Developing Intelligent Interviewers to Collect the Medical History: Lessons Learned and Guidelines.
Medical history
chatbot
conversational user interface
dialog-based system
intelligent system
Journal
Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582
Informations de publication
Date de publication:
07 May 2021
07 May 2021
Historique:
entrez:
9
5
2021
pubmed:
10
5
2021
medline:
12
5
2021
Statut:
ppublish
Résumé
Physicians spend a lot of time in routine tasks, i.e. repetitive and time consuming tasks that are essential for the diagnostic and treatment process. One of these tasks is to collect information on the patient's medical history. We aim at developing a prototype for an intelligent interviewer that collects the medical history of a patient before the patient-doctor encounter. From this and our previous experiences in developing similar systems, we derive recommendations for developing intelligent interviewers for concrete medical domains and tasks. The intelligent interviewer was implemented as chatbot using IBM Watson assistant in close cooperation with a family doctor. AnCha is a rule-based chatbot realized as decision tree with 75 nodes. It asks a maximum of 44 questions on the medical history, current complaints and collects additional information on the patient, social details, and prevention. When developing an intelligent digital interviewer it is essential to define its concrete purpose, specify information to be collected, design the user interface, consider data security and conduct a practice-oriented evaluation.
Sections du résumé
BACKGROUND
BACKGROUND
Physicians spend a lot of time in routine tasks, i.e. repetitive and time consuming tasks that are essential for the diagnostic and treatment process. One of these tasks is to collect information on the patient's medical history.
OBJECTIVES
OBJECTIVE
We aim at developing a prototype for an intelligent interviewer that collects the medical history of a patient before the patient-doctor encounter. From this and our previous experiences in developing similar systems, we derive recommendations for developing intelligent interviewers for concrete medical domains and tasks.
METHODS
METHODS
The intelligent interviewer was implemented as chatbot using IBM Watson assistant in close cooperation with a family doctor.
RESULTS
RESULTS
AnCha is a rule-based chatbot realized as decision tree with 75 nodes. It asks a maximum of 44 questions on the medical history, current complaints and collects additional information on the patient, social details, and prevention.
CONCLUSION
CONCLUSIONS
When developing an intelligent digital interviewer it is essential to define its concrete purpose, specify information to be collected, design the user interface, consider data security and conduct a practice-oriented evaluation.
Identifiants
pubmed: 33965913
pii: SHTI210083
doi: 10.3233/SHTI210083
doi:
Types de publication
Journal Article
Langues
eng