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Collaboration, not Confrontation: Understanding General Practitioners’ Attitudes Towards Natural Language and Text Automation in Clinical Practice

David Fraile Navarro, A. Baki Kocaballı, Mark Dras, Shlomo Berkovsky

2022ACM Transactions on Computer-Human Interaction28 citationsDOI

Abstract

General Practitioners are among the primary users and curators of textual electronic health records, highlighting the need for technologies supporting record access and administration. Recent advancements in natural language processing facilitate the development of clinical systems, automating some time-consuming record-keeping tasks. However, it remains unclear what automation tasks would benefit clinicians most, what features such automation should exhibit, and how clinicians will interact with the automation. We conducted semi-structured interviews with General Practitioners uncovering their views and attitudes toward text automation. The main emerging theme was doctor-AI collaboration, addressing a reciprocal clinician-technology relationship that does not threaten to substitute clinicians, but rather establishes a constructive synergistic relationship. Other themes included: (i) desired features for clinical text automation; (ii) concerns around clinical text automation; and (iii) the consultation of the future. Our findings will inform the design of future natural language processing systems, to be implemented in general practice.

Topics & Concepts

AutomationConstructiveComputer scienceReciprocalNatural (archaeology)Theme (computing)Knowledge managementPsychologyData scienceWorld Wide WebProcess (computing)EngineeringLinguisticsOperating systemArchaeologyPhilosophyHistoryMechanical engineeringArtificial Intelligence in Healthcare and EducationElectronic Health Records SystemsMachine Learning in Healthcare
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