Is AI (artificial or “augmented”) intelligence just another buzzword in a sea of healthcare related acronyms to be tracked in the ‘hype cycle’ popularized by Gartner? Or is it a viable big data set, clinically relevant, deep machine learning, predictive analytics enabler of a better healthcare experience, with better outcomes at lower per capita costs?
The answer is AI is real and it’s time for integration of AI in its various forms of Machine Learning (ML), Natural Language Process (NLP) and Predictive Analytics (PA) into an enterprise’s strategic and operating plans. Make no mistake, the ‘Smart Race’ is on!
To understand the state of AI today tune into the video’s embedded: 1) “AI: What Working, What’s Not” by Frank Chen; and 2) “The State of Artificial Intelligence” where Andrew Ng describes how AI is the new electricity and how it’s transforming industries.
To discover the latest in health AI tune into The HLTH: Create Health’s Future conference live or through Twitter #HLTHEVENT October 27 to 30 in Las Vegas.
HLTH will feature several AI track sessions including Dave Hodgson Co-founder & CEO, Project Rōnin, Sean Lane, Chief Executive Officer, Olive, Amy Compton-Phillips, MD, Executive Vice President, Chief Clinical Officer, Providence St. Joseph Health and Suchi Saria, CEO and Founder, Bayesian Health.
From higher profiled announced partnerships including DeepMind’s partnering with the UK’s National Health Service (NHS) and IBM’s expanding focus on accelerated drug discovery to genomics, the evidentiary track record is building. We’re seeing a growing body of ‘use cases’ suggesting the where, when and how AI can add value to a healthcare ecosystem characterized by a complex tapestry of conflicting incentives as health leaders navigate the pivot from volume to value.
The initial set of conditions for which AI holds both promise and early findings include: the reduction or prevention of (1) falls, (2) pressure ulcers (3) improving care at the bedside (4) facilitating the alignment of clinical staff with institutional or enterprise protocols (5) improved efficiency of operating processes and (7) improving adherence and compliance to health, wellness and medical therapies at home or anywhere through mobile IoT devices and experiences.
In a survey published January 2019 “Machine Learning in Healthcare: Expert Consensus from 50+ Executives” the following themes emerged:
- Broad Scale AI Adoption by 2025: Over 50% of respondents believe that AI will be ubiquitous in healthcare by 2025. On an open-ended question, over 25% of respondents stated that they believe that AI will be nearly ubiquitous in healthcare setting by 2025.
- Dire Need for AI Healthcare Case Studies: Nearly 50% of US companies believe that the healthcare industry “needs to be convinced further of ROI from AI / ML investments”. Decision Support Systems to Improve Patient Care Come First: “Decision support systems” was ranked as the most likely application to be improved by AI (for improving patient outcomes), with an average 4.15 score on a 1-5 scale.
- Hospitals Purchase Mostly by Patient Outcomes and Financial Efficiencies: “Improving Health Outcomes” was rated as the factor of highest importance in getting a customer to buy an AI product, rated a 4.2 on a 1-5 scale. “Saving Money” was rated a close second with a 4.1 score. Most other reasons rated as significantly less meaningful in closing healthcare deals.
- AI’s Near-Term Focus Will be Improving Chronic Conditions: “Chronic Conditions” was listed in nearly one-half of responses when execs were asked to predict patient care improvement across ailments. Of the specific conditions mentioned under “Chronic Conditions”, “Diabetes” topped the list at nearly 30% of the mentions. “Cancer” was less popular and was listed by slightly over one-third of respondents.
While perhaps new to some, Artificial Intelligence or AI is 63 years “old” dating back to a 1956 AI conference at Dartmouth. AI, or its mentions in health system strategy, is increasingly a common topic at forward looking healthcare conferences focused on innovation. In 2017 over 300 companies in the Fortune 1000 mentioned AI in their earnings reports.
Further, AI drives the Amazon ecosystem, Netflix recommendation engine and our new voice agent friends – Siri, Alexa, Cortana, Erica and all those nifty apps on our smartphones. AI gets better and better from the massive data sets being generated, ingested and consumed by all of us moment by moment. Practically everything we do results in “digital data exhaust” that is tracked, stored, contextually analyzed and often sold as fuel for the AI inside our convenience oriented, consumer preference driven tech enabled lifestyles – many of which have achieved “can’t live without” cultural standing.
Deploying an effective AI strategy is not optional for any clinical or life sciences organization, health system or enterprise focused on “sensing”, “predicting” or “creating” future products or services that meet member, patient or customer needs – while delivering on both profitability and targeted outcomes improvement (quality, access, efficiencies or costs). We know that “better sensing” and predicting are essential to lower costs, improve productivity and improve the lives of the people we serve. In the United States today, when your actions create digital data, it becomes the property of LinkedIn, Amazon, Google and all those apps on your mobile Internet connected device – smartphone or wearable. And coming soon are insertable nano-agents circulating inside you, sensing your vital signs and sending a stream of bio-metric data signals intent on helping you optimize your health while minimizing your risk for disease.
While the U.S. market is a “wild, wild west” of the digital data industrial revolution today, China seems uniquely positioned to leverage the massive data sets associated with and produced a population seemingly less concerned about privacy than the ‘mass personalization’ it promises and selectively delivers. In Europe, with the passage of GDPR, the right to your individual data is back in the hands and control of citizens (patients, members, beneficiaries, etc.), not companies’ or data brokers.
Focused or “narrow AI” which senses and predicts and facilitates transactions (e.g. Alexa what is the temperature outside?; or order more Vitamin C) is the primary mode of today’s generation of AI. But as we’ve traveled the world, reported on and engaged thought leaders in precision medicine and personalized health over the last 10 years – it is our view “Super AI” or more social / relationship based AI will leapfrog today’s AI in our product and service labs across the globe and become widely deployed during the next 10 years.
Meanwhile, China has a national policy of being the leader in AI by 2030 (See: Superpowers Audiobook | Kai-Fu Lee | Chapter 1 | China’s Sputnik Moment) – with money deployed in every school and funding to pay AI experts to come to China as opposed to building walls to keep them out.
What is your AI strategy and plan across your enterprise? Where are you on the continuum of grasping and developing on-boarding strategies in your facility or institution? Where is the “low hanging fruit” from an adoption and ROI perspective?
Healthcare AI Leaders and New Movers
In health, AI is powering the next generation of health (care). Now the word care is in parenthesis because today’s world success in healthcare means focusing “health.” Healthcare really is a periodic unwanted purchase and nobody wants to go to hospital unless they really need to go. With the rapid entry of Walmart, Amazon, Apple, Google, Facebook, Microsoft and other consumer products companies to health (care) the focus is on “health”, affordability and convenience.
Becker’s Hospital Review identified 100 leading AI health companies. The list included the newly public Change Healthcare that delivers a range of health IT services such as the Intelligent Healthcare NetworkTM with blockchain and AI. Recently, they announced a focused Claims Lifecycle solution powered by AI.
Jvion uses AI based prescriptive analytics technology that identifies hospital patients’ risk profiles, assesses interventions and identifies possible engagement options. Recently they announced a partnership with the Novant Health Institute of Innovation and Artificial Intelligence. The focus of their collaboration is the reduction of congestive heart failure re-admissions.
Based on our market research there is a new generation of AI solutions being developed. A couple of examples of under the radar innovators are:
- Moterum Technologies, a Neural Life Company, co-founded by David Huizenga, PhD, JD and Manoj Agawala (formerly President of hCentive acquired by Optum) has integrated a revolutionary stroke gait recovery device and specialized neural sensors and algorithms with a digital therapeutic SaaS platform that has an AI engine that saves time and delivers the most up to date recommendations for clinicians to personalize care to individual stroke and Parkinson’s patients. Results on the effectiveness of the Moterum iStrideTM Device was published in the The Journal of NeuroEngineering and Rehabilitation where they reported “All participants improved on all three functional outcomes (gait velocity, Timed Up and Go Test, and 6-Minute Walk Test).”
- Tuzag, Inc., led by Neal Sofian, the innovator behind the first social network in health “Cancer Survivors Network” by American Cancer Society, has built a conversational “Relationship-Bot” that promises to replace the clunky Interactive Voice Response (IVR) front end to health call centers. Tuzag is built on 20 years of 1:1 advertising personalization technology they have Alexa listening indefinitely and remembering previously conversations and then being able to transfer content/learning from previous conversations to a means of delivery: chat, voice, SMS, web, print. Tuzag has moved beyond AI facilitated transactions to providing conversation and a Relationship-Bot! The Tuzag Relationship-Bot is interacting with new movers to improve medical access, daily health check-in for people at home, patients in different clinical situations and new services for health plans.
- Check out Neal’s Geekwire interview or “Can virtual assistants make healthcare more human? Startups create voice tech for doctors and patients”.
The Bottom Line = It’s Time to Act!
If AI is not part of your organization’s 5 year plan – it needs to be very soon. For health systems, Novant Health is a great example of leadership with the launch in June 2019 of Novant Health Institute for Innovation and Artificial Intelligence. To explore another cut on 100 leaders in AI in life sciences and advanced healthcare scan the “Top 100 AI Leaders in Drug Discovery and Advanced Healthcare” by DKA Global.
The time to build and implement your AI strategic plan is now. Health leaders can take their top priority projects – define the problem and then ask “how can AI help us: 1) Focus; 2) Differentiate; 3) Lower Costs; and 4) Improve Quality that create leapfrog solutions that meet BIG customer need and create happiness and positive impacts.”
It’s your choice to lead or follow in the wise and smart use of AI. Let’s figure out how to do it better together using AI and human wisdom and ingenuity!
For more knowledge and insights:
Douglas Goldstein \ twitter: @eFuturist \ M: 703.626.0798 \ doug@eFuturist.net
Gregg Masters, MPH \ twitter: @2healthguru \ email@example.com