XMedical

Archie Norman

The Xmedical team brings with them an altogether different way of looking at healthcare services, drawing on decades of experience in healthcare and across other industries. The team believes that a combination of leading IT and infrastructure, unparalleled marketing systems and the ability to build the best from scratch, can combine with the best people to deliver an different medical experience for patients, doctors and medical teams.

Xmedical, a top UK distributor of Covid-19 tests, aims to transform the medical process for all parties. They offer a wide range of services, including onsite testing and quick result delivery, providing crucial support in these tough times. In collaboration with Mercury Labs, Xmedical has enhanced their service with a custom, fully integrated system for a smooth experience from booking to result issuance.

Challenges:

The need for a streamlined appointment scheduling system to enhance interactions for patients and medical professionals.

Efficient communication was paramount, requiring prompt SMS and email capabilities.

The growing popularity of home-testing has necessitated trustworthy ID verification, likeness confirmation, and photo metadata authentication.

Human agents first examined antigen test images, a process that was lengthy and susceptible to mistakes.

The changing demands for testing, such as home-based and antigen tests, require ongoing software updates and new features.

Our Approach:

Developed a solution that integrated features like streamlined booking, SMS/email communications, and QR check-ins and certificate generation.

Introduced Apple Wallet support for added convenience and integrated the system with laboratories for real-time sample processing tracking.

Implemented an AI vision system to efficiently analyse test photos, categorising them into positive, negative, void, or unsuitable image results.

Split the classification problem into Verification (ensuring the clear presence of a test in each image) and Classification (determining the test result).

Developed the system with Python and Go, leveraging a convolutional neural network for image classification.

Outcomes:

Successfully met all regulatory requirements, delivering results on time in 99% of cases.

Accumulated close to 6,000 five-star reviews, handled over 100,000 tests, demonstrating its reliability and customer satisfaction.

The computer vision model optimised photo analysis, minimising human involvement and enhancing accuracy.

The end-to-end solution transformed Xmedical's Covid-19 testing experience, converting manual processes into an automated platform, leading to enhanced efficiency and patient satisfaction.

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