September | 2020 | Digital Health

Quiroz JC, Laranjo L, Kocaballi AB, Briatore A, Berkovsky S, Rezazadegan D, Coiera E. Identifying relevant information in medical conversations to summarize a clinician-patient encounter. Health Informatics Journal. 0(0):1460458220951719.

To inform the development of automated summarization of clinical conversations, this study sought to estimate the proportion of doctor-patient communication in general practice (GP) consultations used for generating a consultation summary. Two researchers with a medical degree read the transcripts of 44 GP consultations and highlighted the phrases to be used for generating a summary

Rezazadegan D, Berkovsky S, Quiroz JC, Kocaballi AB, Wang Y, Laranjo L, Coiera E. Automatic Speech Summarisation: A Scoping Review. arXiv preprint arXiv:200811897. 2020

Speech summarisation techniques take human speech as input and then output an abridged version as text or speech. Speech summarisation has applications in many domains from information technology to health care, for example improving speech archives or reducing clinical documentation burden. This scoping review maps the speech summarisation literature, with no restrictions on time frame,

Kocaballi AB, Ijaz K, Laranjo L, Quiroz JC, Rezazadegan D, Tong HL, Willcock S, Berkovsky S, Coiera E. Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners. Journal of the American Medical Informatics Association. 2020.

Objective The study sought to understand the potential roles of a future artificial intelligence (AI) documentation assistant in primary care consultations and to identify implications for doctors, patients, healthcare system, and technology design from the perspective of general practitioners. Materials and Methods Co-design workshops with general practitioners were conducted. The workshops focused on (1) understanding

Wang Y, Coiera E, Magrabi F. Can Unified Medical Language System–based semantic representation improve automated identification of patient safety incident reports by type and severity? Journal of the American Medical Informatics Association. 2020.

Objective The study sought to evaluate the feasibility of using Unified Medical Language System (UMLS) semantic features for automated identification of reports about patient safety incidents by type and severity. Materials and Methods Binary support vector machine (SVM) classifier ensembles were trained and validated using balanced datasets of critical incident report texts (n_type = 2860, n_severity = 1160) collected

Hassanzadeh H, Karimi S, Nguyen. Matching Patients to Clinical Trials Using Semantically Enriched Document Representation. Journal of Biomedical Informatics, Volume 105, 2020, 103406

Recruiting eligible patients for clinical trials is crucial for reliably answering specific questions about medical interventions and evaluation. However, clinical trial recruitment is a bottleneck in clinical research and drug development. Our goal is to provide an approach towards automating this manual and time-consuming patient recruitment task using natural language processing and machine learning techniques.

Quiroz JC, Laranjo L, Tufanaru C, Kocaballi AB, Rezazadegan D, Berkovsky S, Coiera E. Empirical Analysis of Zipf’s Law, Power Law, and Lognormal Distributions in Medical Discharge Reports 2020, Eprint 2003.13352, ArXiv, Cs.CL

Bayesian modelling and statistical text analysis rely on informed probability priors to encourage good solutions. This paper empirically analyses whether text in medical discharge reports follow Zipf’s law, a commonly assumed statistical property of language where word frequency follows a discrete power law distribution. We examined 20,000 medical discharge reports from the MIMIC-III dataset. Methods

Yin K, Jung J, Coiera E, Laranjo L, Blandford A, Khoja A, Tai W, Phillips DP, Lau AYS. Patient Work and Contexts – A Scoping Review. J Med Internet Res 2020;22(6):e16656

Background: Self-management (or self-care) is widely promoted but many patients struggle to practise it effectively. Moreover, few studies have analysed the nature and volume of work required from patients in self-care and how such work fits into the context of their daily life. Objective: To review the characteristics of patient work in adult patients. Patient