Publications | Digital Health

Liyanage H; Liaw ST; Jonnagaddala J; Hinton W; De Lusignan S, 2018, ‘Common Data Models (CDMs) to Enhance International Big Data Analytics: A Diabetes Use Case to Compare Three CDMs’, Studies in Health Technology and Informatics, vol. 255, pp. 60 – 64, DOI http://dx.doi.org/10.3233/978-1-61499-921-8-60.

Publications2018, CDM, common data models, Observational Medical Outcomes Partnership, OMOP, Patient Centered Outcomes Research Institute, PCORI, Sentine

Common data models (CDM) have enabled the simultaneous analysis of disparate and large data sources. A literature review identified three relevant CDMs: The Observational Medical Outcomes Partnership (OMOP) was the most cited; next the Sentinel; and then the Patient Centered Outcomes Research Institute (PCORI). We tested these three CDMs with fifteen pre-defined criteria for a

Ford L, Carter GP, Wang Q, Seemann T, Sintchenko V, Glass K, Williamson DA, Howard P, Valcanis M, Castillo CF, Sait M, Howden BP, Kirk MD. Incorporating whole genome sequencing into public health surveillance: Lessons from prospective sequencing of Salmonella Typhimurium in Australia. Foodborne Pathogens and Disease 2018; 15(3):161-167.

Publications2018, MLVA; Salmonella Typhimurium; public health; surveillance; whole-genome sequencing

In Australia, the incidence of Salmonella Typhimurium has increased dramatically over the past decade. Whole-genome sequencing (WGS) is transforming public health microbiology, but poses challenges for surveillance. To compare WGS-based approaches with conventional typing for Salmonella surveillance, we performed concurrent WGS and multilocus variable-number tandem-repeat analysis (MLVA) of Salmonella Typhimurium isolates from the Australian Capital

Beller E, Clark J, Tsafnat G, Adams C, Diehl H, Lund H, Ouzzani M, Thayer K, Thomas J, Turner T, Xia J, Robinson K, Glasziou P, founding members of the Ig. Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic reviews. Syst Rev 7, 77 (2018)

Publications2018, automation, collaboration, systematic review

Systematic reviews (SR) are vital to health care, but have become complicated and time-consuming, due to the rapid expansion of evidence to be synthesised. Fortunately, many tasks of systematic reviews have the potential to be automated or may be assisted by automation. Recent advances in natural language processing, text mining and machine learning have produced

Domestic Scholarships – COVID-19 and future crisis preparedness in healthcare

NewsAI, AIHI, artificial intelligence, australian institute of health innovation, COVID-19, digital health, macquarie university, pandemic, phd, safety and ethics, scholarship

Apply now The Australian Institute of Health Innovation at Macquarie University are seeking suitably qualified candidates with pioneering ideas for research into understanding the current health system response to the pandemic and strategies for future crisis preparedness. They have FIVE scholarships available with the Ph.D. topic to be determined taking into account the interests, experience, and prior

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.

Publications2020, automatic summarization, clinical conversations, digital scribe, GP consultation, natural language processing, pareto principle

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

Publications2020, abstractive summarisation, automatic speech recognition, extractive summarisation, speech summarisation, spontaneous speech

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.

Publications2020, artificial intelligence, general practitioners, medical informatics, primary health care, qualitative study

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.

Publications2020, incident reporting, natural language processing, patient safety, semantics, supervised machine learning, text classification, UMLS

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

Publications2020, clinical document classification; clinical trials; cohort selection; artificial neural networks; deep learning; natural language processing

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

Publications2020, data mining; MIMIC-III dataset; machine learning; maximum likelihood estimation; power law with exponential cut-off; statistical distributions

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

Publications2020, self-care; burden of illness; self-management; patient work; patient ergonomics

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

Experienced senior researcher wanted for AI in healthcare role

NewsAI, ai researcher in healthcare, recruitment, research vacancy

Macquarie University is seeking an experienced senior researcher to establish a new AI in healthcare research stream. You’ll be part of the Centre for Health Informatics (CHI), at the Australian Institute of Health Innovation, which leads the Centre of Research Excellence in Digital Health (CRE). You’ll collaborate with a highly experienced team of

PhD Scholarship – Digital health for patients and healthcare consumers

News

Come and study Consumer Digital Health through the PhD Scholarship – Digital health for patients and healthcare consumers. The Phd opportunity is part of the CRE in Interactive Digital Technology to Transform Australia’s Chronic Disease Outcomes led by The University of Melbourne. You’ll be supervised by Dr Annie Lau, CRE Chief Investigator, and Consumer Informatics

Does health informatics have a replication crisis?

Newsevidence based medicine, health informatics

The Journal of the American Medical Informatics Association (JAMIA) published recent work by Enrico Coiera and colleagues from Macquarie University and the University of Health Sciences (Austria) of a narrative review of literature on research replication challenges. The review concluded that the cost of poor replication is a weakening in the quality of published research

Why is it so difficult to govern mobile apps in healthcare?

Newsapps, Governance, patient safety

In a recent article led by CRE Investigator, Associate Farah Magrabi published in BMJ Health and Care Informatics, Magrabi discusses the difficulty of governing mobile apps in healthcare and how these issues can be addressed. Mobile apps have become a convenient way to provide health information and communication services directly in the hands of clinicians