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A Trusted Advisor for Doctors and Caregivers

IBM's CarePlex, developed with Boston Children’s Hospital, leverages Watson AI to enhance global healthcare by providing dynamic medical records, personalized care, and a secure space for medical collaboration.

Company/Client
Roles
Activities
  • Interaction Design
  • Experience Design
  • Data Analysis & Visualization
  • Knowledge Management
  • Information Architecture

IBM’s CarePlex was an innovative healthcare platform utilizing Watson’s artificial intelligence to enhance the medical care process for clinicians, patients, and caregivers. The project, a collaboration between IBM and Boston Children’s Hospital, aimed to integrate cognitive computing into healthcare to provide dynamic medical records and personalized care recommendations.

The Challenge

My task as designer was to implement Watson for use in professional medical practice. In order to be valuable in a clinical environment, a system has to be able to distill the huge corpus of information that comprises a particular patient’s complex clinical situation (including symptoms, condition, drugs, therapies, and treatments). The challenge with CarePlex was to present this clinical data in a way that provides insight into the underlying logic behind Watson’s recommendations while ensuring that the most salient points remain clear and accessible.

AI Design

By integrating cognitive computing with practical, user-centric design, CarePlex exemplified how technology can address complex challenges in healthcare, offering personalized, data-driven support to improve patient outcomes.

Design Challenges

The primary challenge was distilling extensive clinical data into an accessible format that highlighted the most relevant information while providing insight into Watson’s reasoning. The system needed to be intuitive and efficient, reducing cognitive load for users in high-stress environments.

Natural Language Interaction

A key feature of CarePlex was its reliance on natural language processing for interaction. This approach allowed users to input and receive information conversationally, streamlining the user experience and focusing attention on critical care decisions.

Transparency & Verifiability

Automatic recommendations of potential resources to supplement and/or clarify Watson’s recommendations, including journal articles, instructional videos, tests, and connections to known subject matter experts.
Physicians, patients, and caregivers could see a list of experts who could provide a second opinion, and connect with these individuals through the secure CarePlex community.

Creating a Living Medical History

The platform integrated various data sources, including hospital records, medical reports, and real-time data from sensors, to create a comprehensive electronic medical record. This living document served as a foundation for Watson’s analysis and recommendations.

Bringing Value to Physicians, Patients, and Caregivers

In order to be valuable in a clinical environment, a system has to be able to distill the huge corpus of information that comprises a particular patient’s complex clinical situation (including symptoms, condition, drugs, therapies, and treatments). The challenge was to present this clinical data in a way that provided insight into the underlying logic behind Watson’s recommendations while ensuring that the most salient points remain clear and accessible.
To make this happen, I designed an experience mediated through natural language and validated through transparency, with direct access to external resources to verify Watson’s diagnoses and recommendations.

Communicating an AI's Thought Process

Visualization of Watson’s predictive analytics provided insight into how it drew its conclusions. Doctors could assess an individual’s needs and select interventions with greater confidence and accuracy.

A Global Community of Experts

CarePlex emerged as a cloud-based SaaS solution that rapidly connected medical professionals worldwide. Its natural language interface facilitated easy adoption across different regions, requiring minimal training. The platform supported a global community, enhancing medical practices with AI-driven insights.

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