The following is a guest article by Jonathan Shoemaker, CEO at ABOUT Healthcare
For a time period that seems like just about forever, the healthcare industry has been investing in improving interoperability.
In the early days, Regional Health Information Organizations and HL7 were supposed to get us to interoperability. Then, “Meaningful Use” and the HITECH Act were going to do it. Today, we’ve got CMS Aligned Networks, TEFCA, and information-blocking-rule enforcement.
Despite all this “progress,” simply moving information between systems has not been enough.
As a result, the industry’s prevailing concept of “interoperability” feels like it’s stuck in the early 2000s. We are still largely defining success as “getting the right data to the right place at the right time.” Today, that should merely be table stakes. The important consideration is whether the most vital information is made relevant and actionable within the care process.
Ultimately, the future of interoperability is not about connecting more systems. It is about weaving intelligence directly into the systems clinicians already use, so insights turn into actions at the moment of care.
This next evolution of interoperability is represented by a decision layer woven directly into native electronic health records (EHR) workflows. Instead of relying solely on standalone applications or dashboards, intelligent systems surface insights and recommended actions at the point of care and coordination.
By integrating natively and augmenting, not replacing, EHRs, this approach enables proactive, automated decision-making that improves patient access, throughput, and experience.
Reframing Interoperability: Insights that Drive Clear Actions
Health systems have more data than at any point in history. Yet decision-making has not become faster or easier. In many cases, it feels heavier.
Part of the reason is structural. EHRs were designed primarily for clinical documentation and billing. They function extremely well as digital claim processors, but they were not designed to be intelligence engines first. Layer onto that a deeply cautious culture around data governance, patient data privacy, and patient safety. Add tight controls on AI experimentation. Also consider the reality that most health systems operate on thin margins and do not employ large data science teams.
The result is a paradox: More data volume, but not more decision velocity.
For years, the industry’s response has been to aggregate data into dashboards. Build another visualization layer and add more reports. The expectation was that if we present enough information, humans would connect the dots and act.
Instead, we have created fractured product stacks and data fiefdoms. Clinicians toggle between multiple screens. Leaders reference multiple dashboards. Valuable insights live outside the primary workflow.
If the EHR is where clinicians spend their day, pulling them into separate tools disrupts concentration and care flow. They should not have to hunt across systems to determine what matters in the moment.
This is where interoperability must evolve. Data exchange is the baseline. The next phase is intelligence integration. Insight must be layered on top of exchanged data, tightly integrated into workflow, and expressed in clear, action-oriented terms.
True interoperability is not just moving information from System A to System B. It is surfacing the most relevant information and predictive and prescriptive recommendations at the exact moment a decision needs to be made.
Case in Point: The Impact of Better Interoperability on ED Observation Status
Consider a common operational challenge in the emergency department: Patients placed under observation status frequently accumulate services and clinical indicators that qualify them for inpatient admission. The data points exist, and the services are documented, but no one may notice in real time that the threshold has been crossed.
This is the classic forest-versus-trees problem. Clinicians are focused on the patient in front of them, while case managers are juggling multiple charts. Patterns that unfold over hours can be difficult to spot without assistance.
An intelligence layer operating within the workflow can continuously monitor cumulative clinical signals in the background. It can detect when the criteria for a status change are met. Most importantly, it can prompt the responsible clinician directly within the native EHR workflow, in real time.
Earlier recognition can accelerate patient movement from observation to inpatient status. That improves care timing. It ensures appropriate reimbursement alignment. It reduces back-and-forth between departments. It minimizes operational friction that so often slows throughput.
Nothing new is being documented. No new data is required. What changes is the ability to see the pattern as it forms and act on it immediately.
The Future of Interoperability: Mesh Intelligence
When the EHR is the platform of record, the objective is not to replace it. The opportunity is to make that platform smarter.
This is where the concept of mesh intelligence comes into play – a network of tightly integrated capabilities that operate within existing workflows, connecting signals across systems and translating them into real-time guidance.
Historically, EHRs have been optimized around documentation and billing. The next evolution of healthcare technology must focus on patient movement and operational decision-making – areas that require visibility across departments, care settings, and roles. That level of coordination cannot be delivered by any single system alone.
Mesh intelligence addresses this challenge by weaving together data signals from across the care environment and translating them into real-time guidance inside the clinician’s workflow. Instead of forcing users to log into another platform, it brings the right information and recommendations to the point where decisions are already happening.
There is also a workforce dimension to this shift. Much of healthcare’s operational knowledge has historically lived in the experience of seasoned nurses, case managers, and coordinators who learned to navigate complex systems over decades. They knew where to click, which reports to run, and how to interpret fragmented information.
As that generation retires, healthcare cannot rely on tribal information alone. New clinicians expect technology to guide them, not slow them down. They are far less tolerant of inefficiency and far more comfortable with intelligent tools that surface insights automatically.
Mesh intelligence helps preserve institutional knowledge by codifying patterns that once existed only in people’s heads. It can accelerate onboarding, support training, and reduce reliance on informal workarounds. Most importantly, it reduces friction by delivering insight directly within the workflows clinicians already trust.
Data is Table Stakes, Decisions are the Differentiator
Healthcare has spent decades focused on connecting systems and exchanging data. That work was necessary, but it was only the first step.
The next era of interoperability will not be defined by how much information moves between systems, but by how effectively that information drives decisions. Health systems need intelligence that operates directly within clinical workflows, where insight can immediately translate into action.
Organizations that succeed will treat data exchange as the baseline and focus instead on delivering real-time, workflow-native guidance that improves patient flow, operational performance, and the clinician experience.
In the end, the true measure of interoperability will not be whether data is accessible. It will be whether the right insight reaches the right person at the right moment – making it easier to deliver the right care, faster.
Jonathan Shoemaker joined ABOUT Healthcare in 2023 as Chief Executive Officer, bringing more than 25 years of health system and information systems experience with a proven track record of transforming and delivering initiatives and solutions that improve healthcare delivery, operations, and growth.
Before joining ABOUT Healthcare, Jonathan was most recently Senior Vice President of Operations and Chief Integration Officer, as well as a member of the Senior Executive team leading Allina Health’s Performance Transformation Office. Before his most recent role at Allina, Shoemaker spent six years as Allina Health’s Chief Information Officer and Chief Improvement Officer. Prior to Jonathan’s tenure at Allina, he held leadership positions at prominent IT & healthcare firms, including NorthPoint Health and Wellness Center, BORN Consulting, and Hennepin County Medical Center.
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