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Artificial Intelligence Market—Key Application Areas for Growth in Healthcare IT, Forecast to 2022

  • Report

  • 126 Pages
  • August 2018
  • Region: Global
  • Frost & Sullivan
  • ID: 4616535

Optimizing Quality and Efficiency of Healthcare Delivery with AI

The study describes how AI technologies are paired with legacy healthcare IT systems to deal with the complexity & growth of medical data. The publisher acknowledges that AI intuitively finds ways to convert these ever-expanding resources into actionable evidence for end users. In this study, the publisher has forecast global revenue for primary healthcare IT segments* which leverage AI to augment product functionalities. Additionally, the study also features and assesses various progressive AI vendors, offering visionary capabilities that strive to normalize disparate patient data, apply scientific algorithm to generate healthcare evidences and drive cognitive reasoning to predict population health outcomes.

The global market revenue has been classified by these end users' corporate receptivity, behavioral agility, and financial ability to fund and sustain AI-enabled HC interventions that promise better outcomes for all.

Democratization of AI is on the horizon, which may disrupt the way healthcare has been perceived and delivered.

Today, AI-powered digital health solutions primarily allow healthcare enterprises to predict, automate, and prescribe evidence-based business decisions. However, AI-powered digital health solutions from technology maturity and real-word applicability standpoint are still in their infancy. Hence the technology penetration across all end users is low to moderate. It has been estimated that at present only around 20% of these end users would be actively using AI to drive real change in the way healthcare has been conceived and delivered. However, as leading IT companies such as IBM Watson Health, Google, Amazon, Microsoft, Philips, GE Healthcare and Salesforce have started to offer impeccable cloud services and tools to independent AI software developers, more progressive applications, capable of ensuring tangible ROI to end users would flourish and drive the overall market penetration for these technologies.

‘Big-Tech’ is taking the lead to catalyse innovation in the healthcare AI market.

Google is primarily using AI to source and normalize EHR data to identify disease patterns that were historically untraceable. IBM continues to grow its presence in healthcare, driven by a focus on AI-powered clinical decision support, imaging analytics and population health management through its Watson Health business. Additionally, Amazon is making inroads into various aspects of healthcare AI (and could make a big move voice applications, cloud infrastructure solutions and visionary research works)-or several big moves in this year. Major EHR companies are committing to reduce physicians’ IT burden by incorporating AI-enabled and voice based medical assistants into their incumbent EHR workflows. Epic recently announced that it has integrated Nuance’s AI-powered virtual assistant platform into its EHR. Functionalities include the ability for clinicians to ask for lab results, medication lists, visit summaries and other information in the Epic Haiku mobile app. Athenahealth is also partnering with progressive start-ups that help physicians automate the process of patient scheduling, clinical documentation and coding.

Putting Patient Data into Work is a Critical Perquisite of Success for AI-powered health IT solutions.

“Big-tech” must acknowledge that patient generated data which next-generation IT platforms interpret has multiple utilities for diverse healthcare stakeholders. Fully informed consent from patients coupled with 100% compliance with stringent data usage regulation has to be ensured to remain relevant in the market.

This new research report on Artificial Intelligence Market – Key Application Areas for Growth in Healthcare IT provides a comprehensive analysis on the global healthcare AI market which is primarily segmented into three service verticals that embrace a range of AI technologies to modernize care, personalize treatment and improve outcomes for key end users.

Key Regional Markets, Covered in the Research Study

  • The United States of America
  • The United Kingdom
  • France
  • Germany
  • China
  • Switzerland
  • Japan
  • India

Types of AI Products Discussed in the Report

  • SaaS Based
  • App Based
  • Integrated Hardware
  • Research-based
  • Doctor-facing
  • Patient-facing
  • Telehealth

Key Service Segments (Vendors are Selected by Sub-Segments), covered in the Research Study*

  • Clinical Applications
  • EMR
  • Clinical Decision Support Systems
  • Clinical Analytics
  • Imaging IT
  • Precision Medicine/Genomics IT
  • Wearable
  • Femtech
  • Mental Health
  • Patient Engagement
  • Population Health Management
  • Telehealth
  • Operational Applications
  • Administrative Management
  • Supply Chain Management
  • Enterprise Content Management
  • Cybersecurity
  • Financial Applications
  • Business Intelligence
  • Revenue Cycle Management
  • Coding and Claims Management

Key Disease Categories, covered in the Research Study

  • Cancer
  • Cardiology
  • Diabetes
  • Endometriosis
  • Infectious Diseases
  • Rare Diseases

*Adoption of AI for the pharmaceutical market, as it relates to digital health, is also discussed but is not included in the market revenue numbers.

Key Issues Addressed

  • What are the regional market trends and industry dynamics in global AI for healthcare IT market? What is the future potential for AI-powered healthcare IT solutions?
  • What is the current market scenario? How much growth is expected? Which are the major market segments? What will be the impact of external trends on each business segment?
  • Who are the major participants in the global AI for healthcare IT market? What and how are they innovating in this space?
  • What are the important business model considerations (penetration, pricing and profitability information) for healthcare stakeholders and providers? Who should pay for healthcare AI products? Is there an untapped opportunity in this market?

Table of Contents

1. Executive Summary
  • Key Findings-Opportunity Analysis: AI for Clinical Applications
  • Key Findings-Opportunity Analysis: AI for Operational Applications
  • Key Findings-Opportunity Analysis: AI for Financial Applications
  • Regional Market Key Findings-AI Footprint across the World
  • Market Engineering Measurements
  • CEO’s Perspective
  • 3 Big Predictions

2. Introduction to Artificial Intelligence
  • What Really is Artificial Intelligence?
  • What is the Difference Between AI and Cognitive Computing?
  • The Evolution of Artificial Intelligence
  • What Technologies Constitute AI?

3. Market Overview
  • Technology Adoption in Healthcare is at an Inflexion Point that is Driving New Industry Paradigms
  • Artificial Intelligence in Healthcare-A Technical Framework
  • How to Categorize AI Systems in Healthcare
  • How is the Value Being Created?
  • AI in Healthcare-Drivers
  • AI in Healthcare-Challenges, Impact and Outlook
  • The Business Ecosystem of AI-Global Perspective
  • The Business Ecosystem of AI-The US Market is Well Organized to Pioneer Innovation
  • The Business Ecosystem of AI-Discussion

4. Regional Views
  • What KOLs Perceive of AI’s Relevancy in Healthcare Across the Globe (In Order of Importance)
  • Methodology For the Following Slides
  • Comparative Assessment of the Global Healthcare AI Sector

5. Technology Overview-Key Application Areas
  • Market Segmentation
  • AI Powered Clinical Management-Application and Category Areas
  • AI for Clinical Applications
  • AI Powered Operations Management-Application and Category Areas
  • AI for Operational Applications
  • AI Powered Financial Management-Application and Category Areas
  • AI for Financial Applications

6. Adoption Outlook
  • What is the State of AI Adoption Across Care Delivery?
  • Types of AI Products Offered to the Healthcare IT Market
  • AI Product Breakdown by Disease Categories and Application Areas
  • Types of End Users, Leveraging AI to Improve Patient Care
  • Top 10 Healthcare IT Services that will Benefit Most from AI
  • Penetration Analysis-Hospitals
  • Penetration Analysis-Physician Practices
  • Penetration Analysis-Payers

7. Forecasts and Trends-Total Market
  • Market Engineering Measurements
  • Forecast Assumptions and Definitions
  • Market Revenue Forecast-Scenario Analysis
  • Revenue Forecast
  • Percent Revenue Forecast by End-user Segment
  • Revenue Forecast by End-user Segment
  • Revenue Forecast by End-user Segments Discussion
  • Percent Revenue by Service Verticals
  • Percent Revenue by Service Verticals Discussion

8. Forecasts and Trends-Hospitals Market Segment
  • Forecasts and Trends-Hospitals Market Segment
  • Market Engineering Measurements
  • Hospital Market-Revenue Forecast

9. Forecasts and Trends-Physician Practices Market Segments
  • Market Engineering Measurements
  • Physician Practices Market-Revenue Forecast

10. Forecasts and Trends-Payers Market Segments
  • Market Engineering Measurements
  • Total Payer Market-Revenue Forecast

11. Competitive Landscape
  • Competitive Landscape Assessment for AI in HCIT-Analyst Commentary
  • Customer and Revenue/Funding Break-up-AI in Healthcare IT
  • Procurement Process-How AI is Sold to End Users
  • Select Vendor Environment Ecosystem Examples
  • Competitive Environment
  • Companies to Watch
  • Promising Participants-Key New Companies in the AI Space

12. Growth Opportunities
  • 5 Growth Opportunities Critical for Future Strategies
  • Levers for Growth
  • Growth Opportunity 1-Predict Diseases
  • Growth Opportunity 2-Personalize Diagnosis
  • Growth Opportunity 3-Automate Clinical Documentation
  • Growth Opportunity 4-Pre-authorize Claims
  • Growth Opportunity 5-Optimize Compliance
  • Strategic Imperatives for AI in Healthcare IT
  • Legal Disclaimer

13. Appendix
  • Selected Sources
  • List of Exhibits

Companies Mentioned (Partial List)

A selection of companies mentioned in this report includes, but is not limited to:

  • Amazon
  • GE Healthcare
  • Google
  • IBM Watson Health
  • Microsoft
  • Philips
  • Salesforce