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WEARABLE REMOTE MONITORING TECHNOLOGY –
MOVING FROM INNOVATION TO ADOPTION
According to a Frost and Sullivan report, the number of patients who are remotely monitored will grow
annually by 48.9% and reach more than 36 million in the next five years. In addition, AARP Health
Innovations@50+ ranks “vital sign monitoring” in its top three markets for health innovation technology.
Given these statistics, it is not surprising that there is both innovation and investment in remote
monitoring technologies to track multiple parameters such as respiration rate, pulse, hydration,
temperature or blood pressure, while incorporating patient-friendly features, such as small size, passive
measurement and unobtrusive design.
However, despite the interest, wearable remote monitoring devices have failed to gain traction among
healthcare providers in a significant way. This is partly because they struggle to deliver on important
features, like accurate measurement of key parameters, ease of use, clinical utility or even wearability.
But also they have yet to figure out how to integrate the data they capture into the healthcare
continuum in a meaningful and useful way. And finally, they are unable to conclusively prove significant
value to payers, which limits their adoption.
Certainly, wearability in an aging or ill population is an issue. Devices which adhere to or rub against the
skin can create skin degradation, particularly in a patient who has poor blood and oxygen flow, which
are common characteristics of the elderly and chronically ill. Small patches and wrist bands can be
difficult to don and doff, and are easily lost or misplaced, by patients with poor eyesight, memory and
dexterity. Dementia patients can potentially tear off adhesive patches or wrist worn devices.
In addition, parameter measurements must be accurate if they are to be used by a health care
professional. Newer technologies, in their rush to be small, unobtrusive, multi-parameter and high tech,
struggle to capture clinically accurate data in a patient who may or may not be obese, and who could be
moving or sweating or even turning frequently in a bed.
The data captured must also be clinically useful, which means it needs to be stored, analyzed and served
up to a provider in a way that he/she can use to impact clinical outcomes. For example, a basic scale,
equipped with a Bluetooth device which allows it to communicate to a home health nurse, has been
shown to capture early fluid retention in CHF patients, and allow simple interventions that prevent
exacerbation. It remains a challenge, however, to communicate vitals and metabolic data to busy
primary care practices with varied technology infrastructures in a way that they find accessible and
useful.
Perhaps most importantly, the business model for these technologies remains unclear. What is the
value of these technologies and how best to demonstrate that, and to whom? The costs of these
technologies will be weighed against the savings they create in the care continuum, and unless they can
prove economic as well as clinical value, they will not be reimbursed.

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For these reasons, medical device and diagnostic manufacturers should be wary about designing to
endpoints that are technologically intriguing but have little medical or economic value. Rather, in early
stage development of wearable remote monitoring technology for clinical use, they should be guided by
the 5 “P”s, Purpose, Patient, Parameters, Providers and Payers.
5P Analysis
 PURPOSE – What are the goals for the device and what are the key unmet needs in the
market/disease/patient population that it seeks to address? Is it to track specific parameters so that
they can be analyzed by the patient or the provider? Is it to track compliance with medication or
activities? Is it to alert the patient or provider to specific changes so that interventions can be
undertaken to prevent escalation of an event? Should it track location or position? A true
understanding of the most useful purpose of a device prevents both under and over-design errors,
and results in an optimal value proposition designed to meet the needs of the market.
 PATIENT – What are the patient’s capabilities and limitations? Is the patient a child or adult? Is it likely
that they will have vision issues, or mobility constraints or small motor limitations? Will discretion be
important? Will the patient be sedentary or active? It is critical that the design fit the patient, their
capabilities and their lifestyle to optimize both compliance and usability. Makers of software
designed for the elderly, for instance, recognize that the ability to double click with the index finger
diminishes over time, and therefore program alternative selection methods.
 PARAMETERS – What is being monitored and what level of frequency and accuracy is required for
optimal health and economic utility? Does the parameter need to be measured periodically or
continually? Is the tracking of concurrent events e.g., activity level or meals, required? The
parameters that are critical to include must be very well understood upfront so that measurements
and data capture support the optimal purpose of the device.

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 PROVIDERS – Provider input is essential for clinical adoption, and often overlooked. An understanding
of how the data can best fit within the provider’s practice, level of training, treatment paradigm and
technology resources is key to designing both the device and the surrounding analytics and service.
First, it is crucial that the data, and particularly the analytics, meet the providers’ criteria for
optimum clinical utility. Do they want a longitudinal analysis at regular intervals, or do they only
want it for use during a patient visit? Or do they just want an alert so that they can intervene before
a patient’s condition worsens? Is the data for use by the physician, or by the nursing staff, or both?
Should it feed into an EMR? All of these are important decisions that can make or break a device’s
adoption by providers. And finally, manufacturers of devices need to understand the varied
technological infrastructures of the provider landscape so that they pre-resolve issues around
compatibility and interoperability, and comply with both accessibility as well as privacy
requirements.
 PAYERS – Wearable remote monitoring devices must demonstrate the value of their technology to
payers. This means developing the business case by proving the ability to reduce specific hard costs
like hospitalizations, ER visits, medications and other interventions, and then setting the price to
optimize adoption. The payment hurdle is significant. Traditional payers have shown little interest in
reimbursing wearable remote monitoring; CMS for instance slashed reimbursement by over 30% for
remote cardiac monitoring in 2009 and has only recently allowed it to creep upward again. Further,
in post-acute settings like skilled nursing and home health, where remote monitoring has the
potential to supplement over-stretched labor, margins have fallen precipitously and any additional
cost is severely scrutinized. Without compelling health economic evidence, traditional payers as well
as evolving payer-provider organizations will continue to resist funding these technologies.
In the end, wearable remote monitoring devices will not succeed because they are novel, small, multi-
parameter, Bluetooth or non-invasive. They will only gain adoption and revenue if they are based on a
strong clinical and economic value proposition derived from a deep understanding of the optimal
purpose, the patient, the parameter(s) requiring measurement, the providers and the likely payer.
Catherine Ellis Anne Smart
Director Director
212 901 6928 212 901 694
catherine.ellis@navigant.com anne.smart@navigant.com
navigant.com/LifeSciences