CONNECTED HEALTH CONFERENCE • SAVE THE DATE • October 16-18, 2019 • Boston, MA
By Amy Bucher, PhD is Behavior Change Design Director at Mad*Pow. She tweets at @amybphd. She is a member of the Society of Behavioral Medicine.
We talk about the potential of digital interventions to revolutionize healthcare. They’re scalable, portable, personal, and pack consumer appeal. But we still aren’t able to say with much certainty under what conditions they work, if any, particularly for some of the populations who could benefit most: The chronically ill, people with significant transportation, cost, or other barriers to traditional healthcare access, caregivers who don’t have formal medical training but want to monitor and assist their loved ones. If we could just figure out what interventions—or even what types of interventions—are clinically efficacious for outcomes that matter, we could recommend the right tools for each person’s interests and needs. And we may even be able to get health plans to pay for them.
So why don’t we know which digital health interventions work? One issue is that we need to figure out how to measure behavior change outcomes reliably. Another major problem is that the digital health industry is hyper-focused on short-term metrics at the expense of more meaningful longer-term ones. Companies look at metrics like sign ups, logins, and clicks to determine whether a product is successful; longer-tail outcomes, like health changes or cost reductions, often follow well after a product has been deemed a hit or failure.
This short-term focus is understandable. It’s a remnant of an advertising-driven internet, where clicks translated directly to revenue. Typical business models urge a focus on short term successes, with quarterly and annual reporting used as the basis for a company’s valuation and appeal, and venture capital funding raised in rounds intended to sustain a business for a few years at most. It may feel risky to entrepreneurs to take a longer view of success, especially in a market where technology can evolve quickly and dramatically.
Fortunately, the most promising future revenue models in digital health include players like pharmaceutical companies, hospitals, health systems, or possibly even government via CMS or the VA. These organizations have a vested interest in making sure solutions are truly efficacious, and they’re not likely to pay for ones that aren’t. To determine which ones those are, we must shift how we think about determining whether digital health interventions work.
It’s time to think about measuring the outcomes that really matter. These may take weeks, months, or even years to come about (hence the term lagging indicator often used to describe them). These outcomes may include:
Fortunately, we can do more than just wait patiently hoping to see positive results. Here’s how we can plan for success:
Ultimately, the stakeholders in the system who purchase digital health products want to see a return on investment. As more companies enter the digital health space, the ability to demonstrate meaningful long-term outcomes will distinguish the survivors from the forgotten.
There will be a pre-conference workshop on behavior change at the Connected Health Conference: