Kocaballi AB, Coiera E, Tong HL, White S, Quiroz JC, Rezazadegan F, Willcock S, Laranjo L. A network model of activities in primary care consultations. Journal of the American Medical Informatics Association. 2019; 26(10):1074-82.

Objective The objective of this study is to characterize the dynamic structure of primary care consultations by identifying typical activities and their inter-relationships to inform the design of automated approaches to clinical documentation using natural language processing and summarization methods. Materials and Methods This is an observational study in Australian general practice involving 31 consultations

Kocaballi AB, Berkovsky S, Quiroz J, Laranjo da Silva L, Tong HL, Rezadegan D, Briatore A, Coiera E. The Personalization of conversational agents in healthcare: a systematic review. Journal of Medical Internet Research. 2019; 21(11):e15360.

Background: The personalization of conversational agents with natural language user interfaces is seeing increasing use in health care applications, shaping the content, structure, or purpose of the dialogue between humans and conversational agents. Objective: The goal of this systematic review was to understand the ways in which personalization has been used with conversational agents in

Kocaballi AB, Laranjo L, Coiera E. Understanding and measuring user experience in conversational interfaces. Interacting with Computers. 2019; 31(2):192-207.

Although various methods have been developed to evaluate conversational interfaces, there has been a lack of methods specifically focusing on evaluating user experience. This paper reviews the understandings of user experience (UX) in conversational interfaces literature and examines the six questionnaires commonly used for evaluating conversational systems in order to assess the potential suitability of

Quiroz, J.C., Laranjo, L., Kocaballi, A.B. et al. Challenges of developing a digital scribe to reduce clinical documentation burden. npj Digit. Med. 2, 114 (2019)

Clinicians spend a large amount of time on clinical documentation of patient encounters, often impacting quality of care and clinician satisfaction, and causing physician burnout. Advances in artificial intelligence (AI) and machine learning (ML) open the possibility of automating clinical documentation with digital scribes, using speech recognition to eliminate manual documentation by clinicians or medical

Yin K, Laranjo L, Tong HL, Lau AY, Kocaballi AB, Martin P, Vagholkar S, Coiera E. Context-Aware Systems for Chronic Disease Patients: Scoping Review. J Med Internet Res 2019;21(6):e10896

Background: Context-aware systems, also known as context-sensitive systems, are computing applications designed to capture, interpret, and use contextual information and provide adaptive services according to the current context of use. Context-aware systems have the potential to support patients with chronic conditions; however, little is known about how such systems have been utilized to facilitate patient

Magrabi F, Ammenwerth E, McNair JB, De Keizer NF, Hyppönen H, Nykänen P, Rigby M, Scott PJ, Vehko T, Wong ZS-Y, Georgiou A. Artificial Intelligence in Clinical Decision Support: Challenges for Evaluating AI and Practical Implications. Yearb Med Inform. 2019; 28(01):128-34.

OBJECTIVES: This paper draws attention to: i) key considerations for evaluating artificial intelligence (AI) enabled clinical decision support; and ii) challenges and practical implications of AI design, development, selection, use, and ongoing surveillance. METHOD: A narrative review of existing research and evaluation approaches along with expert perspectives drawn from the International Medical Informatics Association (IMIA)

Wang Y, Coiera E, Magrabi F. Using convolutional neural networks to identify patient safety incident reports by type and severity. Journal of the American Medical Informatics Association. 2019; 26(12):1600-8.

Objective To evaluate the feasibility of a convolutional neural network (CNN) with word embedding to identify the type and severity of patient safety incident reports. Materials and Methods A CNN with word embedding was applied to identify 10 incident types and 4 severity levels. Model training and validation used data sets (n_type = 2860, n_severity = 1160) collected from

Akbar S, Coiera, E, Magrabi F. Safety concerns with consumer-facing mobile health applications and their consequences: a scoping review. Journal of the American Medical Informatics Association. 2019.

Objective: To summarize the research literature about safety concerns with consumer-facing health apps and their consequences. Materials and methods: We searched bibliographic databases including PubMed, Web of Science, Scopus, and Cochrane libraries from January 2013 to May 2019 for articles about health apps. Descriptive information about safety concerns and consequences were extracted and classified into

Magrabi F, Habli I, Sujan M, Wong D, Thimbleby H, Baker M, Coiera E. Why is it so difficult to govern mobile apps in healthcare? BMJ Health Care Inform 2019;26:e100006. doi:10.1136/ bmjhci-2019-100006

Mobile apps have become a convenient way to provide health information and communication services directly in the hands of clinicians and consumers. Apps can be used to support consumers in a variety of health tasks to manage chronic diseases, support lifestyle changes and in self-diagnosis. For clinicians, they can improve access to patient information and

Hassanzadeh H, Nguyen A, Verspoor K. Quantifying semantic similarity of clinical evidence in the biomedical literature to facilitate related evidence synthesis. Journal of Biomedical Informatics. 2019;100:103321.

Objective: Published clinical trials and high quality peer reviewed medical publications are considered as the main sources of evidence used for synthesizing systematic reviews or practicing Evidence Based Medicine (EBM). Finding all relevant published evidence for a particular medical case is a time and labour intensive task, given the breadth of the biomedical literature. Automatic

Laranjo L, Dunn AG, Tong HL, Kocaballi AB, Chen J, Bashir R, Surian D, Gallego B, Magrabi F, Lau AYS, Coiera E. Conversational agents in healthcare: a systematic review. Journal of the American Medical Informatics Association. 2018; 25(9):1248-58.

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

Coiera E, Kocaballi AB, Halamka J, Laranjo L. The digital scribe. npj Digital Medicine. 2018; 1(1):58.

Current generation electronic health records suffer a number of problems that make them inefficient and associated with poor clinical satisfaction. Digital scribes or intelligent documentation support systems, take advantage of advances in speech recognition, natural language processing and artificial intelligence, to automate the clinical documentation task currently conducted by humans. Whilst in their infancy, digital

Coiera E, Ammenwerth E, Georgiou A, Magrabi F. Does health informatics have a replication crisis. Journal of the American Medical Informatics Association. 2018:25(8)963-968

OBJECTIVE: Many research fields, including psychology and basic medical sciences, struggle with poor reproducibility of reported studies. Biomedical and health informatics is unlikely to be immune to these challenges. This paper explores replication in informatics and the unique challenges the discipline faces. METHODS: Narrative review of recent literature on research replication challenges. RESULTS: While there

Rapid response function

About the Rapid response function The CRE in Digital Health conducts rapid literature reviews, data collation and meta-analysis to answer critical digital health issues, with an emphasis on maintaining a neutral and independent position. Chief Investigators (CIs) prioritise questions to be answered and supervise the structuring and analysis of these reports. CIs solicit issues from