What is Wearable Technology?
Wearable technology has evolved considerably since its conception in the 1960s at the Massachusetts Institute of Technology (MIT). Nowadays, wearables come in various forms including smart watches, armbands, smart bracelets, and even glasses, with each offering a wide range of features that benefit the user. Though small and mobile, wearables are powerful technology. They can provide the user with extensive information by utilizing data that generates intelligent individualized insights.
Wearable devices have applications extending several fields, including healthcare, social networking, culture, and education. According to an analysis done by PwC, almost half of individuals possess a wearable. Of these users, roughly 45 percent have some sort of fitness band. With such widespread use, wearables can have significant utility within the field of healthcare, with potential in the diagnosis, treatment, and prevention of disease states.
How Can Wearables be Integrated in Healthcare?
Wearables integrate mechanics and software engineering to garner real-time and real-life insights about our bodies, overall health, and wellness. This information is gathered throughout use and intelligently evaluated, regulated, and provided to the user. These functions help to communicate accurate data on physiological and pathological mechanisms that are clinically relevant, establishing wearables’ utility in the healthcare space. For example, wearables have been programmed to communicate exercise alerts, detect signs and symptoms, collect laboratory indicators, and provide medication adherence reminders. This data is stored virtually, allowing for easy access and cloud sharing with healthcare providers as well as other relevant stakeholders.
How do Wearables Track Data?
Wearables can collect data both passively and actively . Wearables input passive data via sensors contained within the device. Wearables receive active data via patient-reported information that the user can input into the device’s programs. Application programming interfaces (APIs) help to aggregate and integrate data from various apps.
What are Electronic Health and Medical Records?
An electronic health record (EHR) or electronic medical record (EMR) involve the digital collection and storage of patient protected health information. Because of the electronic nature of this data, EHRs/EMRs can be shared across different providers, facilities, and settings.
Like wearables, the origins of EHRs/EMRs began in the 1960s. It was not until the past few decades, however, that EHRs/EMRs gained traction thanks to the technological advancements of the modern time. The Health Information Technology for Economic and Clinical Health Act was passed in 2009, and its purpose was to incentivize adoption of information technology (IT) within the healthcare sector. Such systems included implantation of revolutionary EHR and EMR platforms. Other policies such as the Meaningful Use policy by the Center of Medicare and Medicaid’s (CMS) also incentivized EHR/EMR use by providing financial benefits for those that incorporated such systems into clinical practice.
Likewise, between 2001 and 2011, EHR utilization rose from 18 to 57 percent. By the year 2015, 87 percent of physicians were utilizing EHR, with the most popular vendors being Cerner, Epic, and Meditech. These systems and their utilization have only expanded in recent years, and EHR/EMRs have since become the modern ‘norm’ for most healthcare facilities alike.
How are Wearables Integrated Into EHR/EMR Systems?
With the developments of both wearables and EHR systems over the past few decades, the two modalities have become intertwined. Medical devices and EHR systems have become integrated, providing useful and real-time health data that constantly feeds into a patient’s medical record. This integration began with simple inputting of physiological parameters such as basic vital signs. The field has since evolved and expanded to incorporate alternative data that can help to further inform patient care decisions and develop therapy action plans. With the extensive uptake of wearable technology by patients and consumers, one can expect an increase in available patient health data for use by practitioners. Presently, more than 400 devices are marketed that are compatible with EHR. This number is likely to rise to even greater heights as technology continues to advance and adoption becomes more widespread. The ways in which wearables can sync and transmit data to an EHR record varies, but several systems and applications are currently available. Healthie, for example, is a platform that connects a patient’s technology to EHR systems. Healthie leverages its mobile iOS app for Apple Health, Fitbit, and Google Fit, and integration is done on the web via an online account. After device syncing, a patient’s data will be uploaded automatically so that both the patient and their provider can monitor a patient’s health status simultaneously.
How can Healthcare Utilize Integration for Wearables and EHR?
Screening and diagnosis
As wearables offer real-time data collection, patients may not have to necessarily wait for a doctor’s visit to receive a diagnosis. One such example of how wearables and EHR can work together to identify disease comes from research performed by the Stanford University School of Medicine. “> The Apple Heart Study enrolled more than 400,000 individuals that utilize wearables. The study evaluated how using an Apple Watch and mobile app that have heart-rate pulse monitoring capabilities could detect atrial fibrillation. Atrial fibrillation oftentimes goes undiagnosed as it is often asymptomatic. However, it is a major cause of stroke and hospitalization. Of the participants that had an irregular pulse notification, 57 percent received medical attention afterwards. A third of patients with an irregular alert that followed up using an ECG patch were later diagnosed with atrial fibrillation. Likewise, these study results demonstrate how wearable technology can play a vital role in the identification and diagnosis of diseases, like atrial fibrillation. When integrated with EHR systems, abnormal alerts could flag for medical attention, allowing for more preventative and predictive medical care.
Driving Treatment
In addition to early detection of disease, the wearable technology/EHR interface can also help to evaluate treatment efficacy and safety. One study, for example, utilized a wireless sensor network platform to assess a user’s respiratory sound, respiratory rate, electrocardiogram (ECG), and blood oxygen saturation. These measurements helped to monitor chronic obstructive pulmonary disease (COPD) treatment efficacy based on relevant parameters. Within the same space, Lit et al. leveraged acoustic respirators to assess asthmatic children for nighttime wheezing. Results indicated that 57 percent of individuals had several nighttime wheezing episodes that had poor correlation with normal lung function measurements. These insights, when integrated with an EHR system and thus communicated to the provider, have the potential to inform more individualized treatment.
Epidemiologic Purposes
Epidemiological studies have traditionally leveraged self-report to collect data regarding routine physical activity. Self-reporting, however, usually has low to moderate validity, making it a somewhat unreliable measure for research purposes. Technology such as wearables, however, can be used as validated tools to provide accurate and reliable measures of activity that self-reports cannot. Wearables collect real-time unbiased and continuous data on physical activity over extended periods of time and in large sample sets. With this robust data, epidemiologic studies can leverage the wearable-EHR interface to better understand physical activity, disease trajectories, and predictive factors. Likewise, researchers and providers can leverage this data to develop more effective strategies for monitoring and intervention, thereby improving clinical decision making.
What are the Challenges Facing Integration?
platform to assess a user’s respiratory sound, respiratory rate, electrocardiogram (ECG), and blood oxygen saturation. These measurements helped to monitor chronic obstructive pulmonary disease (COPD) treatment efficacy based on relevant parameters. Within the same space, Lit et al. leveraged acoustic respirators to assess asthmatic children for nighttime wheezing. Results indicated that 57 percent of individuals had several nighttime wheezing episodes that had poor correlation with normal lung function measurements. These insights, when integrated with an EHR system and thus communicated to the provider, have the potential to inform more individualized treatment.
Epidemiologic Purposes
Epidemiological studies have traditionally leveraged self-report to collect data regarding routine physical activity. Self-reporting, however, usually has low to moderate validity, making it a somewhat unreliable measure for research purposes. Technology such as wearables, however, can be used as validated tools to provide accurate and reliable measures of activity that self-reports cannot. Wearables collect real-time unbiased and continuous data on physical activity over extended periods of time and in large sample sets. With this robust data, epidemiologic studies can leverage the wearable-EHR interface to better understand physical activity, disease trajectories, and predictive factors. Likewise, researchers and providers can leverage this data to develop more effective strategies for monitoring and intervention, thereby improving clinical decision making.
What are the Challenges Facing Integration?
Privacy and Security
Wearables have the ability to collect several types of data outside of just health information. Other use cases involve geographical location tracking and tracking of living habits as well as behaviors. Like any other stored data, there is the potential for data breaches. Therefore, healthcare systems will need to ensure adequate security safeguards and privacy policies to keep this information protected to maintain patient trust.
Technical Issues
While wearables can utilize robust medical data, they can also exhibit technical difficulties. One such problem may involve the specificity of a device’s sensor(s), which is usually low. Because of the low specificity, the device may elicit “false positives” for benign clinical signals. This could impose an administrative burden for providers, who may have to follow-up on such alerts in the EHR. Additionally, low sensitivity devices could miss clinically relevant signals, creating a potential liability. Another technical issue involves wearable battery life. The constant input and transmission of data, storage, and syncing with EHR platforms require longer battery lives. If the equipment were to die and not be re-charged, the EHRs may have missing data and cause gaps, making it harder to interpret.
Legal Issues
Integrating patient health data from wearables into an EHR may lead to shifting responsibilities for clinicians. Inundated with a wealth of health information inputted into the EHR, the physician may now be liable for a missed diagnosis or misdiagnosis. Thus, the wearable-EHR integration poses both an administrative and legal burden. A legal framework is needed to outline the responsibilities and expectations of providers in the context of potentially unreliable data.
Final Thoughts
The technological landscape has rapidly evolved over the past years to provide new and improved methods of diagnosis, treatment, and disease prevention. The wearable-EHR interface represents one of these new innovations, providing the opportunity to collect real-life and real-time health data with integration into a patient’s medical record. This data can assist in the screening, prevention, management, and treatment of disease as well as aiding disease research using real world evidence. However, the field must still consider potential drawbacks of such integration, including the security, technical, and legal risks surrounding implementation.