Conversational agents in healthcare: a systematic review

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. We searched PubMed, Embase, CINAHL, PsycInfo, and ACM Digital using a predefined search str...

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Bibliographic Details
Published in:	Journal of the American Medical Informatics Association : JAMIA 2018-09, Vol.25 (9), p.1248-1258
Main Authors:	Laranjo, Liliana, Dunn, Adam G, Tong, Huong Ly, Kocaballi, Ahmet Baki, Chen, Jessica, Bashir, Rabia, Surian, Didi, Gallego, Blanca, Magrabi, Farah, Lau, Annie Y S, Coiera, Enrico
Format:	Article
Language:	eng
Subjects:	Artificial Intelligence Communication Delivery of Health Care Natural Language Processing Reviews Speech Recognition Software
Online Access:	Get full text
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Summary:	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. 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. 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. 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. The protocol for this systematic review is registered at PROSPERO with the number CRD42017065917.
ISSN:	1067-5027 1527-974X