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Wearable sensors and remote monitoring technology can help HCPs monitor and manage COPD more effectively.
Chronic obstructive pulmonary disease (COPD) is the third leading cause of death1 worldwide, according to the World Health Organization. In the past, a viable research study would have required participants to complete an in-hospital COPD assessment and return for routine on-site vitals checks. Plus, participants had to keep a written journal of their daily activities. It was a hassle for all involved—especially the patients.Now, similar research is possible at home. Healthcare providers can monitor and manage COPD more effectively and aim to prevent further progression using wearable sensors and remote patient monitoring (RPM) technology.
In clinical research, multi-center observational exploratory studies can correlate wearable sensor data with clinical parameters in monitoring COPD. Exploring the data derived from continuous multi-vital monitoring using a wearable sensor can help identify potential digital biomarkers. A Bluetooth-enabled sensor can monitor an ECG signal to derive heart rate and heart rate variability. The sensor can also provide respiratory rate, activity measures, and skin temperature data. The three-axis accelerometer can provide data on respiratory function, breathing patterns, exacerbations, and cough detection. This helps to monitor stages and signs that the study participant’s status is worsening or improving remotely, and in real-time.
Taking place across multiple sites, a study sponsor can use a combination of Vivalink wearable sensors and mobile app eCOA features, combining ePRO data with more traditionally-derived insights to collect an information spectrum on each study participant. Each participant can receive a phone preloaded with the mobile application. Through the mobile application, sensor data will be continuously live-streamed and synced to the cloud. Over the course of a study, the participants’ eCOA/ePRO data, which are also automatically synced to the cloud, will provide additional context to the wearable sensor data and enable a more complete assessment of COPD exacerbations.
There are several obstacles to overcome in digital data collection for COPD research. The collection of data is conducted remotely in participants' homes using Bluetooth-enabled remote monitoring technology. However, one significant constraint is time, as it is crucial to account for potential seasonal factors that could impact a participant's condition or introduce confounding variables. For instance, climate or environmental conditions can trigger confounding exacerbations in COPD patients. In certain harsh climates, capturing clinically relevant data within appropriate study timelines becomes imperative.
There is also the challenge of data transformation and ingestion. The Vivalink platform enables turnkey ingestion using a variety of data push and pull mechanisms, whether into data repositories, study databases, or third-party electronic-data capture platforms.Both raw unstructured data and aggregated structured data can thus be incorporated into the various downstream data analysis workflows more seamlessly. Physiologic parameters and continuous data will be examined for interesting features related to disease states. The combination of the clinical study database, as well as the data science work, will lead to the determination of correlations and biomarkers related to COPD.
When tailoring digital health technologies and sensor data for a specific use case, there are technical requirements that should be considered to ensure the technology is fit-for-purpose.Vivalink’s core competency in sensor technology and data streams was a key factor in selecting the appropriate sensor configuration and signal processing to achieve the data output appropriate for both workstreams of outcomes assessment and data science. In studies with multiple outputs — raw data from a multi-parameter Vivalink sensor with clinically-relevant time and frequency-based sampling, and structured data can be aggregated in numerous ways for outcomes assessment.
Using Vivalink’s existing cloud server infrastructure, the data is either available for a sponsor to populate a study database/EDC repository so the information is readily available with fewer touchpoints for the data management team or a data repository for exploratory analysis. Typically, a sponsor's data management team asks the vendor for a regular data transfer every few months. In this case, using the Vivalink platform, live-streamed data can be transmitted as quickly as the sponsor desires, and aggregated data can be pushed out at regular intervals. As a result, the team can assess data proactively instead of waiting for bulk transfers, making the overall study more efficient.
Studies deployed globally must adhere to international data privacy and security regulations. Some governments require companies to store citizens' data within their borders. For example, certain data storage laws2 require telecommunications companies to store metadata locally. Similarly, some countries prohibit citizens’ health records3 from being exported. Global studies also need to accommodate native language requirements.
To ensure proper participation, all patient-facing materials, such as the mobile application and user manuals, are translated into patients' native languages. Additionally, in-app instructions and support, including a patient compliance dashboard, are included to facilitate participant adherence and assist them in utilizing the technology as required by a study’s protocol. While digital technology and wearables aren’t new to the industry, they can be new to those participating in a study. Therefore, it is important to ensure usability to reduce attrition.
The technology behind a study enables the sponsor to attain various types of data based on the needs of the end user. To gain a comprehensive understanding of each participant's disease state, the platform utilizes sensor data and eCOA/ePRO. By automating engagement through an app and synchronizing information in the cloud, the platform efficiently manages data streams for individual participants.
Implementing this process eliminates the need for manual data collection, processing, and input by study personnel. Participants no longer have to remember to take readings and record information. Storing data in the cloud enhances awareness among data monitors and participants, helping both parties stay on track.
While sensors can produce vast amounts of data, it is essential that the data is compatible and seamlessly integrates with subsequent stages of analysis and utilization. In other words, sensor data must be structured and formatted in a way that enables efficient and effective use in later stages of a study. By formatting and aggregating voluminous data into a clinical study database, researchers can save time and money, thereby benefiting their research.