Project Goal:

The Discharge Importer Tool (DIT) aims to streamline data entry for clinicians by automatically extracting relevant information from patient discharge reports using natural language processing (NLP). Its split-screen interface displays the discharge letter on the left and the input form on the right, allowing users to review and confirm the accuracy of pre-filled data fields.

My Contributions:

1. Target Group Research: Gathered research on the target group, identifying user needs and creating scenarios to ensure the DIT aligns with clinician workflows.
2. Prototype Testing: Tested the current prototype with clinicians to gather feedback on usability and functionality, informing necessary adjustments.
3. Iterative Design: Iterated the design through wireframes, mockups, and UI designs, refining the user interface based on clinician feedback and usability testing.
   

   
4. User Scenarios Development: Created user scenarios to illustrate the context of interactions with the DIT, ensuring that the tool meets the needs of diverse clinician personas and their workflows.
   
5. Functional Requirements and NLP Prediction: Established detailed functional requirements to guide DIT development, including the design of NLP prediction presentations that minimize bias and enhance user trust in the system.

Outcome:

The outcome of this project is a comprehensive design document that outlines all aspects of the Discharge Importer Tool (DIT). This document includes user requirements, functional specifications, and design rationales, ensuring a clear understanding of the tool’s functionality and workflows. By providing detailed guidance on the implementation of the DIT, it aims to facilitate efficient development and integration into clinical settings.

Project Goal:

The goal of the patient Virtual Assistant (pVA) is to support stroke patients by helping them complete medical questionnaires and providing access to stroke-related information. It is designed to improve patient engagement by offering a straightforward way to manage their own health data. Ultimately, the pVA aims to streamline the collection of patient-reported outcome measures, contributing to better-informed stroke care.

My Contributions:

1. User Needs Assessment: Conducted research to understand patient needs, focusing on accessibility and usability for stroke survivors.
2. Personas and Scenario Development: Developed seven detailed personas and scenarios to guide the design of the pVA, ensuring it effectively addresses diverse patient needs and interaction styles.
3. Prototype Development and Iteration: Created initial Figma prototypes and led Wizard of Oz workshops to simulate interactions, iteratively refining the design based on direct patient feedback and usability insights.
4. Conversational Flow Framework: Established a framework for the VA's conversation flow, drawing on literature analysis to ensure natural and effective communication with patients.
5. Functionality and Interface Design: Defined core features and interface elements specifically for stroke patients, focusing on usability and intuitive navigation.
6. Requirements Documentation: Compiled comprehensive functional requirements and specifications, providing a clear development roadmap that aligns with patient needs and project objectives. I visualised the process of one of the requirements, which was linking the pVA to the RES-Q database. Below you can see the original mapping of the process and my redesigned version:
7. Continuous Design Improvements: Integrated findings from usability studies and workshops into ongoing design iterations, ensuring the pVA remains user-centered and effective in real-world applications.

Outcome:

The outcome of the pVA project is a comprehensive service design document that outlines the final design and functionality requirements of the patient virtual assistant. This document serves as a crucial resource for developers, detailing user needs, interaction scenarios, and usability insights gathered from stroke survivors. By providing clear guidelines and specifications, it ensures that the pVA effectively meets the accessibility and usability needs of its intended users.

Additionally I designed an academic poster for one of the pVA user studies:

Project Goal:

The goal of the clinician virtual assistant (cVA) is to enhance healthcare quality by providing clinicians with data-driven insights and visualizations that support informed decision-making. It aims to streamline the analysis of care quality indicators, enabling clinicians to identify trends, assess the impact of treatments, and benchmark against guidelines and peer institutions. By facilitating easy access to relevant data, the cVA empowers clinicians to improve patient outcomes and optimize care delivery.

My Contributions:

1. Design and User Experience: Developed the overall design and user experience of the cVA, focusing on usability and efficiency for clinicians.
2. Figma Prototyping: Created interactive Figma prototypes to visualize the cVA's interface and functionality, enabling iterative feedback and refinement.
3. Frontend Implementation: Collaborated on the frontend implementation of the cVA, ensuring alignment with design specifications and enhancing user interaction.

Outcome:

The outcome of the clinician virtual assistant (cVA) project is a fully designed and user-tested tool that helps clinicians efficiently analyze care quality data through intuitive visualizations. The cVA supports informed decision-making by enabling easy access to trends and benchmarking insights, which ultimately aids in improving patient outcomes. With a clear design and detailed functionality requirements, the project provides a solid foundation for seamless development and implementation in clinical settings.