For decades, healthcare has operated largely as a reactive system — treating patients after symptoms appear and documenting care after it is delivered.
That model is now beginning to shift. Advances in AI and emerging technologies are enabling a new paradigm: one that is proactive, continuous and increasingly intelligent. As health systems move beyond siloed, episodic and facility-bound care, they are beginning to deliver care that extends across the full patient journey.
This emerging model, often referred to as “programmable care,” marks a fundamental change in how care is designed, delivered and continuously improved. To explore what this shift looks like in practice, Becker’s Healthcare spoke with Kushboo Goel, head of healthcare solutions and consulting at Neurealm.
What programmable care means — and how it reshapes patient experience
While the term “programmable care” is still emerging in healthcare, it reflects a growing shift toward care models that are continuously informed by data and dynamically adjusted in real time.
Ms. Goel described programmable care as a significant departure from traditional models. Instead of reacting to acute events, health systems proactively anticipate patient needs using predictive tools. Rather than pausing between periodic visits, care is delivered continuously across home, clinic and hospital settings. And instead of relying on static workflows updated through periodic IT cycles, care pathways evolve in real time based on incoming patient data.
The potential impact of programmable care on the patient experience is significant. For instance, individuals with heart failure who previously were monitored only during in-person clinic visits can now have their vitals monitored continuously through wearables and IoT sensors. Based on the real-time data that is collected, predictive AI can flag early deterioration signals, such as weight increases or decreases in physical activity — even before patients feel symptoms.
As part of programmable care, agentic workflows analyze a patient’s data, automatically escalate notifications to care teams, adjust care plans and schedule outpatient check-ins.
According to Ms. Goel, these actions and interventions occur before a visit to the emergency department is needed, helping to prevent it altogether. With programmable care, the patient experience can be designed, deployed and continuously improved, like software—hence the term programmable
From ‘information processor’ to ‘strategic clinical decision-maker’: redefining the provider role
On the provider side, AI and programmable care liberate clinicians from cognitive load and administrative burden. Instead of spending time on documentation, providers can focus where it matters most: clinical decision-making and caring for patients.
To enable the vision of programmable care for health systems, Neurealm works across three key pillars—agentic workflows, physical AI and platform architecture.
Physical AI, such as ambient listening, captures and structures clinical notes, while predictive models identify patients who need immediate attention. Agentic workflows handle routine coordination tasks, like prescription refills, test orders and referral scheduling. The end result is that physicians spend less time on administrative tasks and more time on high-priority, high-acuity patients.
“With programmable care, the clinician’s role evolves from information processor to strategic clinical decision-maker, spending more time on high-value patient interactions and less time on administrative overhead,” Ms. Goel said.
For care teams, programmable care represents a more fluid, proactive operating model. Rigid handoffs between inpatient, outpatient and home care give way to continuous care. The team structure also becomes more dynamic, as the right person with the right information is engaged at the right moment, regardless of care setting.
Creating programmable care pathways — one integrated health system’s approach
Programmable care requires a unified data platform. Ms. Goel explained how this must include an orchestration layer that sits above the data and translates data-driven insights into coordinated, real-time actions across clinical, operational and administrative workflows.
Another key element is real-time analytics. These support early intervention triggers, dynamic care plan adjustments and proactive patient engagement.
“A diabetic patient’s care team, for example, will get a prompt when glucose trends shift,” Ms. Goel said. “At the same time, patient engagement messages will go out, and appointments will be adjusted automatically.”
A recent collaboration between Neurealm and a leading North American integrated health system illustrates the power of programmable care pathways in action. The regional health system turned to ambient listening to reduce the administrative burden facing clinicians across its complex, multi-hospital network and return the focus to face-to-face patient care.
Virtually all clinicians (94%) in the system adopted the ambient listening solution and 94% reported reduced cognitive burden and greater job satisfaction. On average, providers saved 10.5 minutes per visit and saw 2.13 more patients per day. In addition, the impact on the patient experience was positive, with clinicians spending 6.63 fewer minutes of screen time per exam.
The result: optimized clinical workflows, improved work-life balance for clinicians and higher provider retention rates.
How to overcome hurdles in enterprise deployment
As health systems transition from pilots of programmable care into enterprise solutions, Ms. Goel noted teams frequently encounter technical and organizational barriers. The first barrier is data fragmentation, since the many point solutions in healthcare tend to generate data in silos. Without a unified, interoperable data fabric, scaling becomes impossible.
Workflow integration gaps are another challenge. When technologies require clinicians to change workflows, it often results in slow user adoption. The most successful deployments embed intelligence into existing workflows and systems.
Governance and organizational readiness are also essential. Without transparent, explainable AI that includes clear human-in-the-loop accountability, user acceptance often stalls at the pilot stage.
Health systems that successfully scale programmable care invest equally in change management, training and governance structures, as well as technology.
Advancing foundational capabilities and cultural change
As healthcare leaders explore programmable care models, they must address the infrastructure that supports interoperability, real-time data, and security and compliance.
Cultural shifts are also imperative, particularly when it comes to building trust and managing the pace of organizational change. Trust is multi-faceted, encompassing clinical, patient and systemic dimensions. On the systemic side, Ms. Goel emphasized that accountability frameworks must align with the responsibilities assigned to AI agents.
“Health systems need clear policies defining where human judgment is required, how AI errors are detected and corrected, and how continuous learning systems are governed,” she said.
She also urged leaders to consider that technologies are scaling faster than most health systems can absorb them. Over the next five years, the organizations that will lead will be those that invest equally in people, processes and platforms, not just in AI capabilities.
“Health systems that embrace programmable care will benefit from continuous improvement at the speed of software,” Ms. Goel said. “Those that don’t risk being outcompeted on every dimension that matters — cost, quality and patient experience.”
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