A healthy dose of machine and cognitive technology for health care has been saved
A healthy dose of machine and cognitive technology for health care
Short takes...on Analytics
A blog by Dan Housman, director, Deloitte Consulting LLP
Fantasy? Fiction? The future?
Health care isn't the only industry realizing the challenges and benefits posed by advances in cognitive technologies, machine learning, and artificial intelligence (AI). But it is an industry quickly leveraging these cutting-edge advances, especially in the areas of research, diagnostics, treatment, and patient outcomes. Alarmists worry that smart machines will replace highly skilled practitioners in everyday health care encounters. They fear a depersonalized and invasive experience that could interfere with their health and personal lives.
Fantasy? Fiction? The future? In 2013 the movie “HER” was released in theaters featuring an AI operating system able to relate and integrate itself into the main character’s life so completely that he fell in love with her. With a year to reflect on this–and increasingly with an earpiece or headphones already in my ear from my phone or computer–I am convinced that the future of patient health will engage me like the computer in HER.
Humans and machines: Better together
Picture Scarlett Johansson whispering in your ear, telling you not to eat that second donut. She will know your behaviors, sensor outputs, preferences, and will offer useful whispers of wanted suggestions to keep your health on track. She will suggest that you grab an apple when you are about to eat that second donut, find the right messages that motivate you to exercise after the holidays, and remind you not just of which medications you forgot to take–but also of how important it is to take your medication daily.
In truth, smart machines aren’t likely to take over our lives, but advances in AI, cognitive, and machine technologies will augment human thinking and specialized skill sets. This should be welcome news to patients, many of whom enjoy a love-hate relationship with technology at home, but could benefit from those same technological advances to improve their quality of health care.
An apple a day–plus machine learning and artificial intelligence (AI)
Patients realize that their electronic devices help them with their day-to-day lives, including their health care consumer products, such as fitness bands. As a consumer, I am concerned with the “pain points” of health care, including my interactions with health care professionals, convenience, utility, and price. A health coach that is neither disruptive nor burdensome to my world, and highly personalized to me, is the ultimate expression of a consumer experience. An AI avatar can provide this.
We are at the dawn of yet another AI era, equivalent to the integration of multiple devices into a single smartphone. The applications of cognitive computing are about to assemble themselves into solutions that will march rapidly towards my best friend, my AI health advisor.
For example, the application Lark is now on the market as a health coach that chats with you on the phone. It chats using advanced learning and presents information against the context of your daily experience. You don’t pick from a complex list of foods to represent your lunch. You enter something in free text, just as you would text a friend. Another example: Cognitive Scale has constructed a health application called Cognitive Concierge focused on specific conditions. It uses a cloud approach to data, absorbing it from many facets and recommending insights on the user’s condition and the environment. So if you have asthma or chronic obstructive pulmonary disease (COPD), Cognitive Concierge knows to warn you when there is a high pollen count. It can be customized and deployed by health systems to integrate into their care management processes.
Taking the pulse of cognitive apps
Machine learning is also providing extensions to physicians’ ability to interpret images with viewing diagnostics such as medical imaging. Enlitic is using advanced machine learning to find signals in medical images that radiologists might miss. Unlike machines, the human mind cannot effectively look across all images of all patients and identify critical patterns. Welltok and Watson Health are also heavily investing in the generation of cognitive applications, with early interest in high stakes decisions, such as helping to review protocol selection options for oncologists. The race is on to make an advisor that patients will welcome into their world.
Other applications available today are cognitive tools that are working behind the scenes to match content with need. For example, the ability to offer education or entertainment to an individual is being adapted to optimize prioritization of the videos that can help patients better understand a disease based on their level of understanding, and at what stage they are battling the disease. Some offer cartoons illustrating how protected their cells are based on their adherence to HIV medication regimens.
Breaking through adoption barriers
Roadblocks to reaching the state of machine nirvana are the many concerns about ethics, risk, and compliance. But compliance will rapidly become the space of cognitive computing. Let’s look at the banking industry for illustration. How does a global bank determine that their thousands of locations are in compliance with global, regional, and local legal requirements regarding operating procedures? They either need to have an army of people reading every legal document and every internal policy for discrepancies, or they have to train a cognitive assistant to help highlight where potential gaps occur, and then use humans to confirm gaps and figure out how to remediate issues.
Just as cognitive computing is taking center stage for the banking industry, it will take center stage for health care, helping to address issues around privacy and compliance with Health Insurance Portability and Accountability Act (HIPAA) requirements. These compliance rules will be embedded into the AI that communicates with patients about their health. As a result, reporting of adverse events and dangerous health situations can be streamlined, getting the information to qualified professionals who can mitigate issues quickly.
Put me in, coach!
So here is a summary of why my Cognitive AI health coach is coming and accelerating as it comes…
- The patient wants to be engaged in his or her preferred context and not have to actively seek out health and behavioral information
- Gleaning the patient’s intent and reality of mood will best come from hearing things he or she says and being able to cognitively process speech vs. asking for complex forms to be completed
- Knowledge bases are consolidating in clouds that an AI assistant can pull from
- Sensor devices are everywhere, and only an AI can really make sense of them
- Speech recognition is coming online for hearing what we are saying
- Image recognition technology needed to identify useful information in our world is progressing rapidly
- The large volume of potential recommendations for non-critical decisions will be a ripe place to filter using a cognitive AI
- The rest of consumer components are going down this path, so health care would be well advised to piggy back on the progress of these other industries
- Compliance issues are going to be some of the first cognitive use cases, so this important area will be embedded into the Cognitive AIs
As discussed in the in the paper, “Cognitive technologies for health plans: Using artificial intelligence to meet new market demands,” developments in cognitive technologies and artificial intelligence could help improve cost-effectiveness, customer service, and population health. But to anyone working anywhere in the provider, pharmacy, or consumer wearables markets: Get prepared to adapt to a new world where a few blue ribbon AIs dominate the patient’s spare attention. In that world, your own products and services must integrate to generate artificial mindshare in the AI health coaches. I believe that we will see the pieces of this trend converging over the next three years–with winners emerging in less than seven.
For more on machine and cognitive trends that are shaping the health care industry of the future, read Deloitte’s Analytics Trends 2016.
Note: Parts of this post were excerpted from the blog, “Implications for the rise of AI in health care and patient engagement.”