Development of an AI-Powered Shared Decision-Making and Monitoring Mobile Application for Healthcare Management

The healthcare organization faces difficulties in effectively communicating treatment options, monitoring patient conditions over time, and facilitating shared decision-making between patients and clinicians. There is a need for a user-friendly, accessible digital tool that synthesizes research data, personalizes treatment options, and supports ongoing care management within strict privacy and security frameworks.

A large healthcare provider or hospital network aiming to enhance patient engagement and clinical decision support through innovative digital solutions.

• Create a cross-platform mobile and web application that simplifies complex treatment research data into user-friendly formats for patients.
• Enable personalized ranking and recommendation of treatment options based on individual patient profiles and preferences.
• Facilitate ongoing monitoring of patient health metrics, allowing for re-evaluation and adjustment of treatment plans over time.
• Support clinicians with an interface to input relevant knowledge and treatment guidelines.
• Ensure secure and compliant management of sensitive health records and personal data.
• Improve communication and shared decision-making between patients and healthcare providers, increasing patient understanding and adherence.

• User-friendly interface for summarizing and presenting treatment research data tailored to individual patient profiles.
• Algorithm for calculating personalized rankings of treatment options based on transparent, adjustable criteria.
• Long-term health condition tracking to facilitate ongoing reassessment and decision adjustments.
• Interfaces for clinicians to input or update relevant medical knowledge and treatment data.
• Web-based access for patients and clinicians to shared health information with strict privacy controls.
• Responsive, cross-platform mobile and web applications built with modern technology stacks.
• Support for secure data storage and compliance with health information security standards.

• Electronic health records (EHR) systems for accessing patient data.
• Medical research databases and knowledge repositories for accurate information updates.
• Secure cloud storage or server solutions to host sensitive health data.

• High performance and responsiveness across all platforms.
• Scalability to support increasing user base and data volume.
• Robust security measures, including data encryption at rest and in transit.
• Compliance with relevant privacy laws and health data regulations.

The implementation of the health decision support application is expected to improve patient understanding of treatment options, enhance shared decision-making, enable continuous health monitoring, and facilitate more personalized treatment plans. These improvements aim to increase patient engagement, reduce decision-related anxiety, and support medical research efforts, ultimately leading to better health outcomes and optimized resource utilization within healthcare organizations.