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9 digital health predictions you can count on, and the reasons behind this year’s pattern building behaviors.
The past 2 or 3 years have been years of remarkable progress (and a lack thereof) in digital health. They’ve been years of disruptive ideas, breathtaking innovations, and startling failures. And because of that, my digital health predictions for 2016 may not seem as sparkling as years past.
I believe that rather than looking ahead into a year of startling disruption, we’re past due for a plateau. 2016 will be that plateau in the form of a pattern recognition year, a year of maturing and focusing on building replicable patterns so that we can sustain the big things we’ve already built.
What does that mean? Here are some of the specific things that I think we might see:
Clinical development will start to use new and different patterns, all of which will become recognizable very quickly.
In 2016, the life sciences industry will finally get it together. If you follow digital health news, you’ve probably seen announcements about bigger budgets and more specific planning in the life sciences sector for 2016. It’s that funding that will help us build patterns around digital diagnostics, therapeutics, and enhancers, allowing digital tools to finally make an impact therapeutically on consumers in a predictable and sustainable manner. We’re also ready, this year, to change the patterns around drug creation and digital diagnostics, all in a meaningful and repeatable way.
With that, we’ll see stronger and more reliable regulatory practices for life science products and processes.
Once the life sciences sector starts to move in a way that’s more recognizable, they’ll likely organize around one or two sets of practices. That cadence will allow more soothing regulatory practices, which will be really beneficial for all.
However, there won’t be any moonshot discoveries.
As I said earlier, I don’t expect to see any moonshots in 2016. Instead, we’ll see incremental advances, which we desperately need: slightly better analytics, slightly better content, slightly better loyalty programs, and slightly improved health outcomes. This will be a stabilizing, fine-tuning year, a year where pattern recognition is important before we can push the envelope again.
Unfortunately, we may see a truly adverse event tied to digital health in 2016.
This is a tough prediction, and I thought for hours about whether or not I should include it in this blog. Ultimately, though, I decided that this prediction is important to discuss if we’re to have any chance at preventing it.
Thus far, we haven’t seen a truly massive adverse event around digital health. We’ve seen hacking around healthcare data during the past few years. But I worry deeply that we’re getting to the point, this year, where connected devices are the fullest they’ve ever been of vital pieces of health and security information. However, they aren’t as cloaked security-wise as they should be. This leaves huge opportunities open for hacking, attacks, or something even worse: a massive change up of medications or doses for hundreds of people, for example.
If this kind of event did occur, we’d likely see a strong downstream effect in the digital health industry, especially in terms of regulation and distribution. To even think about these kinds of adverse events is a necessary part of maturity in a growing industry, as these events should sadly be almost expected at this point. If this is a pattern recognition year, we must remember that hackers are most attracted to just that: patterns.
Beyond this, CRM models for managing customer experience will become defacto.
A retail model of healthcare has already started to permeate the healthcare landscape, and it will force itself into the limelight in 2016, encouraging data portability for moving from one power account to another, easily. Along with this, the retooling of relationship management is something I’m really excited about for 2016. Consumers already have higher expectations around relationship management than ever before, so they’re more likely to pick retailers with better digital strategies. This will require a retooling of all user experiences into standard CRMs, instead of proprietary models.
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