PCL Health

1. Unified Platform:

   • Design an architecture that seamlessly connects elderly individuals (patients), their family members (carers), and clinicians on a unified platform.
     
     

2. Integration with Monitoring Devices:

   • Monitor various health vitals such as blood pressure, heart rate, SPO2 levels, and sleep patterns.

   • Integrate these monitoring devices into the system to ensure accurate and continuous data collection.
     
     

3. Real-Time Data Updates:

   • Ensure that crucial health data is updated in real-time among the patient, caregiver, and clinical portal, establishing a coordinated and responsive communication channel.

To address these challenges, our team developed a comprehensive remote healthcare system consisting of three main components:

1. PCL Connect (Patient Tablet App)

2. PCL Client App (Carer Mobile App)

3. Clinician Dashboard (Web Portal)
   
   1. PCL Connect (Patient Tablet App)

Features:

• Elderly-Friendly Interface: Designed with a user-friendly interface to meet the specific needs of elderly users.

• Communication Tools: Provides means for seniors to stay connected with their families through calls, chat, and photo sharing.

• Telemedicine Appointments: Care providers can conveniently schedule and manage telemedicine appointments, enhancing the efficiency of caregiving.
  
  

Technology Stack:

• Frontend: Native Android (Java/Kotlin) and iOS (Swift)

• Backend: .NET Framework

• Database: SQL Server

• Real-Time Communication: SignalR for real-time updates
  
  

2. PCL Client App (Carer Mobile App)

Features:

• Health Monitoring: Allows tech-savvy seniors and their loved ones to monitor vital signs and manage health in real-time.

• Continuous Connection: Caretakers can remain consistently connected and just a tap away from their circle of care, including carers, doctors, and family members.

• Emergency Alerts: Provides quick access to emergency contact and alert features.
  
  

Technology Stack:

• Frontend: Native Android (Java/Kotlin) and iOS (Swift)

• Backend: .NET Framework

• Database: SQL Server

• Notifications: Azure Notification Hubs for push notifications
  
  

3. Clinician Dashboard (Web Portal)

Features:

• Centralized Hub: Serves as a centralized hub for clinicians, eliminating room for error in health management.

• Remote Patient Monitoring: Allows for remote patient monitoring and management of health alerts.

• Customizable Alerts: Enables customizable health alerts to ensure prompt response to any health anomalies.
  
  

Technology Stack:

• Frontend: React for a responsive web interface

• Backend: .NET Framework

• Database: SQL Server

• Real-Time Communication: SignalR for real-time updates

Architecture Design:

• Unified Data Flow: Implemented a secure API to facilitate communication between the mobile apps, monitoring devices, and the backend server.

• Cloud Integration: Utilized Azure for cloud services to ensure scalability and reliability.
  
  

Integration with Monitoring Devices:

• Developed custom interfaces to integrate with health monitoring devices via Bluetooth and Wi-Fi.

• Ensured compatibility with commonly used health monitoring devices to capture vital statistics.
  
  

Real-Time Data Updates:

• Implemented a real-time data synchronization mechanism using SignalR to ensure all parties receive immediate updates on health vitals.

• Used data encryption (AES-256) for secure transmission and storage of sensitive health information to comply with HIPAA regulations.

The implementation of the remote healthcare system resulted in:

• Improved Patient Care: Enhanced monitoring and timely interventions significantly improved the quality of care for elderly patients.

• Better Communication: Seamless communication between patients, carers, and clinicians facilitated coordinated care and quick response to health concerns.

• Higher Engagement: Increased engagement of family members and carers in the care process through real-time updates and communication tools.

• Data-Driven Insights: Clinicians gained access to continuous health data, enabling better analysis and personalized care plans.