From Healthcare Priorities to Real-World Validation

What this refers to
Digital health & tech-enabled tools that help extend care beyond traditional settings—supporting virtual-first workflows, ongoing support, and reliable care across distance and time.

Typically supports
Access expansion, continuity of care, home-based care, specialty reach, and patient self-management.

What this looks like in practice

• Virtual care workflows with escalation, follow-up, and care team routing

• Remote support for chronic care, rehab, and recovery outside the hospital

• Patient-facing tools that help people understand trends and manage goals over time

What it is not
Standalone video visits, basic portals, or tools that don’t connect to real care workflows.

What this refers to

AI-enabled tool and data systems that connect care activity, data, and workflows across settings—so teams can act on real-time signals, route work intelligently, and reduce administrative friction inside daily operations.

Typically supports
Transitions of care, cross-system referrals, integrated care, clinician time savings, burnout reduction, cycle-time improvement, and closing care gaps.

What this looks like in practice

• Real-time signals that trigger follow-ups and handoffs (discharge, missed visit, care gap)

• Constraint-aware routing based on urgency, capacity, and available services

• Documentation and task support that drafts notes and surfaces action items

• Automation for intake, referral prep, prior auth, and handoffs—with human approval

• Forecasting and scheduling that adapts to demand and capacity shifts

• Systems that coordinate care across teams and sites—tracking what’s happening, anticipating what’s next, and routing work so patients don’t get lost between

What it is not
Data integration alone or generic task trackers that don’t fit real workflows.

What this refers to
Smart sensing & device-enabled approaches (i.e. wearables and lightweight sensors) that capture health signals through wearables or lightweight sensors—and turn them into useful insights over time for both care teams and patients.

Typically supports
Rehab and recovery, movement/neuro support, safety monitoring, longitudinal engagement, and continuity across settings.

What this looks like in practice

• Next-gen wearables that track fine motor, gait, or tremor change (e.g., a sensor-enabled glove concept)

• Low-friction sensing that supports safety, recovery, and daily function outside clinical settings

• Patient-facing insights that help people spot change earlier and manage their own goals

• Signal summaries that stay useful even with limited connectivity

What it is not
Standalone consumer gadgets, or devices positioned as definitive clinical tests without appropriate oversight.

What this refers to
AR/VR tools that strengthen training and remote support—so teams can build skills faster and extend specialty support without always needing someone on-site.

What this looks like in practice

• Simulation training for high-risk workflows without disrupting clinic operations

• AR-guided support for procedures or equipment setup, with real-time remote expert backup

• Immersive rehab or therapy support that adapts as patients progress over time

Typically supports
Workforce training, remote specialty support, care standardization, rehab, and patient education across distributed settings.

What it is not
One-off VR experiences, marketing demos, or entertainment-first tools that don’t integrate with care pathways or staff workflows.

What this refers to
Advanced modeling and simulation that helps leaders test decisions before rollout—so programs, pathways, and operations improve with fewer unintended consequences.

Typically supports
Population health strategy, pathway design, care management programs, capacity planning, and performance improvement.

What this looks like in practice

• Digital twin / “what-if” simulation to test changes in access, capacity, and care delivery

• Scenario modeling for prevention programs, outreach strategies, and care management approaches

• Pathway modeling across populations (who benefits from what next, and when)

What it is not
Static dashboards, retrospective reporting only, or analytics that can’t be tested in a small, time-bound pilot.

What this refers to
Applied next-generation computing for complex health system decisions—when the number of variables, constraints, and tradeoffs makes standard approaches too slow or too simplified.

Typically supports
Precision medicine, population health strategy, care pathway design, care management programs, access planning, capacity optimization, and system-level performance improvement.
This includes high-performance computing (HPC) today, quantum-inspired methods in practice, and quantum-ready approaches as the field matures.

What this looks like in practice

• Modeling and optimizing precision medicine treatment pathways across populations (who benefits from what next, and when)

• “What-if” simulation for prevention programs, capacity shifts, and care delivery changes before rollout

• Complex planning like access, scheduling, routing, and resource allocation across distributed settings

• Finding patterns in large, messy real-world health data to improve stratification, diagnostics, and outreach at scale

What it is not
 A “quantum computer product,” routine reporting dashboards, or diagnostic tools marketed for individual patient decisions without appropriate validation.