Frontline care teams in 2026 face a paradox: they have record-level digital connectivity at their fingertips, yet persistent gaps in actionable clinical information at the bedside. To improve outcomes and make hospital-at-home and other community models safe and scalable, health systems must move interoperability beyond document exchange. They need to create a usable intelligence layer that delivers context, timeliness, and workflow-embedded decision support. This transformation is essential for enhancing patient care in these settings.
Interoperability’s care problem, stated plainly
Policy wins and vendor advances have made electronic records vastly more shareable. Federal reports indicate that a majority of U.S. hospitals now participate in multiple domains of interoperable exchange, and the adoption of Application Programming Interfaces/Fast Healthcare Interoperability Resources has surged. Clinicians still struggle to get a complete view of a patient’s condition during critical times, such as emergency transfers, post-acute handoffs, and home care for acute issues. When they miss important context, it can lead to tests being repeated, unsafe transfers, and avoidable hospital admissions.
This gap matters for care. Emergency departments facing boarding and inpatient crowding are making triage and transfer decisions without access to full cross-continuum data; the result is delayed care and poorer patient outcomes. Recent analyses linking Emergency Department boarding and transfer acceptance show how operational strain compounds clinical risk.
Why the Care Section Should Care
From the perspective of nurses, therapists, and Emergency Department physicians, interoperability typically fails in three ways that directly harm patients:
Lack of clinical context
Integrated records often deliver documents rather than curated facts. But vital medication changes or recent functional assessments can get buried in PDFs and lengthy notes. Studies of transitions between nursing homes and Emergency Departments document these missing pieces as core drivers of unsafe transfers.
Latency and format mismatch
Data that arrives hours after a change or as an incompatible code set cannot prevent a repeat test or inform an urgent decision. Real-time analytics and decision support tools, when properly fed, reduce unnecessary diagnostics and improve timeliness; conversely, static exchanges do not.
Workflow friction
Clinicians will not adopt systems that increase cognitive load. Interoperability that merely aggregates data without integrating into the Electronic Health Record workflow or role-based views often becomes “more noise.” Industry surveys indicate that buyers are increasingly prioritizing clinician usability and measurable impact over raw connectivity.
Three Capabilities That Change Care Delivery
Contextualized summaries tailored to role and scenarioCare teams don’t want full longitudinal dumps. They want prioritized, short summaries. For example, medication changes in the last 48 hours and a functional baseline are a necessity rather than a preference. Not to mention recent fall or infection flags.
Intelligence-layer tools normalize terminology across settings (Skilled Nursing Facility, home, and ambulatory) and surface critical items upfront, reducing cognitive triage time for Emergency Department physicians and receiving teams.
Research on transitional care indicates that clear communication about key areas, such as medications, goals, and functional status, helps prevent unsafe transfers and informs more informed decisions regarding patient care.
Real-time decision enablement and risk predictionInteroperability should provide real-time support for decisions and predictions about patient risks, such as chances of health decline, readmission, or medication side effects. When predictive AI and Clinical Decision Support are integrated into the Electronic Health Record (EHR) using standard and timely data, studies show that hospitals can more effectively detect health declines and make better operational decisions. Hospitals that use predictive analytics report growth in AI tools integrated with EHR, along with early successes in scheduling, triage, and preventing readmissions.
Full-journey visibility across acute, post-acute, and homeAs hospital-at-home programs and partnerships for post-acute care grow, organizations that understand the entire patient journey can safely move care to less expensive settings. This understanding includes factors such as hospital beds, vital signs, recent activities in skilled nursing facilities, and the availability of caregivers. Federal reviews of hospital-at-home programs have shown that when care is coordinated between different settings and backed by centralized monitoring and data sharing, patients experience lower mortality rates. Additionally, these programs result in reduced readmission rates.
Concrete Care-Focused Business Outcomes To Measure
Health systems must stop treating interoperability as a compliance project and start measuring clinical outcomes tied to the use of information. Key metrics that correlate tightly with patient safety and cost in 2026 include:
Avoidable Skilled Nursing Facility to Emergency Department Transfers
Some patients are sent from skilled nursing facilities to emergency departments unnecessarily because critical clinical information is missing. Tracking these transfers and whether the relevant data was available at the time shows whether interoperability is effectively preventing unnecessary hospital visits. Reducing avoidable transfers improves patient safety and lowers costs.
Emergency Department Dwell Time and Transfer Acceptance Rates
Dwell time measures the duration a patient spends in the emergency department before being admitted, discharged, or transferred. Transfer acceptance rates indicate how often another hospital or facility agrees to take a patient. Complete and timely information allows care teams to make faster decisions, reducing crowding, delays, and operational strain.
Hospital-at-Home Escalation Rates and 30-Day Readmissions
Hospital-at-home programs care for patients in their own homes, rather than in traditional hospital settings. Escalation rates measure the frequency at which home-based patients require urgent hospital care, while 30-day readmissions measure the rate at which patients return to the hospital within a month. Full cross-continuum visibility of patient information helps prevent complications and reduces both escalations and readmissions.
Clinician Time Spent Reconciling Records
Clinicians spend a significant amount of time manually gathering and verifying patient data from multiple sources. Measuring the time spent reconciling records per patient provides a proxy for cognitive burden. Reducing this time allows clinicians to focus more on direct patient care, improving efficiency and satisfaction.
Demonstrating improvements on these measures is the fastest path to sustained funding for intelligence-layer interoperability.
Practical steps for Care leaders in 2026
1. Start with the clinical questions, not the data feeds.Define the three most dangerous decision moments for your organization (e.g., Skilled Nursing Facility transfer, ED disposition, hospital-at-home escalation). Map the specific data elements needed in each moment and require vendors to show those elements surfaced in context during evaluation.
2. Demand standards + and human-centered UX.Standards like Fast Healthcare Interoperability Resources enable transport; buyers must insist that vendors also deliver normalization, terminology mapping, and role-based UX. Vendor pilots should include measurable clinician time savings and error-reduction endpoints, rather than just “connectivity” demonstrations.
3. Pilot with the highest-risk populations and workflows.Run focused pilots in Skilled Nursing Facility-to-Emergency Department pathways, Emergency Department triage, and hospital-at-home admissions where the ROI is easiest to demonstrate. Use a combination of quantitative and qualitative evaluations, such as time-to-decision and clinician satisfaction.
4. Invest in governance that spans care settings.Operational governance must include clinical leaders from acute, post-acute, home-based care, and payer partners to agree on data definitions and performance metrics.
Risks, limits, and realistic expectations
Interoperability alone is not a silver bullet. Prediction models require careful validation and monitoring for bias; data quality remains a significant challenge, particularly among smaller post-acute providers. Moreover, operational strain (including staffing and bed capacity) will blunt the benefits if not addressed in parallel. Recent research into transitions and Emergency Department behavior underscores that technical fixes must be paired with process change.
Conclusion
In 2026, the imperative for care leaders is clear: move interoperability beyond connectivity and into actionable intelligence. Systems that transform shared data into concise, timely, and context-rich information reduce unnecessary transfers, support safer hospital-at-home programs, and enable clinicians to dedicate more time to direct patient care.
Success requires starting with the most critical clinical challenges, measuring outcomes that truly matter to patients and care teams, and holding vendors accountable for delivering usable insights, not just data. Health systems that prioritize intelligence-driven interoperability will not only improve patient safety and operational efficiency but also strengthen clinician confidence and satisfaction.
The future of connected care depends on making data work for clinicians and patients, ensuring every care decision is informed, timely, and safe.
