Background: The diagnosis of epilepsy is at times elusive for both neurologists and nonneurologists, resulting in delays in diagnosis and therapy. The development of screening methods has been identified as a priority in response to this diagnostic and therapeutic gap.
EpiFinder is a novel clinical decision support tool designed to enhance the process of information gathering and integration of patient/proxy respondent data. It is designed specifically to take key terms from a patient’s history and incorporate them into a heuristic algorithm that dynamically produces differential diagnoses of epilepsy syndromes.
Objective: The objective of this study was to test the usability and diagnostic accuracy of the clinical decision support application EpiFinder in an adult population.
Highlights:
- Clinical decision support tools can be implemented in the adult EMU setting.
- Support tools can adapt to user input creating dynamic epilepsy specific differentials.
- Algorithms can predict classification between epilepsy and an alternative diagnosis.