Conversational agents in healthcare: a systematic review

Author:

Laranjo Liliana1ORCID,Dunn Adam G1,Tong Huong Ly1ORCID,Kocaballi Ahmet Baki1,Chen Jessica1,Bashir Rabia1,Surian Didi1,Gallego Blanca1,Magrabi Farah1,Lau Annie Y S1,Coiera Enrico1ORCID

Affiliation:

1. Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia

Abstract

Abstract Objective Our objective was to review the characteristics, current applications, and evaluation measures of conversational agents with unconstrained natural language input capabilities used for health-related purposes. Methods We searched PubMed, Embase, CINAHL, PsycInfo, and ACM Digital using a predefined search strategy. Studies were included if they focused on consumers or healthcare professionals; involved a conversational agent using any unconstrained natural language input; and reported evaluation measures resulting from user interaction with the system. Studies were screened by independent reviewers and Cohen’s kappa measured inter-coder agreement. Results The database search retrieved 1513 citations; 17 articles (14 different conversational agents) met the inclusion criteria. Dialogue management strategies were mostly finite-state and frame-based (6 and 7 conversational agents, respectively); agent-based strategies were present in one type of system. Two studies were randomized controlled trials (RCTs), 1 was cross-sectional, and the remaining were quasi-experimental. Half of the conversational agents supported consumers with health tasks such as self-care. The only RCT evaluating the efficacy of a conversational agent found a significant effect in reducing depression symptoms (effect size d = 0.44, p = .04). Patient safety was rarely evaluated in the included studies. Conclusions The use of conversational agents with unconstrained natural language input capabilities for health-related purposes is an emerging field of research, where the few published studies were mainly quasi-experimental, and rarely evaluated efficacy or safety. Future studies would benefit from more robust experimental designs and standardized reporting. Protocol Registration The protocol for this systematic review is registered at PROSPERO with the number CRD42017065917.

Funder

National Health and Medical Research Council

Centre for Research Excellence in Digital Health

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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