With over 50% of Americans developing 2 or more chronic conditions by the year 2030, it is now more critical than ever for robust data acquisition from the patient’s home setting.
Traditional telehealth solutions just replicate “more of the same” inherent in the clinical setting. Over two-way video, clinicians ask patients for point-in-time readings or even manual data entry histories rather than using the precious time to proactively respond to patient needs. This approach often provides a distorted perspective that lacks contextual information and is not representative of a patient’s actual state. The phenomenon of “white coat hypertension” is a well known example of this.
Virtual care provides a more transformative path forward. By integrating continuous and trusted data from the home, clinicians can gain access to crucial biomarkers and functional markers; both of which can inform the patient’s health status course of treatment. By focusing on passivity of data collection, clinicians have the ability to make inroads to solving one of the most bedevilling issues in virtual care: patient compliance and adherence. And most importantly, since data from the home setting can now be acquired relatively inexpensively, this approach will open opportunities for care regardless a patient’s means or ability with technology.
Over the past decade, the rise of consumer and FDA-cleared devices has led to a wealth of patient data including both biomarkers and functional markers of health.
Primary biomarkers include more traditional patient vital signs, whereas functional markers include sleep quality, behavioral data, and activity tracking providing a rounded picture of a patient’s health.
By integrating continuous markers of health, all acquired through home-based or wearable sensors, combined with a patient’s EHR history and social determinants of health like socio-economic status, access to transportation, and caregiver context, a more nuanced and accurate perspective emerges on health status and risk. In turn, this will enable clinicians and patients to:
- Act virtually. Giving clinicians the confidence to take clinical action - virtually - a good example of which is timely and temporal medication titration according to Guideline Directed Medical Therapy (GDMT). Given that only 1% of heart failure patients are on GDMT at any given time, the need for this is critical at scale.
- Act proactively. Giving clinicians the ability to risk-stratify patients based on need and provide the right level of care at the right time.
- Act Independently. Giving patients the tools to self manage, set goals, and take charge of their own health as continuous data informs their health and lifestyle choices.
Amongst the larger barriers to capturing continuous and contextually relevant data from the home is user adherence and compliance. According to some insiders, after the first 30 days, only 30% of FitBit users are still active. This kind of engagement decay, and resulting data loss, will not ‘cut it’ if meaningful clinical benefit is to be derived.
Data-driven virtual care ought to take a different approach; focusing on both passivity of data collection and simplicity of use. Sleep sensors and smart rings are often described by patients as “set and forget” due to their passive user experience. By curating the best consumer and FDA cleared devices together, virtual care providers foster a consumer grade setup process that appeals to all ages and types of patients.
When implemented in practice, the results of employing frictionless devices like sleep sensors are impressive. For instance, Mercy and Myia report that 80% of the patient population provides data on a daily basis in an ongoing chronic care program.
According to Nature, approximately 30% of heart rate data from wearable sensors, when comparatively examined, presented inaccuracies due to activity changes. These inaccuracies can especially become an issue if clinicians only have access to point-in-time data from one home device or sensor.
And yet, having a multitude of rich data sources, all from a controlled context, will foster more trust in data amongst clinicians. Integrating nighttime data from a sleep sensor, daytime data from a wearable device, and other relevant contextual information like social determinants of health allows clinicians to better understand the why of what they are viewing and how to address it within the perspective of the patient’s condition.
Historically, continuous data acquisition from the home was a luxury only available for the “wealthy well” due to both the cost of devices and a steep user learning curve. Unfortunately, this is directly inverse to patient need as low income Americans are more likely to develop chronic conditions like heart failure and diabetes.
And yet now, two significant advances, the reduction in cost of sensors and the growth of consumer-oriented user design, are enabling virtual care providers to meet patients where they are—regardless of means or ability with technology.
The cost of at-home sensors has significantly declined as much of the core technology is now commoditized. This has enabled providers with virtual care programs to include a robust mix of sensors and devices in the home.
The impact of this strategy can open up access to care like never before. Mercy Virtual’s home-based program has shown that 8 out of 10 Medicare-aged patients can set up a curated kit of sensors in about 10 minutes, without any assistance.
To see how Myia Health is building the operating system for data driven virtual care, please click here.
This article is part of a content series from Myia Health. Click here to read more.
Myia Health is the operating system for virtual care. Myia’s platform ingests a wide range of real-world data from curated sensors and sources, transforming it through applied machine intelligence into actionable and objective clinical insights. Myia equips clinicians with the precise information they need to both optimize care and prevent unplanned medical events. For more information, please visit: Myia Health.
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June 26, 2020 at 09:54PM
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Why Continuous Patient Data is the Key to Virtual Care - ModernHealthcare.com
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