Project Overview
In today’s healthcare ecosystem, patient well-being extends far beyond the walls of a clinic. Recognising this, a leading US-based healthcare provider turned to Cubet to help close the gap between traditional clinical care and everyday lifestyle factors. The core challenge? Clinical systems like EMRs provide a static view, largely limited to what's discussed during patient appointments. Yet, critical indicators like sleep quality, physical activity, heart rate fluctuations, and calorie burn happen continuously, and silently, outside the hospital. To bring this invisible data into the clinical spotlight, Cubet was tasked with building a robust mobile-first solution. The goal was simple but ambitious: empower doctors with real-time visibility into patient behaviour using smartwatch data, while offering patients AI-generated, personalised health insights that guide them towards better daily choices.
Industry
Healthcare/Digital Health/AI & Lifestyle Medicine
The Client
A prominent healthcare provider in the United States, committed to leveraging technology for proactive, personalised, and data-informed patient care, especially in chronic disease and preventive health management.
Challenges Addressed
Traditional EMRs are not designed to capture how patients live between visits. That means crucial data, how much they move, sleep, or eat, is lost. The client needed a secure, intelligent platform to:
- Integrate real-world data from wearables like Apple Watch and Samsung Galaxy Watch
- Sync this data with their EMR without disrupting workflows
- Use AI to make the data clinically meaningful
- Provide tailored lifestyle advice to patients in real-time
- Give doctors new visibility into patient behaviours that affect long-term health
Bringing all this together in a seamless, cross-platform mobile experience was essential.
Collaboration in Action
Cubet developed two distinct yet interconnected interfaces: one for patients and one for doctors.
The Patient App:
Built natively for iOS and Android, the app connects with Apple HealthKit and Samsung Health to automatically collect lifestyle data, steps, sleep, heart rate, calorie burn, and more. AI models analyse this data in real time to detect behavioural trends like poor sleep, sedentary patterns, or rising resting heart rate. In response, the app delivers lifestyle nudges and personalised suggestions, whether that’s increasing daily hydration, making room for breathing exercises, or modifying bedtime routines.
The Doctor’s Interface:
Seamlessly integrated into the client’s EMR system, the clinician dashboard surfaces lifestyle trends and highlights anomalies. It doesn’t just display data, it translates it. Physicians can review AI-generated insights, receive risk alerts, and get automated clinical suggestions, all without leaving their existing system. The outcome? Faster, more informed treatment decisions and deeper patient engagement.
Technologies Deployed
Mobile Application Layer:
- iOS: Developed in Swift with deep integration into HealthKit
- Android: Developed using Kotlin, integrated with Samsung Health SDK and Google Fit APIs
- Native push notifications for real-time health alerts
- Background sync ensures continuous data updates without manual input
Backend & Intelligence Engine:
- Node.js serves as the API layer connecting devices, backend, and EMR
- Python-based AI engine analyses behavioural data to generate lifestyle recommendations
- PostgreSQL and MongoDB for hybrid data storage—structured clinical metrics and semi-structured behavioural patterns
- Fully HIPAA-compliant, with OAuth 2.0 authentication and secure encryption of patient data
EMR Integration:
- Built with HL7 FHIR APIs to integrate seamlessly with the client’s existing EMR infrastructure
- Custom middleware facilitates two-way communication between the app and EMR
- Role-based access controls and audit logs ensure privacy, compliance, and traceability
Innovative Feature
The standout feature is the AI-powered lifestyle intelligence engine. It doesn’t just collect data from wearables, it interprets it. By analysing sleep cycles, resting heart rate variability, activity trends, and more, the platform identifies risk early and delivers meaningful recommendations before a clinical event occurs. It's preventive care in motion, driven by daily data. This system turns patient behaviour into actionable clinical signals, all without burdening the doctor or the patient with manual logging or extra appointments.
Value Delivered
- Achieved 95%+ real-world accuracy in syncing smartwatch data across platforms
- Delivered a fully integrated EMR solution, with no disruption to existing workflows
- Enabled personalised chronic care plans, supported by real-time coaching
- Empowered doctors to proactively intervene based on lifestyle trends
- Introduced automated alerts and scoring to prioritise high-risk behaviours and patients
What used to be hidden between clinic visits—poor sleep, inactivity, rising stress now surfaced, scored, and addressed in real time.
User Feedback
Patients appreciated the simplicity and the relevance of the insights. No manual input, no technical hurdles—just actionable feedback, delivered daily.
Physicians praised the visibility into a previously blind spot—real-life behaviour. It added context to consultations, made chronic care plans more responsive, and improved engagement with patients.
Conclusion
This wasn’t just an app. It was a bridge between two worlds—consumer health tech and clinical decision-making. By tapping into lifestyle data from wearables and applying intelligent analysis, Cubet and the client created a continuous loop of data, feedback, and care.
Impact Made
The platform redefines what continuity of care really means. Doctors are no longer limited to snapshots taken during appointments—they see the full story of how their patients live, day to day. And patients, instead of waiting for health issues to escalate, get proactive support grounded in their own daily patterns. This project sets a precedent for how real-time data, AI, and clinical systems can work together to power a smarter, more preventive healthcare model.