Bull Session

Digital Healthcare Services in 2016 (and Beyond)

January 14, 2016          

Episode Summary

On The Digital Life this week, we chat about digital healthcare services in 2016 (and beyond). From sensor technology for medication adherence to conversational UI, health analytics to digital care planning, we cover the top industry trends to watch. If you like what we have to say on this topic, we encourage you to check out our piece on MobiHealthNews.

Jon:
Welcome to episode 138 of The Digital Life, a show about our adventures in the world of design and technology. I’m your host, Jon Follett, and with me are director Juhan Sonin and designer Beth Herlin, both from Involution Studios. Welcome to the show guys.

Beth:
Thanks, Jon. It’s great to be here.

Juhan:
Likewise.

Jon:
All right, so for our podcast topic this week, we’re going to chat a little bit about digital healthcare services in 2016 and beyond. If you like what we have to say on this topic, we encourage you to check out our company piece on MobiHealthNews. That’s M-O-B-I-H-E-A-L-T-H-N-E-W-S.com, so check out our piece there. It’s getting lots of shares, so people seem to be responding to it. Let’s dive in now to digital healthcare services in 2016 and beyond.

We’re going to start off with medication adherence getting a boost from sensor tech. We all know that everything is getting miniaturized, and that sensors are becoming ubiquitous, and they’re making their way into all sorts of tracking devices and into our phones, and so this is going to impact digital health in a major way, and we think some of these is going to be coming along in 2016. Now, adherence of course is extremely difficult to get people to take their meds on a regular basis, and so let me direct this question to you, Beth. How is sensor technology going to make adherence any easier for folks?

Beth:
A big problem with medication adherence is actually tracking to see if patients are taking their medication. They don’t want to also have to fat finger in, “Yes, I took it this day. No, I didn’t take it this day,” so any type of automatic or ambient sensor that can register whether or not that pill has been taken or that treatment has been done can drastically reduce the workload of patients.

Jon:
Solving this problem of adherence could have a major effect on the cost of healthcare because as we know, adherence is an extremely expensive problem if people can’t keep to their medications. More or less, it’s the equivalent of them not taking them or not taking them properly which just causes all sorts of difficulties down the line. One of our … things that we’re looking at is the idea of self-reporting. Beth, could you tell me a little bit more about self-reporting as it relates to adherence and how sensor technology can help with that?

Beth:
Essentially, sensor technology can almost eliminate the need for self-reporting, so a service, for instance, that might have a sensor on the pill bottle can register whether or not that pill has been taken, so there is no need for the patient to report. You remove that subjectivity of the patient maybe lying or something like that, or maybe mixing up which medication was actually taken, so it leads to higher accuracy and less workload for the patient.

Jon:
All right, so for our second digital service for 2016, this is a favorite of mine is the conversational user interface we think is going to be embedded into more healthcare related applications. This is, of course, driven by advances in voice recognition and artificial intelligence, so I’ll put this question to you, Juhan. How do you see conversational interfaces becoming more of a part of m-health in 2016?

Juhan:
For the history of medicine, it is usually been a one-way conversation. We just went on the conversation. It’s been a one-way mode of communication where there’s been a little tidbit about what the patient is doing, and the rest of the time, it’s the doctor, or the nurse, or someone else telling them what to do. Even the software today, it’s still much of the same ilk. It’s the one-way mode of communication where I’m being told what the problem is, or what the research is, or what to do next.

Now, what you’re seeing slowly come in is a two-way, three-way, n-way kind of conversation with you and the machine, with Dr. Watson in the loop, with you talking to that service, with you talking to your doctor back and forth, so these automated services more and more are going to actually behave like what we’re doing here today with you and Beth, and with me where we’re talking in concert, and there is an evolving conversation with it, and so that should also feel very natural just like … Maybe my conversation here is not very natural, but it should be with a machine or with other services is that I have a question, and it engages me like another human would, and I think this is the key to how you get people interested and engaged as it’s not … It doesn’t feel like something they run at a UNIX prompt and guessing like Zork go west, and then there’s a response maybe. This is a much more dynamic experience and more human for that matter.

Jon:
All right, so for number three of our trends to watch, we have analytics for patients and clinicians not just payers anymore. What we mean by that is, of course, the patient-centered metrics which payers have had access to in big enterprise-grade software systems where they could slice and dice the data and see what patients were costing them lots of money and what outcomes were unsatisfactory, et cetera, et cetera.

These systems have been part of health IT for some time now, and of course, they’ve been enhanced over time with nice visualizations and different ways of looking at the information, but this year, we think that healthcare analytics is going to expand, and we’re going to see more on the patient side as well. Beth, could you talk to me a little bit about how you see this happening and what the importance is of being able to analyze both your short and long-term health analytics?

Beth:
Yeah. I think one of the biggest problems with … We hear this term “big data” a lot. Everyone has a Fitbit or some kind of activity tracker that’s providing massive amounts of data all the time, and it’s not really clear exactly what we’re supposed to do with that information yet. Once we’re able to start predicting what this data means for you in the future, we can start having a much more engaging interaction with patients. We can evolve that into a unified health score for a patient. Not just a singular patient, but maybe start to compare how those health scores are happening across different interventions for both a single patient and an entire population of people.

Jon:
Terrific. Does this mean that I’m going to be able to start looking at my data and there’s going to be some software that’s going to give me recommendations about what I should be doing next?

Beth:
Right, so having that data and providing insights then allows you to start giving recommendations for exactly what actions should be taken to either confirm that positive future or prevent that negative future from happening.

Juhan:
There’s this idea that in the financial world of risk scoring, right? We’ve had this for some time. How are you going to quality for mortgage? How does a bank know? They do a financial risk analysis on you as a United Statesian, right? It’s been around for a long, long time. Mostly, because we care more about finances and anything else in our world, but now, the insurance, the health insurance mafias have had a long time … for a long time had this kind of similar scores where they score how people are going to do in the future based on their demographics as soon as they have solved this other kind of data points.

That’s what they’ve been using to dole out healthcare or to charge you for healthcare, and how to look at risk, and how to look at predictive risk, so that needs to shift and will shift on to the patient side. I want to be able to get the same vital score and the same one for my health, so I can start to see, “Well, what do I need to evolve? How do I need to change my behavior?” I think that’s coming for patients ASAP.

Jon:
Our fourth trend for digital health services is disease detection on your smartphone. Now, that’s a tall order, Juhan. How is that going to work?

Juhan:
I’ve got already … A few years ago, I remember seeing a demo from another MIT-er, and they showed how you could listen to someone’s voice as they talk into their phone over the course of days, months, and years, and listen to the tremors in their voice to detect disease. One big one is Parkinson’s. How can you listen to the vocal cord changes, the physical changes to your muscles there be able to see and hear that in advance?

We get very used to our voice and very used to how we operate and don’t notice these very small subtle changes. Yeah. That’s what machines are very, very good at, and that’s just one example of how we’re going to be doing detection on a disease level with the phone. That may translate into gait, gait analysis. It may listen to other parts of our vocalizing or lack of vocalizing, change in vocabulary. Maybe it becomes much more stagnant. These are things that are just beginning to mature or at least get to a place where they’ll be able to be used for diagnostics.

Jon:
All right, so for item number five, Beth, I know this is a topic area that you’ve spent an inordinate amount of time researching in your day to day work. Digital care planning and getting better patient outcomes in a tech-driven world. Could you tell us a little bit about how you see care planning shaping up in 2016?

Beth:
Sure. The main problem with care planning right now is that a lot of us go into a doctor’s office. We tell them what’s wrong with us, and they say, “Okay. Do these things,” and then we leave the office usually very empty handed and with a lack of understanding of what exactly they told us to do. Having a digital form of whatever the care plan is that our clinicians are creating and architecting for us can help better implement that plan in our lives.

Typical care plans consist of some kind of health history, your health concerns or problems, goals, interventions, and instructions, and then the review of all of that, plus your care team that’s going to help carry that out, so having some kind of service that can keep track of those goals that you’ve set with your doctor and help implement the … whether it’s through reminders or through delivering. Maybe it’s digital cognitive behavioral therapy is actually delivering treatment via the phone, and then tracking your progress towards those goals according to the interventions that are taking place. We can really start to get a better idea of how people are doing within their care plan and help evolve it over time and adjust it until it works for them.

Jon:
All right, so service number six. This goes to you, Juhan. Computable records and the next generation of the EMR conversation. Tell me, what is a computable record and how does that differ from what we have today?

Juhan:
For those of us who visit the doctor on a rare occasion or once a year, twice a year, whatever your frequency is, you will most likely have a record with that clinic, with that hospital system in an electronic healthcare system, right? Usually, owned by that particular hospital. Most often, when you try to go somewhere else, I go to a different hospital system, they will have no understanding, no record, and no history, and I have to fill the same damn paperwork out, paperwork notice again, and again, and again depending on where my promiscuous health encounters are.

The sad thing is that 2016 will most likely not see a huge spike in medical record interoperability, the ability to go from one hospital to another or to one service to another to be able to share my records beautifully. However, we are seeing several good things on the horizon, and one of them is The Argonauts Project where it’s a consortium of institutions, some big and some very big, that are rallying behind the FHIR, F-H-I-R schema, and that is one hope that we can have is that while it’s not the best of schemas, data schemas, it’s better than nothing. It’s better than CCD, and that for me is one hope or one signal flare for goodness.

The ultimate thing that I would like is that I want to be able to, one, have a record that I own, that I control. Two, that I’m able to dish it out to whoever wants access and to be able to proxy my data or parts of my data to whatever entity or service, digital service wants it, and I really … It should be treated almost like a Git Repo, right? If you’re in GitHub, I can allow people access to it. People can branch or fork it, and I can actually have it come back into my baseline, right? I like it to act much like our GitHub accounts now.

Then, also, the final thing is really the record itself should have some kind of flag or series of flags to say, “How complete am I? How do I know this is a good record?” Right now, again, we have no clue in terms of our own data, how filled up in good ways it is, so I think these are … there are multiple things happening here, and this is more of a stretched goal for 2016.

Jon:
Yeah. You’re probably more aware of how complete your LinkedIn profile is than your medical record. This next trend, we’ll go to you, Beth, and wanted to talk with you a little bit about patient engagement, and how you see that becoming part of m-health, and why patient engagement is so important.

Beth:
Part of the … making that digital care plan really work for the patient is having a really engaging piece of software to facilitate it or implement it. I think a really important part of that engagement is that it’s contextual. Maybe it’s … You enter a grocery store, and the service and your care plan knows that you are hypertensive, and it recommends what foods, what brands, what … where geographically in a grocery store to direct your shopping endeavors to facilitate the right exercise or … I’m sorry, the right nutrition plan for getting your blood pressure levels down. It’s all about knowing where you are, what you’re doing, and how to use that context to the advantage of your health. The face that we carry our smartphones with us everywhere, it’s the most ideal to do that.

Jon:
I’ve seen in your presentations before, Beth, that 99% of care is self-care, and the patient engagement, part of this is so critical because if you think about the medical community providing that other 1% of your healthcare, and then you’ve got the grand large majority of your time. You’re on your own. It really seems to me that patient engagement is going to be a pivotal part of making healthcare work in the United States in 2016 and going forward. For our final digital healthcare trend for 2016 and beyond, we’re going to talk a little bit about virtual helpers, that “digital health companion in your pocket,” we’re calling it. Beth, could you lay the groundwork for that? What’s a digital helper?

Beth:
When we talk about digital helpers, we’re usually referring to some kind of artificial intelligence, something that we can interact with in a very human way using natural speech ideally to get information, complete tasks, whatever it is that needs to be done.

Jon:
To be clear, this is what we have already if you’ve got an iPhone and you’re talking to Siri. This is what we mean by “virtual helper.” How does that service translate into the m-health realm? How does the digital helper facilitate health for patients?

Beth:
I think it can have a variety of impacts, and a lot of them, we’ve talked about so far in this piece. It can be things like making sure that you’re taking your medication, so it’s running some kind of a very human reminder, so that will help with medication adherence. Something else might be more like providing education that’s relevant to you at a certain time or place. It might even help convey information that’s relevant to you like say that you’re asthmatic and the pollen count is fairly high today. It might either verbally let you know that or through some kind of ambient measure convey that information to you without really being obtrusive in your life.

Jon:
Terrific. That sounds like that would be extremely helpful to me during the pollen season, so I look forward to some of those services booting up. Listeners, remember that while you’re listening to the show, you can follow along with the things we’re mentioning here in real time. Just head over to thedigitalife.com. That’s just one L in thedigitalife and go to the page for this episode. We’ve included links to pretty much everything mentioned by everybody, so it’s a rich information resource to take advantage of while you’re listening or afterward if you’re trying to remember something that you liked.

If you want to follow us outside of the show, you can follow me on Twitter, @jonfollett. That’s J-O-N-F-O-L-L-E-T-T. Of course, the whole show is brought to you by Involution Studios, which you can check out at goinvo.com. That’s G-O-I-N-V-O.com. Just a reminder, if you liked what you heard today, you can check out the piece online at mobihealthnews.com and look for “Digital Health Services in 2016 and Beyond.” That’s it for episode 138 of The Digital Life. I’m Jon Follett, and we’ll see you next time.

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