Abstract
BackgroundAdvances in natural language processing and other machine learning techniques have led to the development of automated agents (chatbots) that mimic human conversation. These systems have mainly been used in commercial settings, and within medicine, for symptom checking and psychotherapy. The aim of this systematic review was to determine the acceptability and implementation success of chatbots in the follow-up of patients who have undergone a physical healthcare intervention.MethodsA systematic review of MEDLINE, MEDLINE In-process, EMBASE, PsychINFO, CINAHL, CENTRAL and the grey literature using a PRISMA-compliant methodology up to September 2020 was conducted. screening and data extraction were performed in duplicate. Risk of bias and quality assessments were performed for each study.ResultsThe search identified 904 studies of which 10 met full inclusion criteria: three randomised control trials, one non-randomised clinical trial and six cohort studies. Chatbots were used for monitoring after the management of cancer, hypertension and asthma, orthopaedic intervention, ureteroscopy and intervention for varicose veins. All chatbots were deployed on mobile devices. A number of metrics were identified and ranged from a 31 per cent chatbot engagement rate to a 97 per cent response rate for system-generated questions. No study examined patient safety.ConclusionA range of chatbot builds and uses was identified. Further investigation of acceptability, efficacy and mechanistic evaluation in outpatient care pathways may lend support to implementation in routine clinical care.
Highlights
The first known agent capable of conversation between human and machine was developed in 19661
Advances in natural language processing and other machine learning techniques have led to the development of automated agents that mimic human conversation
Chatbots were used for monitoring after the management of cancer, hypertension and asthma, orthopaedic intervention, ureteroscopy and intervention for varicose veins
Summary
The first known agent capable of conversation between human and machine was developed in 19661. A recent systematic review involving 17 studies and 1573 participants found that chatbots in healthcare were predominantly used in mental health conditions to educate patients and collect data from health-related questionnaires[4]. Advances in natural language processing and other machine learning techniques have led to the development of automated agents (chatbots) that mimic human conversation. These systems have mainly been used in commercial settings, and within medicine, for symptom checking and psychotherapy. The aim of this systematic review was to determine the acceptability and implementation success of chatbots in the follow-up of patients who have undergone a physical healthcare intervention. Efficacy and mechanistic evaluation in outpatient care pathways may lend support to implementation in routine clinical care
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