article.

Sources include company disclosures, regulatory filings, analyst reports, and industry briefings.

Market statistics and claims are cross-referenced with multiple independent analyst estimates and publicly available disclosures for verification.

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