Remote patient monitoring

Callyope is a French healthtech startup that applies speech analysis and AI to mental health care.Its model assesses patient speech to detect symptoms and anticipate relapses so clinicians can monitor patients more frequently and objectively.The platform is being trialled in French hospitals and supports remote patient monitoring through a mobile app and voice journaling.

CallyopeHealthcare

Propeller Health is a digital health company focused on managing chronic respiratory disease such as asthma and COPD.They developed a digital health platform using small custom-built sensors attached to inhalers that connect via Bluetooth to smartphones.Their platform collects medication usage data, combines it with environmental data, and provides insights and reminders to patients through an app.Providers can remotely monitor patients via a Provider Portal to stratify risk and make data-driven treatment decisions.The platform uses Amazon SageMaker for machine learning to forecast patient health based on recent medication use, weather conditions, and other factors, enabling predictive healthcare.Deployed on AWS infrastructure, the solution has scaled to over 100,000 patients across three continents, accelerating innovation and improving patient outcomes.

Propeller HealthHealthcare

Siemens Healthineers Ultrasound Business Area remotely monitors global ultrasound devices to reduce downtime and improve customer experience using AWS.Built a scalable infrastructure using AWS Systems Manager, AWS Lambda, Amazon EC2, Amazon S3, and Amazon DynamoDB to enable remote device management, automated log collection, software updates, and support.Reduced ultrasound device setup time from 2 hours to 5 minutes, minimized onsite technician visits, enhanced IT staff experience, and ensured compliance with global security standards.

Siemens HealthineersHealthcare

Several hospitals including Mayo Clinic are implementing real-time patient monitoring solutions that use Google Cloud AI and cloud services.The implementation addresses the challenge of traditional patient monitoring relying on manual checks and lacking predictive insight in critical care areas like ICU, ER, and post-operative settings.The solution ingests streaming data from IoT and wearable sensors through Google Cloud's Dataflow, applies AI inference with Vertex AI for early detection of health events such as cardiac arrest and sepsis, and supports hybrid edge-cloud deployments with Google Distributed Cloud and Vertex AI Edge.The system integrates with healthcare standards like FHIR and HL7 and emphasizes security and HIPAA compliance.Notably, Mayo Clinic uses remote monitoring kits with Google Cloud AI to track patients and reduce readmissions.Other organizations like Hypros and Portal Telemedicina have deployed sensor AI and diagnostic AI using Google Cloud technologies.

Mayo ClinicHealthcare

EY partnered with BioIntelliSense to bring real-time, AI-powered wearable monitoring to US healthcare. Leveraging a medical-grade wearable and Microsoft AI analytics, the system monitors patient biometric data continuously, shifting clinical monitoring from episodic spot-checks to actionable trend analysis. Clinical staff can now detect and intervene earlier in patient health deterioration, enhancing outcomes. EY provided strategic consulting to ensure robust AI governance, focusing on ethical deployment and integration into clinical workflows. This solution addresses persistent healthcare staffing limits and operationalizes new AI governance protocols started in back-office tasks and soon extending to core patient care.

BioIntelliSenseHealthcare

Cognizant, in partnership with Microsoft, delivered a virtual healthcare solution hosted on Microsoft Cloud for Healthcare focused on remote patient monitoring in the US. This solution utilizes connected devices such as smart watches, blood pressure monitors, and glucose meters to continuously collect patient vital signs and securely share them with healthcare providers. With built-in analytics powered by Azure, historical health data is tracked for early detection of chronic diseases. Patients benefit from telehealth visits, ensuring access to timely and personalized care, while providers can leverage improved data interoperability and reliable Azure cloud infrastructure. Fast Healthcare Interoperability Resources (FHIR), robust APIs, and Teams integration further enhance scalability and provider collaboration. This offering is part of a broader strategy to transform digital healthcare and is the first of several planned virtual care advancements by Cognizant using Microsoft technology.

US healthcare providersHealthcare

Capita Healthcare Decisions developed Head Home, a remote patient monitoring solution utilizing Microsoft Azure Health Data Services to support the NHS hospital-at-home model. By unifying patient health data in the cloud and leveraging wearables, care teams can monitor patients' health indicators such as blood oxygen, heart rate, temperature, respiratory rate, blood pressure, and ECG remotely and in real-time. The system enables timely reactions through personalized thresholds and notifications, helps reduce hospital pressures and elective care backlog, and fosters better patient outcomes and satisfaction. The solution includes a voice personal assistant for patient-care team communication and integrates data from multiple wearable device providers via FHIR and DICOM standards, improving interoperability and operational efficiency. The platform is part of Capita's broader clinical decision support offering, expanding NHS capability for proactive at-home care while maintaining strong data protection standards. The article provides an overview of the technical and operational benefits Head Home delivers in the UK healthcare context.

Capita Healthcare DecisionsHealthcare

Healthcare providers worldwide, including institutions in Poland and the US (like Cedars-Sinai Medical Center), have implemented AI-driven voice chatbots and conversational agents to improve patient management and operational workflows. These technologies have supported acute care triaging, chronic disease management, remote monitoring, appointment scheduling, medication reminders, and automated, paperless documentation. Notably, the CardioCube voice app, validated under FDA guidelines and integrated into electronic health records, has demonstrated success in supporting heart failure and diabetes patients in home monitoring. The COVID-19 pandemic accelerated adoption, with chatbots used for employee symptom screening, virtual visit triaging, and patient engagement, as seen at hospitals such as University of California San Francisco Health. The solutions automate workflows, provide hands-free interactions, support regulatory compliance, and integrate with hospital IT systems. Challenges persist, including privacy, regulatory complexity (e.g., HIPAA/GDPR), interoperability, and widespread user adoption. Evidence points to improved operational efficiency and enhanced patient experience, with clinical validation and regulatory oversight evolving alongside technological progress.

Cedars-Sinai Medical CenterHealthcare

O2matic, a Danish medtech company, launched an AI-powered home oxygen therapy solution for patients with chronic obstructive pulmonary disorder (COPD). Built on Microsoft Azure, the system utilizes Azure IoT Hub and Microsoft Intune for device management and secure real-time data transfer. The AI algorithms automatically adjust oxygen flow based on continuous patient monitoring, keeping patient oxygen saturation at safe levels and reducing the need for hospital visits. Healthcare staff can monitor patients remotely, reducing exposure risks, particularly during the COVID-19 pandemic. Trials at Hvidovre Hospital showed that O2matic's system kept oxygen levels in the desired range 85% of the time compared to just 47% with manual treatment, leading to improved quality of life and greater patient independence.

O2maticHealthcare

Protecting Brains, Saving Futures (PBSF) utilizes Microsoft Azure for remote brain monitoring in neonatal ICUs, identifying seizures and enhancing medical responses to prevent life-long complications like cerebral palsy. This AI-enabled cloud-based integration empowers hospitals nationwide, significantly increasing the detection rates for undiagnosed neonatal epilepsy and reducing societal costs related to lifelong disabilities.

PBSFHealthcare