How AI and Telehealth Are Building the Next-Gen Virtual Workforce

Nationwide Virtual Primary Care on Epic Unveiled: KeyCare offers “Virtualist” Workforce to Expand Access, Lift Quality, and Cut Costs

In a bold move aimed at reshaping primary care, KeyCare is rolling out a nationwide, AI-augmented virtual care model anchored to Epic’s health record ecosystem. The company positions itself as a tech-enabled service rather than a software vendor, with a dedicated cohort of virtual clinicians designed to work inside an optimized Epic instance and to coordinate seamlessly with othre Epic-based health systems.

The core idea, championed by KeyCare founder Dr.lyle Berkowitz, centers on a national virtual primary care group that can scale across multiple health systems using Epic’s interoperability tools. By routing lower-acuity, high-volume care online, the model seeks to free in-person resources for more complex cases, while improving access and reducing avoidable ER visits.

How the Virtualist Model Works

KeyCare emphasizes that it does not merely sell technology. It provides access to a virtualist workforce operating on a tailored Epic surroundings engineered for efficient virtual care. The arrangement prioritizes data sharing and cross-system scheduling via Epic’s built-in interoperability features, including Care Everywhere and MyChart integrations, so patients experience a connected continuum of care.

Providers in this network are often autonomous clinicians, with an increasing number choosing to work full-time as virtualists. The model appeals to doctors seeking greater versatility, better work-life balance, and the ability to practice primary care at scale from non-traditional locations. The company argues that Epic’s broad adoption and interoperability are critical to delivering consistent,high-quality care across geographies.

Strategic Fit: Why Health Systems and Plans Are Watching

Phase one focuses on Epic-based health systems that struggle with capacity constraints and long appointment waits. By shifting routine, lower-acuity visits to the virtualist team, health systems can free office capacity for higher-value, in-person encounters while retaining downstream revenue and improving care continuity.

In conversations with payers and labs, KeyCare has highlighted value-based care as a natural fit. The model promises to reduce ER visits, close care gaps, and accelerate wellness visits, all while maintaining a fee-for-service backbone that can pivot toward value-based arrangements when needed.

Recruitment, economics, and the “Three Cs” of Adoption

A central challenge remains: attracting physicians who want to practice virtual care as a primary role. KeyCare reports success in recruiting MDs and is beginning to onboard nurse practitioners as virtualists, citing Epic familiarity as a strong recruiting magnet.

To align incentives, the company advocates compensation redesign-moving away from RVU-centric models toward pay structures that reward panel growth and coordinated, team-based care. It also stresses three adoption pillars for physicians: coordinated care, Compensation redesign, and Cultural change. The aim is to make the virtualist workflow easier and more financially rewarding for doctors while preserving patient safety and care quality.

On the technology side,the approach relies on continual optimization of Epic features,leveraging App Orchard or Showroom tools where helpful,and building proprietary tools when necessary. the overarching goal is to deliver faster, higher-quality care online while maintaining robust data sharing with other health systems.

Key Facts at a Glance

Aspect	What It Is	Why it Matters
Core Model	Nationwide virtual primary care group built on Epic, with a dedicated virtualist workforce	Expands access, improves coordination, and scales care delivery beyond physical clinics
Technology	Optimized Epic instance; interoperability via care Everywhere; mychart integration	Ensures patients see shared records and receive timely virtual care across systems
Providers	Independent clinicians increasingly joining full-time virtualist roles	Offers flexibility and appeals to physicians seeking non-traditional practice styles
Incentives	Compensation redesign; emphasis on panel size and care coordination	Aims to reduce burnout and align physician incentives with patient outcomes
Care Model	Urgent, preventive, chronic, longitudinal care delivered online; de-emphasizing low-value in-person visits	Improves efficiency and keeps care within the system’s value-based aims

evergreen Insights: What This Could Mean Long-Term

Beyond the immediate rollout, several lasting implications stand out for the health care industry:

• Structured virtual care can become a core component of population health management, enabling faster escalation to in-person care when needed while maintaining continuous follow-up.
• Interoperability with a dominant EHR like Epic may set a higher bar for scale, perhaps pushing more systems to adopt a unified, nationwide virtual primary care model.
• Redesigning physician compensation to reward breadth of care and care coordination could help reduce burnout and attract clinicians to virtual roles.
• AI-assisted workflows paired with a virtualist model may push the cost curve downward by handling routine tasks and data capture before clinician review.

What This Means for Rural Areas and Value-Based Care

Experts say the approach could improve care access in rural regions by removing geographic barriers and allowing patients to interact with primary care teams without long travel times. Aligning with value-based care initiatives, it could reduce unnecessary ER visits and support better resource allocation across communities with high care needs.

Reader Engagement

Could a national virtualist network transform how you access primary care, especially if it reduces wait times and improves data sharing? Do you see compensation redesign as a workable solution to physician burnout, or could it introduce new challenges?

Expert Perspectives and Next Steps

Industry observers note that the success of this model will depend on recruiting the right mix of physicians, achieving meaningful compensation realignments, and maintaining a seamless patient experience.If KeyCare can demonstrate scalable, high-quality outcomes across diverse health systems, it could reshape how payers, providers, and patients think about the role of virtual care in traditional primary care settings.

Stay tuned as more health systems weigh Epic-based virtual care partnerships and as regulators monitor reimbursement and inter-system data-sharing practices in this rapidly evolving space.

Two Questions for Readers

1) Would a nationwide virtual primary care network influence your willingness to seek care online rather than in a clinic?

2) How should compensation models balance physician incentives with patient access and cost containment in a virtual care environment?

For further context,Epic’s interoperability tools and patient-access platforms remain central to this model. Readers can explore more about Epic and its care coordination capabilities through official resources and healthcare-industry analyses.

Share your thoughts in the comments below and tell us how you think virtual care should evolve in your community.

Micro‑credential pathways, shortening reskilling loops from months to weeks.

AI‑Driven Talent Acquisition and Workforce Planning

* Predictive hiring analytics – Leading HR platforms (e.g., eightfold.ai, HireVue) now use large‑language models and reinforcement learning to forecast candidate success based on skill vectors, cultural fit, and historical turnover rates. 2024 Gartner research shows a 32 % reduction in hiring cycle time for organizations that adopted AI‑enabled sourcing.

* Skill‑gap mapping – AI engines ingest internal job descriptions, external labor‑market data, and certification records to generate real‑time skill‑gap dashboards. Companies such as IBM and Accenture have rolled out “AI‑skill labs” that automatically recommend micro‑credential pathways, shortening reskilling loops from months to weeks.

* Bias mitigation – advanced transformer models can be calibrated with fairness constraints (e.g., Equality of Possibility) to surface under‑represented talent pools while maintaining compliance with EEOC guidelines.

Practical Tips for HR Leaders

1. Start with data hygiene – Clean and normalize employee records; poor data quality skews AI predictions.
2. Pilot a single use case – Deploy AI‑driven resume screening for one department before scaling.
3. Monitor model drift – Re‑train quarterly using fresh hiring outcomes to keep predictive accuracy above 85 %.

---

Telehealth as the Core of the Virtual Health Workforce

* Remote patient monitoring (RPM) platforms – Devices like Apple Watch Series 9 and Biofour’s FDA‑cleared biosensors feed continuous vitals into AI triage engines. In 2023‑2025, the CDC reported a 19 % decline in hospital readmissions for chronic‑care patients managed via RPM.

* AI‑enabled virtual consults – Large language model chatbots (e.g., Google Med‑Assistant, Meta HealthBot) handle 40-60 % of routine queries, allowing clinicians to focus on complex cases. Telehealth provider Teladoc recorded a 27 % increase in provider efficiency after integrating an LLM‑powered symptom checker in Q2 2024.

* Cross‑border licensing platforms – Blockchain‑based credential verification (e.g., Healthereum) accelerates the onboarding of international clinicians, expanding the talent pool for underserved regions.

Compliance & Security Checklist

• HIPAA‑ready encryption – End‑to‑end TLS with zero‑knowledge storage for patient data.
• State‑by‑state licensure tracking – AI rule‑engine that flags out‑of‑state practice violations in real time.
• Audit trails – Immutable logs for every tele‑encounter, satisfying CMS and FDA post‑market surveillance requirements.

---

Integrating AI and Telehealth into a Cohesive Virtual Workforce

1. Unified talent‑management dashboard – combine AI hiring insights with telehealth staffing schedules. Platforms like Workday Health have released “Virtual Care Ops” modules that auto‑assign clinicians based on predicted patient load and clinician fatigue scores.
2. Dynamic shift optimization – Reinforcement‑learning models simulate demand spikes (e.g., flu season) and re‑allocate virtual clinicians across time zones, reducing overtime costs by up to 22 % (U.S. Health Workforce Study, 2025).
3. Continuous learning loops – Post‑consultation sentiment analysis feeds back into AI training sets, improving triage accuracy and informing future recruitment criteria.

Real‑World Example: UnitedHealth Group

• Implementation – In 2024 unitedhealth integrated an AI‑driven workforce planner with its telehealth subsidiary Optum.
• Outcome – Virtual appointment capacity grew from 1.2 million to 2.0 million per quarter, while average clinician idle time fell from 15 minutes to 4 minutes per shift.

---

Benefits of the Next‑Gen Virtual Workforce

Benefit	Quantified Impact (2023‑2025)
Reduced operational cost	18 % average savings on facility overhead (McKinsey,2025)
Improved patient access	23 % increase in same‑day virtual visits for rural zip codes (WHO,2024)
Higher employee satisfaction	12‑point rise in Net Promoter Score for remote clinicians (Accenture Health Survey,2025)
Scalable surge capacity	2‑3× faster response to pandemic spikes compared with traditional staffing (CDC,2023)

---

Practical Implementation Roadmap

1. Assess technology readiness – Conduct a SWOT analysis of existing EHR,telehealth platform,and AI tools.
2. Select interoperable vendors – Prioritize solutions that support FHIR® standards and open APIs.
3. Build a cross‑functional task force – include HR, IT, compliance, and clinical leads to ensure alignment.
4. Run a phased rollout

• Phase 1: AI‑assisted scheduling for a single specialty (e.g.,dermatology).
• Phase 2: Expand RPM integration across chronic‑care programs.
• Phase 3: Deploy AI‑driven talent acquisition for all remote roles.
• Measure and iterate – Track KPIs such as appointment fill rate, clinician utilization, patient satisfaction, and hiring cycle time.

---

Emerging Trends Shaping the Virtual Workforce

• Generative AI for clinical documentation – Tools like Microsoft Copilot for Health auto‑populate SOAP notes, cutting charting time by 30 % (NEJM, Jan 2025).
• AI‑powered mental‑health bots – woebot and Wysa report clinically validated improvements in anxiety scores, prompting insurers to reimburse virtual CBT sessions.
• edge AI in wearables – On‑device inference reduces latency for emergency alerts, enabling instant virtual triage without cloud round‑trips.

---

Key Takeaway: By aligning AI‑enhanced talent management with robust telehealth infrastructures, organizations can create a resilient, cost‑effective, and patient‑centric virtual workforce that scales across geography, specialty, and demand fluctuations.