People are increasingly turning to digital health devices to monitor their health daily, thanks to the ubiquity of cellphones. More than 95 percent of the U.S. population owns a cellphone, and more than 77 percent owns a smartphone. These tools allow the direct capture and transmission of health data from individuals in their everyday environments across geographic and socioeconomic backgrounds. Sensors embedded in smartphones, Fitbits, Apple Watches and phone-tethered glucometers collect the data and transmit it via Wi-Fi or cell services. Mobile health (mHealth) apps and text messaging enable individuals to return survey data to researchers in real time. Sensors in the environment can monitor homes for temperature, particulate matter, light exposure and so forth. Perhaps most important, these tools capture data over time, which provides valuable insights into the health of individuals involved in a treatment regimen or research projects. Nevertheless, the usefulness and utility of mHealth apps and wearables in clinical practice is still emerging. Validity and utility of these devices vary, and their integration into electronic health record (EHR) systems is happening only gradually.
The most popular wearable devices are activity trackers. Consumers use them to track steps taken in a day, distance traveled, exercise intensity, sleep-wake states and so on. Of the 200 devices on the market today, the most popular are the Fitbit and Apple Watch. These devices are generally considered reliable and valid for everyday consumer use as well as for research purposes. Other devices that claim to measure blood sugar and take electrocardiograms, such as the Helo, should require U.S. Food and Drug Administration (FDA) oversight and validated results.
Systematic reviews and meta-analyses in the literature suggest that these wearables have small positive effects on physical activity and weight loss. Health benefits of these devices for sleep are still being determined, though. Newer activity trackers have additional embedded sensors such, as the new Apple Watch Series 4, which has the ability to take an FDA-approved electrocardiogram. Since 2017, AliveCor has had an FDA-approved phone-tethered electrocardiogram on the market as well.
While activity trackers may be some of the most popular devices, there are many others. Cellular- enabled scales for measuring body weight, for instance, transmit data for patients losing weight or those with congestive heart failure who need to track fluid retention. There are more than 25 phone-tethered glucometers and 50 such blood pressure monitors for patients with diabetes or hypertension. The market also includes oxygen saturation monitors, medication trackers, sun exposure monitors, smart asthma inhalers, seizure detectors and more.
These digital health tools hold much promise to improve health outcomes and care delivery. However, the landscape is quickly evolving as new devices make it to the marketplace in record time. As the competition to create the next best device heats up, companies in business today may fail tomorrow. For example, companies that manufacture fitness trackers are going head to head to see which can command the lion’s share of the market, which is crowded with big-name technology firms such as Microsoft, Apple and Fitbit. It is not easy for consumers to compare the devices; they vary in design, communication platforms and price. However, the competition may serve to drive down prices, which is good news for consumers and researchers alike.
Just as consumers must evaluate these devices, researchers must also examine the differences in features and hidden costs. Data quality, validity and format vary across every device and app. Further, access to data varies by company and can come with a price. For example, companies such as Fitbit only give a certain granularity of data back to users unless consumers or researchers pay for access. Laboratory-grade devices produced specifically for research purposes by companies such as ActiGraph can be expensive, though they provide granular data.
As the number of digital health devices grows, concerns about privacy and security grow as well. The devices are vulnerable to hacking, and some popular tools put sensitive consumer data at risk by sharing it with third parties. The FDA also considers some devices “mobile medical apps” that fall within its oversight. In short, anything that is a diagnostic tool or a lab-on-a-chip (e.g., glucometer) requires regulatory approval.
The learning curve is steep as health systems and researchers discover ways to tie data from these devices into EHRs and patient portals. Epic, for example, allows clinicians to “prescribe” Apple’s HealthKit app. This allows patients to send data such as blood sugar readings from an iPhone-tethered glucometer into the patient portal. A clinician can set limits for “abnormal” alerting of these values. If the data are abnormal, it informs a designated clinician through the EHR in-basket. The clinician can then send the patient a message securely through the patient portal.
The time-intensive data that these tools generate from patients in their everyday environments is creating new opportunities to gain a greater understanding of disease processes. They are also creating new challenges as providers and researchers learn to analyze these data and visualize multiple streams of data in useful ways for both patients and clinicians. Similar to a hospital telemetry system, software will need to do most of the work to analyze the incoming data. Machine learning and other analytics techniques will need to be applied to the data so they can respond in a feedback loop to guide patients and clinicians in understanding the data, such as sending alerts when trends in health status occur. Moreover, these data will need to be appropriately visualized for diverse audiences and fit into care delivery models that are able to use these tools in health systems and payment models.
With changing payment models, such as bundled care and limited reimbursement for 30-day readmissions, these tools could be ways to monitor patients between clinic visits. For example, a cellular-enabled scale and a phone-tethered electrocardiogram that are used daily following discharge of a cardiac surgery patient could help recognize early decompensation, thus enabling a more proactive healthcare system.
Wearables health technologies are on the rise, and new devices continue to emerge. As we begin to understand the validity of these tools and the utility of having patients track health data from home, we must learn how to appropriately and affordably integrate these tools into new care delivery models for individual and population-level health. All clinicians, though particularly nurses, will be important influencers in understanding how to do this and how to use these devices to improve health outcomes.
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