This Case Shows Specific Expertise. Find the Companies with the Skills Your Project Demands!

You're viewing one of tens of thousands of real cases compiled on Many.dev. Each case demonstrates specific, tangible expertise.

But how do you find the company that possesses the exact skills and experience needed for your project? Forget generic filters!

Our unique AI system allows you to describe your project in your own words and instantly get a list of companies that have already successfully applied that precise expertise in similar projects.

Create a free account to unlock powerful AI-powered search and connect with companies whose expertise directly matches your project's requirements.

Enhanced Facial Recognition Platform for Healthcare Database Management

langate.com

Health & Fitness

Key Challenges

Healthcare organizations face challenges with duplicate patient records leading to inaccurate treatments, inefficient workflows, and potential safety risks. Remote patient identification is also a growing concern, particularly with increased reliance on telehealth and the need for secure data access.

About the Client

A healthcare technology company specializing in clinical data management solutions for healthcare providers, researchers, and pharmaceutical companies. Their focus is on improving data accuracy, efficiency, and security.

Project Goals

Enhance the accuracy and efficiency of patient identification using facial recognition.
Prevent duplicate patient entries in clinical databases.
Enable secure remote access to clinical data for healthcare professionals.
Improve the reliability and comprehensiveness of patient records.
Maintain compliance with HIPAA and GDPR regulations.

Functional Requirements

Facial recognition-based patient and staff identification.
Web-based platform for database management and verification.
Mobile application (iOS and Android) for on-the-go verification.
Automated duplicate detection and prevention.
Secure access control and data encryption.
Integration with existing clinical databases.
Audit logging of all verification events.
Support for deidentified unique identification codes to ensure privacy.

Preferred Technologies

.NET framework

Xamarin

Facial Recognition Algorithms (e.g., OpenCV, Azure Face API)

Cloud-based infrastructure (e.g., AWS, Azure, GCP)

Integrations Required

Electronic Health Record (EHR) systems
Clinical database systems
Identity Management systems

Non-Functional Requirements

High accuracy and low false positive/negative rates for facial recognition.
Scalability to handle a large number of users and records.
High availability and reliability.
Strong security and data privacy (HIPAA, GDPR compliance).
Performance: Verification process should complete in under 30 seconds.
User-friendly interface for both web and mobile platforms.

Expected Business Impact

The enhanced facial recognition platform is expected to improve the accuracy and efficiency of clinical database management, reduce duplicate records, enhance patient safety, streamline workflows, and provide a competitive advantage for Healthcare Data Solutions Inc. It will also facilitate more efficient and secure remote patient access, contributing to the growth of multi-location patient management systems.