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AI-Integrated Patient Records

Using AI programs to integrate into Patient Records for Personalised Healthcare

The Project

This project involves the newest development of artificial intelligence (AI) and combines it into patient records to identify and highlight medical risks and hazards for individual patients, with a focus on enhancing user experience (UX) through comprehensive research and thoughtful design. By leveraging AI technology, the project aims to enhance productivity, accelerate the adoption of digital healthcare, and personalise patient care.

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Benefits of this:

  • Empowers healthcare providers with actionable insights to deliver personalised and proactive patient care.

  • Improves patient outcomes by enabling early detection and intervention for potential health risks.

  • Enhances patient engagement and satisfaction through personalised healthcare recommendations and interventions.

  • Supports healthcare professionals in making informed decisions and optimising treatment plans based on individual patient needs.

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Services

UX Research

UX Design

Python

Production tools

Figma

Python

Electronic Patient Records

Jira

Lead Time

24 Months Contract

12 Months Research

12 Months Design

Research 

Stakeholders gathering

Usability study

AI Capabilities

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Outcomes

Mitigate hazards of health risks

Support for GPs, Doctors and clinicians

Automated software

Design 

Interface of potential risks

Python Code

Figma prototypes

Research

User Research

 

Project Kick Off

We arranged a meeting with chief medical officers, head of patient safety and the dev team  to discuss the following points:​

  • What currently is being miss misprescribed and misdiagnosed?

  • What is an increase in patient health issues?

  • What illness do you think could have been detected earlier?

  • What are the most time-constraining areas in healthcare? 

AI image

This Project is in Progress

Due to non-disclosure agreements, specifics regarding the project cannot be disclosed at this time. Responsibilities include access to sensitive data, which cannot be released until January 2025

  • LinkedIn

Reading, UK

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