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Beyond Patient-Reported Outcomes: How Smartphone-Based Health Checks Can Improve Decentralized Clinical Trials
Bringing convenient, repeatable physiological measurements into patient-centric clinical research
Clinical trials depend on good data. Yet much of the information collected between site visits still comes from questionnaires, diaries, interviews, and participants’ memories. These patient-reported outcomes are essential because they capture symptoms, daily functioning, treatment experience, and quality of life from the patient’s perspective. But they do not always reveal what is happening physiologically at the moment a participant reports feeling well, tired, stressed, dizzy, or short of breath.
As trials become more decentralized, sponsors and contract research organizations (CROs) have an opportunity to connect the patient’s experience with more frequent, objective health information-without automatically adding another device to the participant’s routine. Smartphone-based health checks can help bridge that gap by allowing participants to complete guided measurements remotely through technology already built into a familiar device.
Patient-reported outcomes remain vital – but they are only part of the picture
Patient-reported outcomes (PROs) answer questions that a sensor cannot: How severe is the pain? Can the participant complete normal activities? Is a treatment interfering with sleep or emotional wellbeing? This information is indispensable in patient-centered research.
At the same time, PROs can be affected by recall, interpretation, response timing, and inconsistent completion. A participant may remember the worst moment of the week rather than the typical one. Two people may interpret the same rating scale differently. A diary entry may also be completed hours – or days -after the event it is intended to describe.
Objective measurements do not replace the patient’s voice. They add context. When physiological data is collected close to the time of a reported symptom or scheduled assessment, research teams may gain a richer view of the participant’s condition and its changes over time.
A decentralized trial should reduce friction, not relocate it
Decentralized clinical trials are trials that include activities performed away from traditional trial sites, including through telehealth, in-home visits, or local healthcare providers. Moving an activity outside the site, however, does not automatically make it easy for the participant.
Every additional device may introduce shipping, setup, charging, pairing, training, support, and return logistics. These demands can affect engagement and create operational complexity across sites and geographies. A smartphone-based approach can reduce some of this friction because many participants already know how to use their own phones and can complete a guided check from home or another convenient location.
For sponsors and CROs, that can mean a more scalable route to scheduled remote assessments. For participants, it can mean fewer unnecessary trips and a simpler experience between site visits. The appropriate implementation will always depend on the protocol, population, endpoint strategy, regulatory requirements, and validation needed for the intended use.
What smartphone-based health checks can add
Using the camera in a smartphone or tablet, Binah.ai’s software-based technology enables contactless spot checks of a range of health indicators. Depending on the selected configuration and intended use, these can include measurements such as heart rate, breathing rate, heart rate variability, oxygen saturation, and blood pressure. Binah.ai also offers contact-based continuous monitoring for use cases in which ongoing measurement is required.
Within a decentralized or hybrid trial, this capability may support several practical goals:
- Collecting measurements at defined moments between site visits, according to the study protocol.
- Adding physiological context to symptoms, electronic diaries, and other patient-reported information.
- Following trends over time instead of relying only on occasional clinic-based snapshots.
- Supporting remote screening or eligibility workflows where the technology is appropriate and validated for the intended purpose.
- Reducing manual entry by integrating health-check capabilities into an existing trial application or digital platform.
- Offering spot checks alongside continuous monitoring to suit different study designs and participant journeys.
Five ways the model can strengthen trial execution
1. Create a more complete data story
Consider a participant who reports fatigue on an electronic questionnaire. A nearby health check could provide additional information about heart rate, breathing rate, oxygen saturation, or other protocol-relevant indicators. Neither data source tells the entire story alone. Together, they may help investigators interpret events with better temporal context and decide whether follow-up is needed under the study plan.
2. Increase the frequency of observation
Traditional site visits produce controlled but relatively infrequent snapshots. Remote measurements can create more opportunities to observe change between visits. When checks are scheduled consistently and completed under clearly defined conditions, the resulting longitudinal view may help research teams identify patterns that isolated measurements could miss.
3. Reduce participant burden
Travel, time away from work, mobility limitations, caregiving responsibilities, and distance from research centers can all make trial participation difficult. Enabling suitable activities at home can make participation more accessible. A software-based check may also avoid the logistics associated with distributing a dedicated device for every measurement workflow.
4. Support broader participation
If fewer routine assessments require a trip to a central site, sponsors may be able to recruit from a wider geographic area. That does not guarantee diversity, but it can remove one practical barrier for people who live far from major research centers or find frequent travel difficult. Inclusive study design must also address connectivity, digital literacy, language, accessibility, device compatibility, and human support.
5. Fit health data into the digital trial workflow
The greatest value comes not from adding another isolated data stream, but from connecting measurements to the systems and processes already used by the study. Binah.ai is available as an SDK, enabling organizations to incorporate health checks into existing digital experiences and determine how information should flow to authorized stakeholders.
Data quality requires more than convenience
A convenient measurement is useful only when it is collected in a controlled, interpretable way. Trial teams should define when and how participants perform each check, the environmental and behavioral conditions required, how failed or low-quality measurements are handled, and what constitutes acceptable adherence.
The protocol and data-management plan should also address device compatibility, software version control, training, support, timestamping, auditability, missing data, anomaly review, and the relationship between remote measurements and site-based assessments. Any technology used to support endpoints, eligibility, or safety decisions must be evaluated and validated for that specific context of use.
Privacy and patient trust must be designed in
Health-data collection can increase trial participation only if people trust the process. Participants should understand what is measured, why it is collected, who can access it, how long it is retained, and how it may be used. Consent language should be clear, and data collection should be limited to what the study genuinely needs.
Binah.ai performs its measurement process on the end user’s device and does not save images or videos. Binah.ai does not have access to the extracted health data. This edge-based architecture can help organizations design a more privacy-conscious experience, while sponsors and their technology partners remain responsible for the broader data flow, storage, access controls, consent, and regulatory compliance of the trial solution.
The future is not “PROs or objective data” – it is both
The most patient-centric clinical trials will not silence the patient’s voice in favor of more technology. They will combine what participants say with carefully selected objective measurements that make their experience easier to understand. Smartphone-based health checks can help create that connection while keeping the participant experience simple and familiar.
For sponsors, CROs, and clinical technology providers, the opportunity is to build a data ecosystem that is more continuous, contextual, and accessible—without losing sight of scientific rigor, transparency, and human oversight.
Want to explore what comes next? Watch Binah.ai’s on-demand webinar, The Future of AI-Powered Clinical Trials, for a discussion of continuous real-world data, the evolving regulatory landscape, consent, and patient-centric AI.
