Initial User-Centred Design of an AI-Based Clinical Decision Support System for Primary Care

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Michaela Christina Neff - , Universitätsklinikum Frankfurt (Autor:in)
  • Jannik Schaaf - , Universitätsklinikum Frankfurt (Autor:in)
  • Richard Noll - , Universitätsklinikum Frankfurt (Autor:in)
  • Svea Holtz - , Universitätsklinikum Frankfurt (Autor:in)
  • Dania Schütze - , Universitätsklinikum Frankfurt (Autor:in)
  • Susanne Maria Köhler - , Universitätsklinikum Frankfurt (Autor:in)
  • Beate Müller - , Universität zu Köln (Autor:in)
  • Najia Ahmadi - , Institut für Medizinische Informatik und Biometrie (Autor:in)
  • Michael Wagner - , Universitätsklinikum Frankfurt (Autor:in)
  • Holger Storf - , Universitätsklinikum Frankfurt (Autor:in)

Abstract

A clinical decision support system based on different methods of artificial intelligence (AI) can support the diagnosis of patients with unclear diseases by providing tentative diagnoses as well as proposals for further steps. In a user-centred-design process, we aim to find out how general practitioners envision the user interface of an AI-based clinical decision support system for primary care. A first user-interface prototype was developed using the task model based on user requirements from preliminary work. Five general practitioners evaluated the prototype in two workshops. The discussion of the prototype resulted in categorized suggestions with key messages for further development of the AI-based clinical decision support system, such as the integration of intelligent parameter requests. The early inclusion of different user feedback facilitated the implementation of a user interface for a user-friendly decision support system.

Details

OriginalspracheEnglisch
Seiten (von - bis)1051-1055
Seitenumfang5
FachzeitschriftStudies in health technology and informatics
Jahrgang310
PublikationsstatusVeröffentlicht - 25 Jan. 2024
Peer-Review-StatusJa

Externe IDs

Scopus 85183584090

Schlagworte

Schlagwörter

  • Humans, Artificial Intelligence, Decision Support Systems, Clinical, Intelligence, General Practitioners, Primary Health Care