Understanding the Value of Integrating Patient-Generated Health Data Into Practice

Drew Ivan, chief product and strategy officer, and Jessica Nisenbaum, chief people officer, both with Rhapsody & Corepoint, discuss the benefits and challenges of introducing patient-generated health data into practice, and explain crucial moments and concepts throughout the transition process that health executives should look out for.

Transcript:

Drew Ivan:  Hi, I'm Drew Ivan, I'm the Chief Product and Strategy Officer with Rhapsody and Corepoint.

Jessica Nisenbaum:  I'm Jessica Nisenbaum, Chief People Officer with Rhapsody and Corepoint.

Drew:  Patient-generated health data is kind of a new concept in health care. Previously there was really no method by which patients could easily generate or capture their own health care or any kind of data that they wanted to contribute to their health care record.

Now with the advances in technology, we're starting to see a lot of different ways of patients being able to capture things like fitness data, electronically and automatically, but also things like their own notes about reactions to medications, or other notes that they would like to put in their medical record.

That's kind of the state of the art of patient-generated data at the moment. It's come a long way in recent times.

Jessica:  I think the real value is it empowers individuals to make better decisions about their care and take their care into their own hands, working more collaboratively with their care team. Whether that's their provider or other specialists that they work with, having the data allows them to really make better clinical decisions for themselves.

Drew:  Yeah, they can be more of a participant than a subject of the health care.

Jessica:  I think the use of patient-generated health data is increasing significantly for a variety of reasons. It's the culmination of all the technology available, whether it's wearables, or more access to in-home diagnostic tools that generate data that we can share with our clinicians.

Also, there's just a lot of market pressure right now for the data to be used in more meaningful ways to drive better clinical outcomes across the health care system, both for individuals at the macro level to solve chronic care conditions and other more global issues that are impacting our health care system.

The ability to gather the data, aggregate the data, analyze the data, informs a variety of solutions that actually are having real clinical and financial outcomes that are impactful from an economic perspective if nothing else.

From an employer perspective, they're watching year over year as health care costs rise, and our ability to provide wellness initiatives to our workforces, increases significantly the ability to have data that will help inform that in a way that will drive health care costs down, is significant.

The more that we can leverage the patient-generated health data to reduce those costs, allows businesses to funnel that money into something more meaningful. There's just a dramatic pull for and the need for that data.

Drew:  That's a great point, and the other thing I like about it from a technology standpoint is that previously, if for example, if a doctor wanted to know if the patient was regularly taking their medications, for example, they would ask the patient.

That's really the only way they had to get that feedback of whether the patient was taking the medication, which may or may not be a reliable report. If you could instrument the pills themselves, or the pill bottle to be able to report electronically when the patient took the pill, then you can get a much more accurate and unambiguous report of adherence to medications.

It's good for the patient, because it helps them put them at the center of their health care, but it's also good for the health care practitioners because it gives them a more accurate, more quantitative view of what's going on with the patient.

Jessica:  I think it also can reduce time and cost when you're sitting with your clinical provider. Having the data readily accessible and accurate in a way that can develop a more sort of collaborative approach, developing a care plan for an individual obviously has more value as well.

As people are getting more and more exposure to the data, understanding how to use it, getting more clinical value added to it, there's just more and more of a demand for it, and it's actually being used to simplify health care for people and reduce costs at the same time. It's a critical need.

Drew:  It really leverages the health care providers as well, because instead of checking on the patient maybe every three months when they come in for a check-up, a case manager can watch an entire panel of patients to make sure everybody's taking their pills every day, or their blood pressure is on track, and they get real time data and they can intervene much quicker. They have that view of the patient all the time.

Jessica:  I think about all the apps I have on my own personal phone, all this data that I'm generating that may or may not share with a clinical provider that can add clinical value to it, I have it. I have access to it, that makes me excited about how I can leverage it to do something more impactful in my own personal world.

As I think about the value of that to the people around me, and the value of me having that data for the people I care about around me, and as we start to see trends increase in how comfortable people are sharing that data with one another, and with their providers, there can only be good that comes from that.

The clinical value of being able to put the knowledge and the clinical decision-making tools in the hands of the people can actually impact care at the point of care is only going to become more and more important to our health care ecosystem.

Drew:  As patient-generated data becomes more popular, and becomes combined with the health care providers official clinical records, it starts to open new technological problems that the providers may or may not be equipped to handle. One of the problems is that the patient-generated data often doesn't have a standardized format.

Health care systems are pretty good at moving data around when there is a known data format that can be handled efficiently by existing tools, but a lot it, especially like fitness apps, consumer apps, don't have or don't adhere to a very rigorous standard that health care systems are used to consuming.

That doesn't mean that the data can't be used, or can't be incorporated, but it does mean that it may be a harder task, and it requires a different skill set. You have to evaluate whether the integration teams that are available are able to handle that.

It's not just another data source that you have to incorporate the same way another clinical data source would be represented, it's really a completely different style of data format, it's also a different volume and velocity of data.

If you think about something like heart rate data, that might come 10 times a day, and it's a small packet of information. If you think of something like an EKG that's a much bigger packet of data, but it comes on a different schedule, maybe once a month.

You're getting data on a different schedule, different sizes, and different data format, and that introduces variability and therefore complexity to the integration problem. Executives should be aware that patient-generated data is probably inevitable, so they should prepare their strategy as soon as possible, to be able to handle it.

The outcomes are so much better by combining patient-generated data with clinical data, it's going to lead to better clinical outcomes, better cost outcomes, and as a result, it's going to be inevitable, therefore executives need to start planning now for what data they're interested in, what their policies will be around acquiring and retaining that data, and exactly how they want to use it as part of clinical programs.

Those are problems may be for the chief information officer, the chief medical officer, or if they have a chief nursing officer or chief medical information officer, those would all be good executives to be involved in this kind of strategic discussion.

There's a lot of challenges with integrating patient-generated data. We already talked about a lot of them with respect to the data formats, but really one of the biggest challenges is going to be just the paradigm shift for providers.

Providers are used to generating a fairly small amount of data on a routine office visit. They take a blood pressure and temperature, maybe height and weight, but really if a patient is measuring their own data on a continuous basis, that introduces quite a bit more data.

There needs to be new methods and tools for filtering through that data to look for the exceptions and the outliers, because reviewing tons of data is hard, and that's not something that clinicians are going to do. They need to have their attention drawn to the parts of the data stream that need their attention.

The paradigm shift of figuring out how to handle this data, what to do with it, and how to turn that into better outcomes, is I think the biggest challenge that we'll be addressing.

Jessica:  I think beyond that too, it's sort of a thought process shift in where we've been. The provider market really has focused so much on transactional issues and responding to acute care conditions and accurate care situations that the prevalence and rate of chronic conditions are growing across the world.

The need for massive amounts of data on an aggregate level, but also massive amounts, as Drew says, more on the individual level as we generate more and more patient-generated health data with devices that we can leverage regularly, just massive amounts of that data and how it's going to get leveraged and looked at to solve these clinical problems is huge.

I also think that as it gets constructed, and as it gets aggregated and analyzed, there's other complexities to that, and ensuring that data, we have to be prepared for how that works.

Drew:  I think integration of data is important for clinical care for a lot of reasons. The reasons that we've traditionally thought of, is that the data should follow the patient on their journey through the health care system.

Because that data represents what's going on with the patient, and therefore any discontinuity in the data flow represents potential hand-off error as the patient goes through the health care system.

For example, if a patient is discharged from a hospital and goes into long-term care, if that care summary or discharge instructions has to be printed out and sent with the patient, that's an opportunity for it to get mishandled, lost, or misread.

Whereas if it's electronically transferred, it can go straight from one organization's record keeping system to the next, and that improves the care. That's what we're used to focusing on. As patient-generated data comes into play, that actually extends the integration problem outside of the health care system, and into the consumer system or into actually the patients' homes.

You can begin combining lots of things, not just health care data, but all of their other data that they generate as part of living a digital life, into their overall care plan. Things like figuring out how active they are, where they're going, when they're going, what their eating and sleeping habits are.

These are all things that can get rolled into the overall patient profile and leveraged to produce better outcomes. We don't know how to do that yet, nobody's really tried as far as I know, but for sure one of the foundational technologies to enable that, will be getting the data into a single place. That's where interoperability comes in.

Jessica:  Then being able to share it beyond just the individuals themselves, with their family members, and their employer, so that those other people invested in their care and in their clinical outcomes can help leverage the data in ways that will also solve clinical outcomes and provide health and wellness benefits.

Drew:  So far we've been talking about almost like individual units of patient-generated data, which can help in a lot of scenarios, but we haven't really talked about is getting all that data into one place and then doing analytics on it, because big data is kind of the short-hand answer for how do we take what we've learned through all of these new inputs that we have, and use technology itself to figure out some insights about the patterns that are in that data, that may not be obvious to a human reader of the data.

It's not just a concern with individual patients, it's really, it can turn into a way for health care itself to learn about entire populations of patients based on the data that's collected across the population.