COVID-19 has brought a decade of change to telehealth and virtual care in just a few weeks. According to consulting firm Frost and Sullivan, telehealth visits are expected to grow from 36 million last year to over 200 million by December of this year. And the telehealth market in the United States is estimated to grow seven-fold by 2025.
While telehealth brings an upgrade in consumer grade convenience which is long overdue in healthcare, simply shifting encounters to a virtual setting replicates “more of the same” - a traditional healthcare model gone mobile. Forward thinking providers can seize this moment and fundamentally seek transformation through virtual care.
Whereas telehealth is reactive and episodic, virtual care is preventative, continuous and personalized, whereby the goal is matching the right level of care to the right patient, at the right time.
Results of this transformation to virtual are compelling. Mercy Virtual, the “world’s largest hospital without beds,” has reduced hospital admissions and ER visits by more than 50% for complex patients living with chronic disease by transforming care and workflows to a more continuous and preventative approach.
To meet this transformational imperative, providers need to develop fundamentally new capabilities.
In the traditional in-person setting, patients may spend a few minutes with their clinician per visit and receive a point-in-time reading of their vital signs.
Telehealth replicates this experience with clinicians asking patients for point-in-time readings from at-home devices like blood pressure cuffs or pulse oximeters.
But health systems looking to leverage the full capabilities of telehealth technology shouldn’t be replicating this in-person experience, which has numerous inherent flaws.
First, this approach may provide distorted data that is not representative of a patient’s actual state, e.g., white coat hypertension, diurnal nuances.
Further, while readings from consumer devices like, say, an Apple Watch or a Fitbit have the potential to be valuable and are being integrated more and more into clinical systems, they can also introduce “contextual contamination”, rendering data useless or spurious. For instance, a clinician or system may mistake abnormally high heart rate readings for distress when the patient was really just walking up a flight of stairs.
Virtual care, when integrating continuous data streams from the home, offers a more transformative path forward. Primary biomarkers like heart rate, respiratory rate, and others, when continuously collected with discernable context, can provide significant predictive value on a patient’s temporal health status. More importantly, these primary biomarkers can now be collected quite easily with non-invasive devices thus rendering issues around patient access or means with technology less challenging.
Additionally, functional markers of health like sleep data, engagement data, social determinants, and even environmental context all provide clinicians with a whole viewpoint on any given patient. Tying this data together creates a true opportunity for both preventive and personalized patient care.
Traditional telehealth has no capacity, in both experience design and system architecture, to make sense of the deluge of data from the real world. Even more so, a basic telehealth model struggles to adapt and learn from each new patient interaction, as the learned knowledge from each patient interaction is effectively lost when clinicians press “end call” after each session.
Virtual care provides us with a transformative path forward.
Through the application of machine learning, virtual care can make sense of this deluge of real world data. Machine learning can parse and organize complex multivariate data requisite to understanding patients with complex chronic conditions. It is an absolute necessity to ensure these new streams of data have maximal utility and minimal noise.
Second, it can effectively “learn” from each interaction, becoming more nuanced and skilled in its recommendations to clinicians as it achieves more scale in patient interactions and clinician actions. This “network effect” in value is more commonly seen in consumer applications but will enter virtual care for the first time as machine learning achieves more scale.
And third, it can provide clinicians with the transparency into the underlying inputs and drivers of risk assessments and recommendations that they need to feel confident in a system derived recommendation.
Telehealth per se does not address one of the most pressing problems facing medicine: the time stress and burden of technology. EHRs and other systems add time to clinicians’ work day, prevent clinicians from practicing top of license, and drive what’s commonly known as “Alert Fatigue.”
Virtual care presents us with the opportunity to create technology that’s in service of clinicians; not the other way around.
“It must fit into the existing workflow” is a traditional and popular healthcare mantra. This is misguided in a world of preventative virtual care.
Employing virtual care technology, clinicians can automate and orchestrate actions, parallelize encounters via asynchronous communication, and develop personalized care protocols and plans.
Virtual care will allow surface actionable information when and where it counts or is critical to the on-going patient care. Ultimately, technology can be clinicians’ friends rather than an administrative burden, unlocking more personalized levels of care at greater scale and efficiency.
These changes can have significant implications on the practice of medicine.
First, it can shift time back to clinicians. Rather than spending time on their screens inputting data (currently about 2:1 ratio to patient time), clinicians would be able to spend more time in patient interactions.
Second, it would allow clinicians to practice at the “top of their license” by exchanging administrative busy work and routine visits for deep thought with their most complex cases and rewarding clinician / patient dialog that fosters prevention.
For more information on how to transform your practice as you make the shift to virtual, please visit Myia Health.
This article is part of a content series from Myia Health. Click here to read more.
Myia Health is the operating system for value-based 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 11, 2020 at 10:00PM
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Virtual Care: The Transformational Change Agent This Moment Demands - ModernHealthcare.com
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