Person-based design and evaluation of MIA, a digital medical interview assistant for radiology.

algorithms consumer health information conversational agent medical history taking natural language processing patients radiology user-centered design

Journal

Frontiers in artificial intelligence
ISSN: 2624-8212
Titre abrégé: Front Artif Intell
Pays: Switzerland
ID NLM: 101770551

Informations de publication

Date de publication:
2024
Historique:
received: 11 05 2024
accepted: 22 07 2024
medline: 2 9 2024
pubmed: 2 9 2024
entrez: 2 9 2024
Statut: epublish

Résumé

Radiologists frequently lack direct patient contact due to time constraints. Digital medical interview assistants aim to facilitate the collection of health information. In this paper, we propose leveraging conversational agents to realize a medical interview assistant to facilitate medical history taking, while at the same time offering patients the opportunity to ask questions on the examination. MIA, the digital medical interview assistant, was developed using a person-based design approach, involving patient opinions and expert knowledge during the design and development with a specific use case in collecting information before a mammography examination. MIA consists of two modules: the interview module and the question answering module (Q&A). To ensure interoperability with clinical information systems, we use HL7 FHIR to store and exchange the results collected by MIA during the patient interaction. The system was evaluated according to an existing evaluation framework that covers a broad range of aspects related to the technical quality of a conversational agent including usability, but also accessibility and security. Thirty-six patients recruited from two Swiss hospitals (Lindenhof group and Inselspital, Bern) and two patient organizations conducted the usability test. MIA was favorably received by the participants, who particularly noted the clarity of communication. However, there is room for improvement in the perceived quality of the conversation, the information provided, and the protection of privacy. The Q&A module achieved a precision of 0.51, a recall of 0.87 and an F-Score of 0.64 based on 114 questions asked by the participants. Security and accessibility also require improvements. The applied person-based process described in this paper can provide best practices for future development of medical interview assistants. The application of a standardized evaluation framework helped in saving time and ensures comparability of results.

Identifiants

pubmed: 39219700
doi: 10.3389/frai.2024.1431156
pmc: PMC11363708
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1431156

Informations de copyright

Copyright © 2024 Denecke, Reichenpfader, Willi, Kennel, Bonel, Nairz, Cihoric, Papaux and von Tengg-Kobligk.

Déclaration de conflit d'intérêts

DP was employed at Mimacom AG at the time of chatbot development and paper writing. Thus, Mimacom AG financed the implementation of the system prototype. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Auteurs

Kerstin Denecke (K)

Artificial Intelligence for Health, Institute for Patient-Centered Digital Health, School of Engineering and Computer Science, Bern University of Applied Sciences, Biel, Switzerland.

Daniel Reichenpfader (D)

Artificial Intelligence for Health, Institute for Patient-Centered Digital Health, School of Engineering and Computer Science, Bern University of Applied Sciences, Biel, Switzerland.

Dominic Willi (D)

Artificial Intelligence for Health, Institute for Patient-Centered Digital Health, School of Engineering and Computer Science, Bern University of Applied Sciences, Biel, Switzerland.

Karin Kennel (K)

Artificial Intelligence for Health, Institute for Patient-Centered Digital Health, School of Engineering and Computer Science, Bern University of Applied Sciences, Biel, Switzerland.

Harald Bonel (H)

Department of Radiology, Lindenhof Hospital, Bern, Switzerland.
University Institute for Diagnostic, Interventional and Pediatric Radiology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.

Knud Nairz (K)

University Institute for Diagnostic, Interventional and Pediatric Radiology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.

Nikola Cihoric (N)

Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.

Damien Papaux (D)

Mimacom AG, Bern, Switzerland.

Hendrik von Tengg-Kobligk (H)

University Institute for Diagnostic, Interventional and Pediatric Radiology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.

Classifications MeSH