The Sick Care Artificial Intelligence Use Case Primer

The Sick Care Artificial Intelligence Use Case Primer

Digital health definitions vary but the term is usually used to describe the use of information and communications technologies to exchange medical information. How it is used and for what purpose varies from one use case to the next. 

Here's how I slice and dice the industy:

1. Remote sensing and wearables

2. Telemedicine

3. Data analytics and intelligence, predictive modeling, AI, blockchain

4. Health and wellness behavior modification tools

5. Bioinformatics tools (-omics)

6. Medical social media

7. Digitized health record platforms

8. Patient-physician patient portals

9. DIY diagnostics, compliance and treatments

10. Decision support systems

Research published by MarketsandMarkets projected that the healthcare artificial intelligence market is expected to grow from $667.1 million in 2016 to more than $7.9 billion by 2022, a compound annual growth rate of 53 percent over the forecast period. This explains why companies such as IBM and Google are dominating advancements as they develop deep learning techniques that can revolutionize the way diseases are diagnosed, treated, and even prevented.

However, with AI’s success, comes its many challenges.

According to Niall Brennan, former chief data officer at Centers for Medicare and Medicaid Services (CMS), one of the key challenges related to whether or not artificial intelligence and machine learning gain traction is “translating it into something tangible that will resonate with payers and lead them to think about realigning financial incentives” to improve patient outcomes and reduce healthcare costs. In other words, while you need to demonstrate technical, commerical and clinical value, you also need to make the business case for translating data to value.

Artificial intelligence is being deployed in sick care in many different ways:

  1. Surf-n-turf. Patients can use AI driven symptom checkers to identify most likely diagnoses and then triaged (turfed) to the most appropriate care site or healthcare professional
  2. Patient track and trace. AI is used to track patients with chronic dieases to improve compliance and minimize waste
  3. Sickcare to healthcare. AI used for disease prevention and maintaining wellness
  4. Mobile learning. AI used to create personalized mobile learning platforms
  5. Patient engagement.
  6. Reducing doctor burnout
  7. Transforming clinical documentation and EMRs
  8. Patient reported outcomes (PROs)
  9. Drug discovery and development
  10. Supply chain management
  11. Improving patient safety and quality
  12. Improving eldercare
  13. Behavioral health
  14. Social determinants
  15. AI hype
  16. Disparate health outcomes and care inequality
  17. Precision medicine
  18. Pattern recognition in pathology, radiology, retinal scans and dermatology
  19. Chatbots
  20. Robotics

If that doesn't make your head explode, how about combining AI with blockchain? Or using AI to pick AI investment winners? Or a platform that allows you to use AI to create AI?

The list of potential AI applications in biomedicine and clinical care will continue to expand. The challenges for AIntrepreneurs are substantial. Most AI digital health companies will fail (here are the reasons why) and they will have to deal with the social, economic and ethical issues.

We will all need to work together if patients and doctors are to win the 4th industral revolution.

Arlen Meyers, MD, MBA is the President and CEO of the Society of Physician Entrepreneurs.

Share this article

Leave your comments

Post comment as a guest

terms and condition.
  • Mitchel Sudyko

    We need more digital tools that can help both clinicians and patients make better healthcare decisions.

  • Rebecca Alderson

    To best assist doctors, clinical computing tools should approximate the same process.

  • Lauren Hutchinson

    Excellent! A paradigm shift is over due in terms of health care and how we solve problems in this time and age.

  • Marcus Garcia


Share this article

Arlen Meyers, MD, MBA

Former Contributor

Arlen Meyers, MD, MBA is a professor emeritus of otolaryngology, dentistry, and engineering at the University of Colorado School of Medicine and the Colorado School of Public Health and President and CEO of the Society of Physician Entrepreneurs at He has created several medical device and digital health companies. His primary research centers around biomedical and health innovation and entrepreneurship and life science technology commercialization. He consults for and speaks to companies, governments, colleges and universities around the world who need his expertise and contacts in the areas of bio entrepreneurship, bioscience, healthcare, healthcare IT, medical tourism -- nationally and internationally, new product development, product design, and financing new ventures. He is a former Harvard-Macy fellow and In 2010, he completed a Fulbright at Kings Business, the commercialization office of technology transfer at Kings College in London. He recently published "Building the Case for Biotechnology." "Optical Detection of Cancer", and " The Life Science Innovation Roadmap". He is also an associate editor of the Journal of Commercial Biotechnology and Technology Transfer and Entrepreneurship and Editor-in-Chief of Medscape. In addition, He is a faculty member at the University of Colorado Denver Graduate School where he teaches Biomedical Entrepreneurship and is an iCorps participant, trainer and industry mentor. He is the Chief Medical Officer at and and Chairman of the Board at GlobalMindED at, a non-profit at risk student success network. He is honored to be named by Modern Healthcare as one of the 50 Most Influential Physician Executives of 2011 and nominated in 2012 and Best Doctors 2013.

Cookies user prefences
We use cookies to ensure you to get the best experience on our website. If you decline the use of cookies, this website may not function as expected.
Accept all
Decline all
Read more
Tools used to analyze the data to measure the effectiveness of a website and to understand how it works.
Google Analytics