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HOW CONTEXT & CONNECTIVITY CONTRIBUTE TO A FULL PICTURE OF HEALTH

Citation: Vázquez E, “How Context & Connectivity Contribute to a Full Picture of Health”. ONdrugDelivery Magazine, Issue 76 (Jun 2017), pp 14-16.

Erika Vázquez shows how recent technological advances make it possible to gather detailed contextual data about patients and gain true insights into whether their treatments are genuinely improving their quality of life.

“A cardiogram takes six seconds to acquire, but there are 86,400 seconds in a day. Today’s technology provides the opportunity to examine those other 85,394 seconds…”

In a study evaluating the effectiveness of a drug designed to control heart rate, monitoring a subject’s pulse over a period of time will undoubtedly help answer the primary question: is the drug effective at controlling the patient’s heart rate?

While the answer to that primary question may be yes, researchers must consider what else happened while the patient was being treated with the drug. Perhaps the subject’s heart rate was well controlled, but the subject became more sedentary and less active. Or perhaps the subject experienced increased restlessness during sleep. The heart rate might be controlled, but that doesn’t mean the treatment is successful. Without the surrounding contextual data, comprehension of a subject’s response to treatment is incomplete.

As the US healthcare system becomes increasingly outcomes based and accountable, evaluating therapeutic efficacy requires researchers to consider the bigger picture of a subject’s health. In the past, the data available to a physician was limited to the information that could be gathered through a patient history, physical exam, and lab tests. An evaluation of health was limited to a snapshot of one tiny moment in time. For example, a cardiogram takes six seconds to acquire, but there are 86,400 seconds in a day.

Today’s technology provides the opportunity to examine those other 85,394 seconds to find the problem. With the help of wearables and novel data-capture tools, we can now look at efficacy over time as we observe the patient in their daily life (Figure 1). These healthcare data collection devices provide a much more accurate and complete assessment of compliance and medication efficacy. The modern day ability to look at a patient’s data within the context of their own natural habitat, for example their work, school or home settings, provides a level of validity that simply is not attainable in the artificial environment of the doctor’s office.

From academia to pharma, wearables are providing robust physiological data to reach study conclusions. As Validic (Durham, NC, US), a provider of digital health data analysis solutions, points out, activity and sleep data collected by wearables1 can help trial sponsors to “uncover important patterns such as a participant being less active on days that a medication dose is missed or a participant sleeping more after taking the medication, indicating drowsiness as a possible side effect”. This contextual data also serves as a “useful indicator of behavioural health, providing researchers with a more objective means to understand how a participant may be feeling while taking a drug”.

In Pfizer and IBM’s Project Blue Sky Initiative to study Parkinson’s disease progression with wearables,2 multiple metrics matter. “IBM and Pfizer aim to get a more holistic view of the patient by measuring a number of health metrics, including motor function, dyskinesia, cognition, sleep, and various daily activities,” MobiHealth News reported.

Figure 1: With the help of wearables and novel data capture tools, we can now look at efficacy over time as we observe the patient in their daily life.

When mobile apps and wearables are used as complementary tools in research studies, the full potential of connectivity and context becomes attainable. Apps encourage compliance through reminders and can easily collect subjective data from study participants, providing the context to understand fully the targeted and accurate physiological data wearables capture.

“Activity and sleep data collected by wearables can help trial sponsors to “uncover important patterns such as a participant being less active on days that a medication dose is missed or a participant sleeping more after taking the medication, indicating drowsiness as a possible side effect…”

Oklahoma State University (Stillwater, OK, US) researchers evaluated the feasibility of a novel methodology for assessing “physiology, behaviour, and psychosocial variables”. The study used two objective sensors (a BioHarness (Zephyr, Annapolis, MD, US) and a wActiSleep- BT monitor (ActiGraph, Pensacola, FL, US)) and a mobile app to monitor each subject’s daily routine over a 20-day period.3 The results suggested that wearable sensors combined with ecological momentary assessment technologies (in this case, app questionnaires) are capable data-generating tools for developing “dynamical systems models of high value health behaviours such as sedentary activity, moderate to vigorous physical activity, sleep, and diet”. Additionally, results indicated that “a wearable sensor holds promise for linking subjective feeling states with physiological data and has the potential for informing intervention development”.

Takeda USA (Deerfield, IL, US) and Cognition Kit (a joint-venture between Cambridge Cognition (Cambridge, UK) and Ctrl Group (London, UK) are “collaborating on a study to assess whether mobile apps and wearables with continuous monitoring capabilities can be used to glean new insights into major depressive disorder4 that could drive better treatment.”

The Cognition Kit app collects physiological data and evaluates cognition. MobiHealth News explained that the study aimed to “use continuous monitoring to catch underrecognised symptoms of major depressive disorder, thereby providing a more holistic view of the user’s mental health”.

For GlaxoSmithKline’s clinical trial leveraging Apple’s ResearchKit to study rheumatoid arthritis,5 the company focused on “asking patients the right questions”. GSK Chief Medical Officer Murray Stewart told Clinical Leader, “Carrying that a step further, we also know rheumatoid arthritis patients can be prone to suffer from depression. Designing questions that deal with depression can also be recorded on the app and allow researchers to better understand the patients and data. This will help researchers to get a more holistic view of the health of a patient.”

By utilising mobile technology and wearables, researchers gain a comprehensive overview of subjective and objective data that was previously unattainable. Success is no longer measured by assessing if drugs and procedures do what they are supposed to, but by measuring whether or not the patient is better for it. Evaluating contextual data helps to measure therapy success through the lens of quality of life.

This article is based on the author’s March 2017 blog item “The Value of Contextual Data in Health Monitoring”.

REFERENCES

  1. Plumer J, “Wearables in clinical trials: it’s about correlation and context”. MobiHealthNews, Oct 10, 2016.
  2. Pai A, “Pfizer, IBM partner to create wearable sensors system to study disease progression in people with Parkinson’s”. MobiHealthNews, Apr 7, 2016.
  3. Brannon E et al, “The Promise of Wearable Sensors and Ecological Momentary Assessment Measures for Dynamical Systems Modeling in Adolescents: a Feasibility and Acceptability Study”. Transl Behav Med, 2016, Vol 6(4), pp 558-565.
  4. Mack H, “Takeda and Cognition Kit partner for Apple Watch-based study on depression”. MobiHealthNews, Feb 27, 2017.
  5. Miseta E, “GSK Uses Apple ResearchKit in Rheumatoid Study”. Clinical Leader, Feb 21, 2017.

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