Overview of new diabetes technologies and their role, as well as challenges they bring.
With the rise in the use of technology in patients, including sensors, mobile apps, social media, and location-tracking technology, it appears to be even more possible than ever to monitor disease progression and to intervene when needed. The use of these technologies, very prevalent in the United States, can be particularly useful in chronic conditions such as diabetes. This article reviews the current status of these technologies and discusses the challenges in integrating these systems into clinical care.
One new technology is the use of passive sensors: these sensors detect the number of steps that a person takes during a day, and the most common is the smartphone. Some sensors can also sense geographic position, atmospheric pressure, ambient light, voice, touchscreen pressure, fall detection, spirometer, and hear-rate sensor. Other devices include smartwatches or fitness bands, which may also be used to detect motions such as smoking and seizure activity. Certain smartwatches can even provide electrocardiogram information to detect atrial fibrillation. Other, less common sensors include patches to measure muscle activity and posture, radiofrequency sensors to detect pulmonary edema, smart fabrics to measure pressure, humidity, and temperature. Now there are even smart homes that are embedded with many different types of sensors to record vital signs and monitor physical activity (including falls).
Personal devices may also be used for momentary ecologic assessment (EMA) to capture patient-reported outcomes. EMA is considered to be less subject to recall bias and can be administered multiple times a day to collect information on chronic pain, anxiety, substance use disorders, and many other conditions. Yet another application of mobile health technology is for functional assessment. Functional performance can be measured by patients performing standardized tasks (going for a walk, assessing voice tremor for parkinsonian, memory, and reaction time assessments). All the data collected from these sensors must be converted to digital biomarkers such as daily step count, or average nightly sleep, to be relevant to clinicians. This is why engineers and clinicians need to work together to decide what to measure for clinical needs.
More than just measuring these patient outcomes, active interventions must be utilized along with this monitoring. In patients with diabetes, various reminders and behavioral management programs should also be used along with these monitoring programs. A significant challenge of mobile health is the fact that many patients stop using these devices within six months. Therefore, strategies to improve patient engagement must be utilized. Common goal setting and joint review of data are methods to do this. Another challenge includes the quantity of the data, which can be overwhelming. Visual tools and ancillary staff to help review and triage data should be used to help interpret the data, or to only have the digital biomarkers that inform clinical action or understanding be shown. It can also be challenging to fit this new presentation of data into the workflow; the data should be integrated with the EHR, but this can be extremely costly and challenging. The federal government has called for greater interoperability through an emerging data-exchange standard called fast healthcare interoperability resources (FHIR), which allows third-party apps to integrate into the EHR workflow. This is currently being done on the Apple Health app, but Android does not have an equivalent yet. Another tool to help integrate is to allow the output to be written into the database of the HER. That way, clinicians can view the patient’s third-party app or sensor in an embedded window without the need for a separate login. This may require additional staffing to help patients with set up and to provide technical support. Another concern is the fact that these technologies come with frequent hardware and software updates; the FDA has now proposed to regulate these new technologies to validate them. Standards need also be set for the accuracy of digital biomarkers. These technologies also come with potential threats to privacy and autonomy and could lead to biases against disadvantaged groups.
With the vast evolvement in mobile technologies, there is a clear benefit for clinicians, patients, and even payers. However, many challenges have yet to be tackled, and these concerns need to be addressed. Additionally, there is an ethical concern for patients with reduced digital literacy and non-access to these mobile technologies. This is why clinicians must take an active role in the development of these mobile health devices that have the potential to be transformative in the health care field.
[Sim I. Mobile Devices and Health. N Engl J Med. 2019 Sep 5;381(10):956-968. doi: 10.1056/NEJMra1806949. Review.]
Alessa Grieff, PharmD candidate, University of South Florida College of Pharmacy