An enterprise-grade system, BioT PaaS is built on the following 3 pillars: Connect, Collaborate, and Care.
Securely connect devices to the cloud in order to bring the power of cloud to device manufacturers.
Secure data transfer and storage, optimized per data type (numeric biomarkers, waveforms, images, raw data files, and more).
Cloudify - Go beyond device power and implement advanced data-driven AI algorithms on the cloud.
Remote device management – Configuration, status, alerts.
Constant updates – Seamless update of capabilities.
- Centralized, zero-touch firmware updates.
- Cloud software updates - Update once, affecting all deployments at zero time.
Open platform - Gain access to the collected big data to improve service for caregivers, expedite clinical trial analysis, gain visibility into Post-Market Clinical Follow-up (PMCF) studies, and correctly identify possible risks and real-world behavior in a timely manner.
Share information with doctors, patients and the ecosystem (subject to configurable fine-grained attribute-based access control policies).
Improve patient engagement and gain better data for your clinical trial and PMCF by personalizing the patient experience:
- Engage when the patient is most likely to cooperate and when the data is still fresh (for example, sending a questionnaire after you’ve detected a medical event).
- Send notifications via the medium convenient to your patient.
- Tailor questionnaires based on experience with the individual patient, and improve feedback.
Integrate with the ecosystem (EHR, RPM, EDC, QMS, etc.), share and receive information to improve your data, as well as improving clinician experience by integrating into their existing workflows.
Analyze adherence patterns, per patient group, across your entire deployment, to gain a better understanding of how best to get patients to use the device or follow exercise protocols.
Improve patient outcome by:
Understanding adherence patterns and creating personal engagement in order to effectively prevent non-adherence.
Identifying critical events and creating automatic actions (alert physician, patients, etc.).
Providing real-world, accurate information for physicians, allowing better treatment decisions to be made by strong visualization modules. It combines observations with clinical events helping to develop intuition for cause and effect.
Providing self-management tools to patients allowing them to become an active factor in their own treatment.
- Visualization of the patient's current status and adherence, allowing the patient to understand how they are affecting the outcome.
- Self-reporting of feedback on their condition and treatment.
- Adherence management tools allow the patient to take an active part in managing their adherence, by setting targets and keeping up with them.
Updated about 1 year ago