MedCity Influencers

How AI can conquer the last data frontier

Companies that leverage AI can leapfrog antiquated players with data that can do everything from coach a person about which exercise regimen has the biggest impact on their health outcomes to which medicine a clinician should prescribe to a specific patient.

AI, machine learning

For the last 20 years, I have worked in the technology industry. Innovation has rapidly advanced to solve every kind of problem from business, to transportation and retail. Analytics and algorithms invented to optimize supply chains, arbitrage pricing or identify the best personalized offers for retail shoppers have received billions of dollars of investment. On the consumer side, recent advancements have been even more profound with apps to help people do everything from track personal finances to match with a soulmate.

Unfortunately, there’s one industry lagging behind the rest.

While there has been some promising medical device innovation, system-level healthcare innovation is truly lacking. If you walk into your doctor’s office, you will likely see clinicians sitting behind an old computer, typing notes or filling out forms in an antiquated, hard-to-use electronic health record (EHR) system. As a result of these outdated systems, doctors spend nearly half of their time on EHR and desk work, and only about 30 percent of their time meeting with patients.

Why did healthcare get the short stick? The industry faces multiple barriers to innovation. Privacy concerns and regulatory hurdles slow the pace of new developments. EHRs, which were not originally installed to capture and unify data across types, lack standardization and encounter interoperability challenges.

The advent and recent legal requirement to store healthcare information in EHRs have created a treasure trove of clinical data that is waiting to be unlocked for a whole host of analytical purposes. However, we find ourselves with enormous amounts of valuable data siloed in multiple, discrete applications and even within the same EHR system, the designs of these systems often keep data fragmented and not in a form that a clinician or HCP can use to get insights to provide better care.

There is a huge opportunity in front of us to unify this data to enable research, to allow clinicians to connect the dots on specific patient care plans or to determine the trajectory of an individual’s disease state. Investment dollars are starting to show that there has been a sea-change. Innovation is happening. In fact, just in the first half of 2017, $3.5 billion was invested in 188 digital health companies.

These investment dollars are funding everything from new equipment companies (Peloton) to next-generation EHR companies (Modernizing Medicine) to companies like mine that are focused on insights for a specific chronic disease like diabetes (Glooko).

As the investment dollars come in, those companies that leverage the power of AI and machine learning will likely have the biggest impact because they can deliver insights and experiences that resonate with users. They can leapfrog the antiquated players with data that can do everything from coach an individual about which exercise regimen has the biggest impact on their health outcomes to which medicine a clinician should prescribe to a specific patient. Ultimately these tools present a worthwhile investment as they can help scale the healthcare system to handle the rapid growth of chronic disease globally, innovate to drive healthier living, produce better health outcomes and lower costs to the system.

So how does using AI enable healthcare companies to leapfrog and lead when it comes to leveraging technology to deliver care and improve outcomes? Below are five ways technology and specifically AI can be a scalable advantage for healthcare companies.

Technology as an early warning system
Preventive care is not only good for patients, it’s good for insurance companies and health systems too. That’s because less costs are incurred and people need less acute care. Through data, technology companies have been able to develop early warning algorithms that can identify if a person is trending in the wrong direction.

For example, if over time a person’s weight is creeping up, their glycemic control is changing or showing signs of depression, AI tools can identify this early, warn patients and healthcare providers and even recommend the most effective solutions to prevent or slow down the issues.

Add speed and scale to diagnosis
It might be taboo to say this, but we’ve found that a good algorithm and training data can identify issues in a sea of data faster than clinicians and for more people.

During a standard appointment, a clinician gets about 15 minutes to evaluate a patient’s medical history, their input on how they are feeling, weight, blood pressure, temperature and laboratory data. During that same 15 minutes, they have to conduct an exam and often capture the interaction in an EHR. With algorithms and built-in analytics, issues can be rapidly brought to light for the clinician without them having to find the proverbial “needle in the haystack.”

Provide personalized care
When was the last time your doctor told you to lose some weight and exercise more? Often, we receive generic advice that isn’t necessarily specific and personal to our metabolic rate, preferences, and history. In these cases, AI can step in. With just a little data, an algorithm can tell you everything from how certain meals affect you to which exercise works best.

Support in between visits
Most of us are able to visit the doctor just a few times a year. In between visits things like Google searches, online communities, advice from friends and our own intuition guide our personal care.

Wouldn’t it be great if you get more clinical and direct support in-between visits? Technology can make this happen at scale. Digital health tools can give individuals quick access to a care professional as well as deliver health insights that can help individuals make decisions and get support in between visits.

Digital therapeutics
A relatively new concept, digital therapeutics uses technology to help individuals self-manage aspects of their care plan. In diabetes, this could mean anything from computing the right insulin dose to prescribing changes to a device setting or determining the right mix of medications for metabolic control. These technologies go beyond recommendations, communications and reminders to actually carrying out a clinician’s prescription to ensure adherence and compliance with the care plan.

Using technology and AI to ‘conquer’ some of the biggest cost drivers in healthcare can have a dramatic impact both on individuals and how clinical care is delivered. It’s about time.

Photo: ANDRZEJ WOJCICKI, Getty Images

 


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Michelle deHaaff

VP of Strategy at Glooko

Michelle deHaaff is VP of Strategy at Glooko. A long-time technology industry veteran, Michelle leads strategy at the diabetes-focused digital health company. Michelle brings to Glooko over 20 years of technology industry experience with a focus in analytics and customer experience. Previously Michelle held leadership positions in marketing and product management at Medallia, a customer experience management company, Attensity, a natural language processing analytics company and Blue Martini, a data-driven e-commerce company. Michelle also consulted Silicon Valley giants as a CRM consultant at Ernst and Young management consulting. Michelle earned a BS in Marketing from NYU's Stern School of Business and an MS in Integrated Marketing from Northwestern University.

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