Digital Health Technologies in Clinical Trials: Wearables, Sensors, and Smarter Data
Imagine joining a clinical trial without ever visiting a hospital. Your smartwatch tracks your heart rate while you sleep. A sensor on your arm measures glucose continuously. Your phone asks how you feel each morning, and the answers flow straight to the research team. That scenario is not science fiction. It is the world of digital health technologies (DHTs) in clinical trials, and it is changing how medicines get developed.
Three kinds of digital health tools
The Clarity Clinical Solutions video on digital health breaks these tools into three broad categories.
First are wearables: smartwatches, activity trackers, continuous glucose monitors, ECG patches, and smart rings. They sit on the body and collect physiological data in real-world settings. Second are sensors: connected blood pressure cuffs, digital stethoscopes, pulse oximeters, and even ingestible sensors that confirm a patient took their medication. Third are apps and platforms: electronic patient-reported outcome (ePRO) apps that replace paper diaries, telemedicine systems for remote visits, and digital therapeutics that are themselves approved as treatments.
From snapshots to a continuous picture
The shift matters because of how data used to be collected. In a traditional trial, a patient visited the clinic four to eight times a year. Each visit produced a snapshot: one blood pressure reading taken in a stressful clinic setting, or a patient trying to recall three months of symptoms. Paper diaries are famously unreliable. People often fill them in from memory the night before an appointment.
Digital tools change the resolution of the data. A continuous glucose monitor produces 1,440 readings a day instead of one lab value every three months. Activity is logged automatically. Symptoms are recorded in real time. The video describes it as the difference between a photograph and a movie.
Adoption numbers from the video tell the story: the digital health and clinical trials market is worth over $15 billion and growing about 25% a year, and roughly 60% of trials now use some form of digital health technology, roughly a fivefold increase since 2015. Those figures come from the video itself. What is independently verifiable is the regulatory direction: the FDA has issued guidance on how digital health technologies should be verified, validated, and used in registration trials (FDA guidance on digital health technologies for clinical trials), and it runs a dedicated Digital Health Center of Excellence that coordinates agency policy (FDA Digital Health Center of Excellence).
The regulatory side
The central regulatory idea is "fit for purpose." A device used to capture a trial endpoint must be verified to measure accurately, validated to measure what it claims to measure, and usable by the target patient population. The FDA first issued guidance on patient-reported outcomes in 2009 and updated its approach as digital tools matured (FDA guidance on patient-reported outcome measures). Several drugs have now been approved with ePRO data as the primary endpoint for labeling claims.
Privacy adds another layer. HIPAA governs health data in the United States, while Europe's GDPR reaches further into device-generated health data. The FDA has also pushed for stronger device cybersecurity, since connected devices are hackable.
ePRO: retiring the paper diary
Electronic patient-reported outcomes are one of the most practical wins. ePRO apps send daily questionnaires to the patient's phone with timestamps that block backfilling. The video cites completion rates of 80 to 95% for ePRO apps versus 30 to 60% for paper diaries. Because responses arrive in real time, the study team can react immediately when a patient reports severe pain or distress.
What landmark studies show
The Apple Heart Study is the best-known demonstration of scale. More than 419,000 people enrolled in eight months through an iPhone app, using the watch's optical sensor to flag irregular pulses that might indicate atrial fibrillation (the Apple Heart Study results). The study showed it is possible to enroll and monitor participants at a scale no clinic network could match.
In Parkinson's disease, sponsors now use phone and watch sensors to measure gait, tremor, and speech at home. During COVID-19, home pulse oximeters and symptom apps kept trials running through lockdowns.
Your device or ours
One design decision dominates planning: does a patient use their own phone or a device supplied by the sponsor? Bring-your-own-device (BYOD) is cheaper and more comfortable for patients, but different phone models and operating system versions have different sensor characteristics. Provisioned devices are identical for everyone, which protects data quality, at the cost of purchase, shipping, and training burden. The video's rule of thumb: the choice depends on whether the endpoint is exploratory or intended for regulatory submission.
The data problem
The volume of data is the quiet challenge. A single patient on a continuous glucose monitor produces over 10,000 data points a day. The video estimates that a 500-patient, 12-month study using three devices per patient can generate more than five billion data points. Traditional biostatistics was not built for that. Machine learning, signal processing, and feature extraction are becoming standard toolkit items.
Interoperability is the operational headache. A typical digital trial uses five to ten devices from different manufacturers, each with its own data format and cloud platform. Standards like HL7 FHIR for healthcare data exchange exist to fix this, but adoption is still patchy (HL7 FHIR overview). Integration platforms that aggregate sensor data are emerging, and for now, data integration remains the most common source of friction in digital trials.
The bottom line
For decades, trials measured patients in brief clinic visits, a few hours standing in for months of real life. Digital health technologies change that. The picture is no longer episodic snapshots but a continuous story of how a treatment behaves in daily life. Device burden, the digital divide, and interoperability are real problems, and they are solvable ones. This transformation, from occasional snapshots to continuous monitoring, is one of the most significant changes happening in clinical research today.
This article is based on the Clarity Clinical Solutions video "Digital Health Tech - Imagine being part of a clinical trial without having to visit a hospital." Watch it here: Digital Health Tech - Imagine being part of a clinical trial without having to visit a hospital
References
- Clarity Clinical Solutions video — the framework for this article: categories of digital health tools, ePRO data, adoption and cost figures, BYOD vs. provisioned devices. https://www.youtube.com/watch?v=xLYD1yhxuJM
- FDA — Digital Health Technologies for Clinical Trials guidance (verification, validation, fit for purpose). https://www.fda.gov/media/166022/download
- FDA — Digital Health Center of Excellence. https://www.fda.gov/medical-devices/digital-health-center-excellence
- FDA — Patient-Reported Outcome Measures guidance. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/patient-reported-outcome-measures-use-medical-product-development-support-labeling-claims
- National Library of Medicine (PMC) — Apple Heart Study results. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8112605/
- HL7 — FHIR standard overview (interoperability). https://www.hl7.org/fhir/overview.html
- ClinicalTrials.gov — registry of clinical studies. https://clinicaltrials.gov/