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The Challenges of Monitoring Pain Remotely


Most remote pain monitoring studies lack context for the data they collect.

mhealth,population health,remote pain monitoring,pain monitoring wearables,health care analytics news

Healthcare has more resources than ever for remotely monitoring patient conditions, but the usefulness of those resources depends on how they are designed and used. A new literature review identified several challenges that researchers should address if they want accurate insights on patient pain.

The research team, from Chile and the United Kingdom, examined 53 studies that focused on the use of pain-monitoring technology systems. 70% of included studies monitored pain using wearable user interfaces like mobile phones, accelerometers, gyroscopes, and garments for tracking electromyography signals.

Researchers noticed a widespread lack of patient feedback and understanding. While the monitoring technology used to research pain usually sends data back to individual research teams, many devices do not give patients insights into their own triggers and pain patterns. This can prevent them from adjusting their behavior to mitigate discomfort.

The authors posed that policy may have something to do with this. “Medical-grade health monitors that can provide feedback to patients are rigorously tested and highly regulated, which results in slower adoption of new features.” They hypothesized that this may lead studies to instead opt for commercially available consumer-grade monitors that don’t provide feedback.

For better studies, they emphasized the need to focus on context. Contextual factors, from diet and mood to temperature and humidity, influence pain. Sensors used to monitor patients don’t always reflect that. Although some sensors can monitor humidity or pollution levels, for instance, they are typically not present in the devices and applications that monitor pain responses.

Across the reviewed studies, the researchers found 49 types of contextual information that may be important to consider. From those, they created a 5-dimension model to analyze the existing research on:

  • Activity (whether the study required patients to complete specific physical or mental tasks)
  • Identity (information like a patient’s ethnicity or personality)
  • Wellness (things like a patient’s comorbidities, disabilities, and quality of life)
  • Environment (factors like noise, music, food, and social support)
  • Physiology (other measurable metrics like heart rate and blood pressure)

Although the studies typically gathered this information in the survey or questionnaire stages, remote monitoring devices seldom tracked it, researchers found. But half of the studies tracked physiology. The authors noted that some metrics like mood cannot be monitored with sensors, which would require patients to input that data through a device interface.

Another major challenge was that patients may not always know how to use the devices. This becomes a problem when attempting to monitor pain in their day-to-day lives without assistance. Users with low digital skills or cognitive impairments may be more difficult to study for this reason.

Little existing research investigated pain monitoring in seniors, who often have more pain and less tech literacy. The authors encouraged the industry to explore ways of developing devices for such users, and creating ones that are “esthetically adequate for social activities, and require low amounts of interaction.”

The review, “Understanding Monitoring Technologies for Adults With Pain: Systematic Literature Review,” was published recently in the Journal of Medical Internet Research.

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Craig Newman
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