JMIR Publications

ABSTRACT

Background:

Epilepsy is a disease that affects millions of people worldwide. To improve treatment for its various forms and causes, personalized or precision medicine is increasingly being pursued. Precision medicine offers new therapeutic approaches that deviate from the guidelines and precision medicine provides new insights into the treatment of genetically caused epilepsy. To support this, requirements have been identified for a digital diagnostic board designed for use in interdisciplinary epileptology case conferences.

Objective:

he development of a system that displays patient data clearly and interactively. The definition of the requirements for such a system is necessary to clearly present patient-specific and genetic information and support diagnostic and therapeutic decisions in cases of genetic epilepsy.

Methods:

Participatory observations, including eye tracking, thinking-aloud protocols, expert interviews, and focus group discussions, were conducted to identify requirements. The resulting information was used to determine the system's necessary requirements through needs and requirements analysis. These requirements were then evaluated through focus group discussions and cognitive walkthroughs. Based on the requirements, an interaction concept was designed. Finally, a high-fidelity prototype was developed based on the requirements and interaction concept.

Results:

Participatory observations and expert interviews provided insight into the researchers' methods of gathering information and processing cases. These insights were used to identify patient-centered and external data sources, such as OMIM, gnomAD, and ClinVar databases, as well as scores, that will be incorporated into the system. Then, based on these requirements, a high-fidelity prototype was created using Figma.

Conclusions:

This work introduces a novel system concept that supports case conferences on rare and complex forms of epilepsy by coherently visualizing patient-specific molecular and clinical data. A structured requirements analysis informed the definition of core tasks, the development of an interaction concept, and the creation of a high-fidelity prototype, all of which were guided by principles of visual information seeking. These results lay the groundwork for data-driven hypothesis formation in epilepsy research and underscore the necessity of further evaluating the validity, usability, and user acceptance of the requirements.