Behavior Change, Chronic Condition Management, Foundational Health Behaviors, Health Outcomes, Health Plans, Health Research, Health Systems, Partners, Personal Health Technology | By | 06/08/23 | 5 Minute Read

Connecting the Dots on Value-Based Care

Every second, an exponential amount of healthcare data is generated. Healthcare represents as much as 30% of the world’s data volume – more than manufacturing, financial services, or media and entertainment. And with it come endless new opportunities to better understand and act on both individual and population-level healthcare trends.

But here’s the thing: data is only as useful as the insights that can be derived from it. So while providers face a deluge of data, they’re not yet equipped with effective tools to access and analyze that data to actually move the needle on their patients’ health. Meanwhile, payers and those responsible for intervention programs find it difficult to accurately predict risks or see trends of patients and populations, hindering the adoption of a more proactive approach to healthcare – like value-based care (VBC).

The healthcare industry needs a better way to collect the right data and analyze it, one that helps forge a path to better health outcomes. That’s a tall order, but it’s one that can be solved by something that more than a fifth of U.S. adults are already using: consumer wearables.

I recently wrote about why I’m optimistic about the future of VBC. As the next step in this series, I’m focusing on specific use cases that show how consumer wearables can play a role in VBC. To kick us off, I want to talk about the opportunities data presents to derive meaningful insights for personalized care, preventative care, and population-wide health.

The push for personalized care

Successful value-based care depends on close collaboration between patients and their care teams that goes beyond a once-a-year health snapshot. We know that 80% of chronic conditions such as diabetes and hypertension can be managed through lifestyle changes. Critical to successful health outcomes is supporting these changes by understanding patient health on a day-to-day basis.

But here’s the disconnect: It’s difficult for payers, providers, and health systems to educate patients and engage them with their health on an ongoing basis. It’s just not what our current system is set up to do, with patient touchpoints that are episodic and infrequent at best.

The result of these infrequent touchpoints – and the moment-in-time data they provide – is generic, one-size-fits-all advice, like “Eat better” and “Move more,” that comes across as vague and impersonal, and therefore difficult to act on. And the research bears this out: 85% of consumers want more personal engagement with their providers.

For value-based care to succeed, patients and providers need a better, easier way to get on the same page. Rather than piling doctors with more data, we need to deliver real, patient-generated insights based on data that’s already been analyzed. Bringing those insights into the conversation means being able to give more personalized guidance that’s both user-friendly and actionable.

Beyond the raw numbers: The future is trend-spotting

Health and wellness data from wearables is less about what an individual did yesterday or last week, and more about spotting trends into the direction we’re headed over time so we can take action and adjust lifestyle.

My doctor doesn’t care if I walked 10,000 steps yesterday. But my doctor would take notice if I averaged 10,000 steps each day last year, and my trend line is now half that. Or that my resting heart rate once averaged 61 bpm and now it’s consistently higher or lower. These are changes in my health indicators that could prompt a deeper and more valuable conversation.

It’s similar to the way financial apps like Mint changed the way people viewed and understood their finances. Mint didn’t increase your salary, but it did visibly illuminate spending habits over time and paint a larger financial picture. Sure, you could get down to the granular, but the benefit was in the trend line – that’s where people could really start to see if they were on track to meet their financial goals, and identify where there was room for improvement.

In the same way, health data from consumer wearables provides the catalyst to take everyday health and wellbeing metrics and connect them to personalized healthcare guidance. And not just at the individual level.

Tracking key health indicators with wearables can provide population-level data on real-time health trends as they develop. Then, machine learning and AI can turn that raw data into insights. Beyond an overall snapshot of your population’s health, you can also dig deeper into what’s happening with particular segments to identify gaps in care, predict future trends, and inform care interventions. And there’s much more on the horizon for health AI to fully realize the potential of technology in healthcare.

In one study of cancer patients, lower physical activity levels during inpatient recovery were associated with higher risk of hospital readmission. That tells us something tangible about how to better inform care interventions with that population moving forward.

Here are three more examples of how data analytics can be used to gain population-level health insights that can lead to better engagement and better health outcomes.

  1. Precisely target at-risk groups: Data can be used to focus intervention resources on members or subgroups of patients who need the most support. For example, out-of-healthy-range indications can be visualized through user-friendly graphs and actionable insights, making it far easier to focus interventions on the most at-risk members, at the right time.

  2. See and address the gaps: Resources are always limited, which is why it’s critical to know which gaps in care need to be addressed first and which cohort of people would benefit most from being included. Collection and analysis of today’s wearable data gives program designers a complete view of month-over-month trends in areas such as sleep, activity levels, and heart rate – just to name a few. This in turn enables plan managers to build more timely and relevant preventive health support programs.

  3. Broaden engagement: To improve quality measures, health plan and program designers need to know what members of their population are engaged with and where they need additional support. Armed with this information, you can tailor intervention strategies according to population trends.

The future of healthcare is personal and predictive

As healthcare moves to a value-based model, the user data generated by wearables like Fitbit devices provides significant opportunities for payers and providers. By leveraging a simple solution that’s already on people’s wrists, providers can offer more actionable and personalized guidance that’s informed by a person’s day-to-day life. Taken a step further, there’s a clear opportunity to dig deeper into health data on a population scale to spot health trends as they form, hone guidance, and better predict health needs of patients en masse.

To be clear, wearables are not a cure-all to the challenges we face in healthcare – no one single thing is. But they can be used to analyze program impact and unlock insights for a far more complete view into a population’s health and wellbeing. That’s a crucial step toward a more effective and efficient healthcare system.

Looking for more resources on value-based care? Check out our new white paper, Consumer Wearables in Value-Based Care.

EMIDS Healthcare Summit

11/1-11/2 | NASHVILLE, TN