Skip to main content
By Monica E. Oss

Artificial intelligence. Augmented intelligence. Machine learning. Big data. If most health and human service organizations are challenged to develop a performance dashboard or exchange consumer data with other organizations, isn’t it a little early to be talking about these developments? These concepts may seem a bit “out there,” but there really are some initial uses of AI that are up and running, in the here and now.

So where are we seeing the practical uses of AI in today’s developing market? Health systems, payers, and employers are using AI for everything from predictive modeling and diagnostics, to precision medicine and care coordination—these are a few examples of how organizations are using AI to serve complex consumers.

There are multiple large health systems that are using AI and big data analytics for predictive modeling and care coordination. Montefiore Health System is using an AI infrastructure and big data analytics for predictive modeling to recognize everything from consumers who are at increased risk of mortality, to those who are at risk of respiratory failure or sepsis (see At Montefiore, Artificial Intelligence Becomes Key to Patient Care). And Johns Hopkins’ Center for Diagnostic Analytics has developed a new approach to big data analysis, called SPADE (Symptom-Disease Pair Analysis of Diagnostic Error), which helps to recognize diagnostic errors. The system utilizes big data analytics to scan multiple databases to help physicians to recognize errors in diagnosing consumers (see Johns Hopkins Researchers Use Big Data Analytics To Target Diagnostic Errors, Improve Quality).

Tampa General has partnered with GE Healthcare to launch a care coordination “command center” that can process streams of real-time data from multiple sources and “offer alerts and suggested actions to help the hospital track patient progression, predict and prevent safety risks and manage the workload of its staff” (see How AI Command Centers Are Helping Hospitals Harness Analytics To Manage Operations). CHI Franciscan Health launched a similar initiative with GE Healthcare, launching a command center that was “inspired by National Aeronautics and Space Administration’s mission control centers, [and] will feature an artificial intelligence-driven system that leverages predictive analytics and machine learning to assist in staff decision making around hospital operations” (see CHI Franciscan, GE Partner To Implement AI-Powered Command Center).

There are also many new tools that utilize big data analytics, which are currently being used by health plans and provider organizations. One example is Ginger.io, a mobile app that provides behavioral health support (including online cognitive behavioral therapy and mindfulness training), delivered by coaches, therapists, and psychiatrists. Using their AI technology, the app recognizes patterns in how consumers use their smartphones to tailor treatment models (see Using Artificial Intelligence For Mental Health). Ginger.io is currently offered through the UnitedHealthcare and Optum networks; and by the SEIU 775 Benefits Group for community of home care workers. The app has also partnered with multiple large employers, including Buzzfeed and Pinterest, to provide Ginger.io to their employees (see Ginger.io Builds On AI Foundation, Offering New Model Of Emotional And Mental Health Support and Ginger.io Offers Emotional Support To Over 50,000 Home Care Aides In SEIU 775 Benefits Group).

NextHealth’s predictive analytics platform is being used by provider organizations for population health management and to identify risk-reduction opportunities. Through the analytics platform, organizations can identify high-risk populations and develop personalized recommendations for consumers to improve outcomes and reduce costs. One Colorado-based provider organization was able to save $6.00 per member per month by reducing ER utilization among high-risk populations by using the analytics tool (see Executive Case Study: Delivering Outcomes – 6.3% Reductions ($6 PMPM) In ER Utilization In A Medicaid Population).

Mindstrong is a mobile app that passively collects data on consumer smartphone activities such as scrolling, typing, and clicking. Using this data, Mindstrong can identify individuals whose mental health is changing and intervene via telehealth and messaging. Clinical professionals can also view the data 24/7 and are alerted when individuals may need intervention (see The Mindstrong Behavioral Healthcare Solution and Mental Health Meets Digital Revolution: Mindstrong Health Raises $14 Million To Modernize The Diagnosis & Treatment Of Neuropsychiatric Disorders Via Artificial Intelligence (AI) & Smartphones). Mindstrong is currently offered by five county mental health authorities in California as part of their Innovation Technology Suite (see Five California Counties Approved To Launch Virtual Therapies Under Mental Health Service Act).

Health Fidelity is a technology platform that integrates with electronic health records and extracts data using natural language processing (NLP) to analyze and identify risk across populations as well as gaps in business functions. Executive teams and clinical professionals can then use this data to improve care and organizational performance (Health Fidelity Solutions – Provider and Health Fidelity Launches Industry’s First NLP-Powered Risk Adjustment Solution for Providers). Currently Mount Sinai Health Partners in New York and UPMC have signed on to use the Health Fidelity model for provider organizations (see Mount Sinai Health Partners Chooses Health Fidelity’s Risk Adjustment Solution to Support Value-Based Care Efforts and UPMC Selects Health Fidelity’s NLP-Powered Solution for Payer – Provider Collaboration).

These examples show that while AI isn’t yet common practice, its status is quickly shifting, making AI a strategic reality for many health and human service organizations. The AI market isn’t small—and its reach in health care is only increasing. Grand View Research, Inc. estimates the global AI market will reach $36 billion in direct revenue by 2025 (see Artificial Intelligence Market Size To Reach $ 35,870 Million By 2025). And Accenture estimates that AI in health care will reach $6.6 billion by 2021 (see Artificial Intelligence (AI) Healthcare’s New Nervous System). McKinsey & Company estimates the potential annual savings at 0.7% ($300 billion) of gross domestic product (see Artificial Intelligence – The Next Digital Frontier?), and ABI Research estimates that by 2021 the savings will grow to $52 billion (see AI To Save Healthcare Sector US $52 Billion In 2021). As the use of AI in health care expands, its ability to improve outcomes and increase efficiencies will reshape the expectations of consumers and payers. And when AI becomes a more common, every day practice, the organizations that can leverage AI to improve performance will have the competitive advantage.

Want to learn more about AI applications in the health and human service field? Here is a list of curated resources from the OPEN MINDS Industry Library to help you get a grasp of just how far along the path to automation we are:

  1. Ready Or Not, Cognitive Computing Will Change Your Organization
  2. We’ll Accept Robots As Human – And Become Immortal As Human-Machines
  3. Preparing For Your ‘Augmented’ Workforce
  4. Can A Virtual Assistant Make A Dent In Your Workload?
  5. The Virtual Assistants & Avatars Among Us

And for more, join me June 3-6, 2019 in New Orleans, Louisiana for The 2019 OPEN MINDS Strategy & Innovation Institute, where we will four days looking at how today’s health care innovations will become tomorrow’s standard practice.

Login to access The OPEN MINDS Circle Library. Not a member? Create your free account now!

Close

Support Request

Need help now?

Call our toll-free phone number 877-350-6463