Convergence of Virtual Care & Artificial Intelligence

The synergy behind virtual care and AI in Healthcare needs to be expanded. Virtual Care needs a digital strategy as it will serve as the data pipeline for AI in Healthcare. It will give birth to learning healthcare system

Convergence of Virtual Care & Artificial Intelligence
Ready to Publish
Ready to Publish
Publish Date
Nov 9, 2021
Long Form
Blog Ideas
Video Recording
Unlisted YouTube Video

Artificial Intelligence (AI) has emerged as the technology of our time with the potential to be as disruptive as the discoveries of fire and electricity. Being not only a technology but also a technology enabler, AI has found usage in almost all fields and industries. Artificial intelligence is currently being developed and deployed to solve specialized, specific problems and that is where its commercial success lies. Similarly, in recent years, Virtual Care (VC) has brought about a paradigm shift in care delivery and is increasingly being provided on the same principle as software is delivered in today's age – as a service (SaaS). Termed “Virtual Care as a Service (VCaaS)”, can be distributed on-demand, with pay-as-you-go or direct pay/subscription model utilizing Cloud technology with node and edge enhancement. AI in healthcare will be delivered on a similar Artificial intelligence as a Service (AIaaS) model as well. AI in healthcare needs to fill in the production gap and this is possible with the AlaaS model. The precision of evidence is key to success and a modular approach will bring trust and ease of deployment. Interoperability and information blocking rules will tear down data silos. As-services model thinking will create minimal viable products that can be scaled and deployed, and where outcomes can be measured in real time and reimbursed. As the model evolves both a marketplace and in future platforms will emerge to create a value chain of Virtual Care and AI products in synergy. In this chapter, we will discuss the synergistic relationship of AI and VC in healthcare and its convergence in the form of modular services which will bring exponential disruptive change in healthcare and the realization of healthcare 4.0.
Video preview

This talk and blog is part of the Summit
Held Virtually on 21 & 22 October 2021
This talk will be published in an upcoming book
"Artificial Intelligence in Clinical Medicine (AIICM)"


  • Identify the Problem
  • Digital Transformation
  • Understanding VCaaS Model
  • Understanding AIaaS Model
  • Convergence & Synergy between VCaaS & AIaaS
  • Legal and Regulatory
  • FDA’s role
  • Reimbursement
  • VCaaS and AIaaS in practice (e.g. Stroke)

Identify the Problem

  • Production Gap
    • Proof-of-Concent
  • Data, Data & Data
  • Scaling
  • Trust
    • Precision of Evidence
  • Who will pay for it?

Digital Transformation

Digitization → Digitalization → Digital Transformation
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Understanding VCaaS Model

Virtual Care Continuum

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Data Pipeline

VCaaS is the data-pipeline for AI in Healthcare
Apple Plans Blood-Pressure Measure, Wrist Thermometer in Apple Watch

Virtual Hospital @ Home

Ultimate expression of Virtual Care as a Service:
  • Labs-on-wheel
  • Mobile radiology
  • Telerehab
  • Continuous & remote monitoring

Understanding AIaaS Model

Narrow, problem-specific, Goal Oriented.
  • Moduler
  • Plug & Play
  • Interoperable
  • Integrated with VCaaS
  • Risk
  • Trust
  • Integration
  • Value of Evidence
  • Evidence of Value
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Convergence & Synergy between VCaaS & AIaaS

  • Concentrate on Value exchange
    • Patient centric
    • Provider centric
  • Problem to Solution
    • Avoid Type 3 Error
  • VCaaS with HealthIoT - Data pipeline
  • AIaaS Data Insight to prediction
  • A vicious circle of continuous improvement and new services
  • Approval
    • FDA's software as a medical device (SaMD)
    • Modular Approval (not platforms)
  • Interoperability
    • Curse Act
    • Information Blocking
  • FDA’s role
    • FDA has grown to encourage the use of virtual care to improve data quality, volume, variety & velocity
    • 343 Entries in the database with none showing continous improvement! Why?
      • Risk
      • Data Shift
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Who will pay for AI in Healthcare?
  • Compensation for AI services in its early stages
  • New Technology Add-On Payment (NTAP) - CMS
  • Burden
    • Of Proof (It works!)
    • Also of Value (It Saves!)

VCaaS and AIaaS in practice (e.g. Stroke)

Role of Artificial Intelligence in TeleStroke: An Overview

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VCaaS and AIaaS in practice (e.g. Stroke)

  • Why Pay for Virtual Care?
    • Pre-Pandemic
      • Lack of Physicians (e.g. Stroke, Psychiatry) > Proven Value
    • Pandemic
      • Contactless Care
    • Post-Pandemic
      • Convenience & Value
      • Genie is out of the bottle
  • AI in Healthcare
    • NTAP for Stroke
    • Why?
    • Creates Value

Stroke Care in Evolution

  • Cost of Stroke (2016 US-dollar values)
    • 103.5 billion
      • Direct Cost - $38 billion
      • Indirect Cost - $38.1 billion
      • Premature mortality - $30.4 billion
  • VCaaS
    • Acute Care
    • At home Care
    • Chronic Care
  • AIaaS
    • Acute imaging
    • Patient monitoring
    • Rehab monitoring

Colossal Opportunity

  • 1 Trillion a Year
  • If 10% that is 10 billion a year


Junaid Kalia MD

Written by

Junaid Kalia MD

CEO | Founder | President NeuroCare.AI - Advancing Digital Health Ecosystem in Emerging Countries!

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