S. Fu, S. Octavia, M. M. Tanaka, V. Sintchenko and R. Lan. (2015). Defining the Core Genome of Salmonella enterica Serovar Typhimurium for Genomic Surveillance and Epidemiological Typing. J Clin Microbiol (Vol. 53, pp. 2530-8).

Abstract: Salmonella enterica serovar Typhimurium is the most common Salmonella serovar causing foodborne infections in Australia and many other countries. Twenty-one S. Typhimurium strains from Salmonella reference collection A (SARA) were analyzed using Illumina high-throughput genome sequencing. Single nucleotide polymorphisms (SNPs) in 21 SARA strains ranged from 46 to 11,916 SNPs, with an average of

U. Gurjav, B. Burneebaatar, E. Narmandakh, O. Tumenbayar, B. Ochirbat, G. A. Hill-Cawthorne, B. J. Marais and V. Sintchenko. (2015). Spatiotemporal evidence for cross-border spread of MDR-TB along the Trans-Siberian Railway line. Int J Tuberc Lung Dis (Vol. 19, pp. 1376-82).

Abstract: BACKGROUND: Mongolia has the fifth highest incidence of tuberculosis (TB) in the Western Pacific Region, with high rates of multidrug-resistant TB (MDR-TB). OBJECTIVE: To examine the recent spatiotemporal dynamics of MDR-TB in Mongolia. METHODS: All MDR-TB cases diagnosed from 2004 to 2012, identified from the National Tuberculosis Control Programme database, were included in the

V. Sintchenko and E. C. Holmes. (2015). The role of pathogen genomics in assessing disease transmission. BMJ (Vol. 350, pp. h1314).

Abstract: Whole genome sequencing (WGS) of pathogens enables the sources and patterns of transmission to be identified during specific disease outbreaks and promises to transform epidemiological research on communicable diseases. This review discusses new insights into disease spread and transmission that have come from the use of WGS, particularly when combined with genomic scale phylogenetic

X. Zhou, Y. Wang, G. Tsafnat, E. Coiera, F. T. Bourgeois and A. G. Dunn. (2015). Citations alone were enough to predict favorable conclusions in reviews of neuraminidase inhibitors. J Clin Epidemiol (Vol. 68, pp. 87-93).

Abstract: OBJECTIVES: To examine the use of supervised machine learning to identify biases in evidence selection and determine if citation information can predict favorable conclusions in reviews about neuraminidase inhibitors. STUDY DESIGN AND SETTING: Reviews of neuraminidase inhibitors published during January 2005 to May 2013 were identified by searching PubMed. In a blinded evaluation, the

J. C. Kwong, N. McCallum, V. Sintchenko and B. P. Howden. (2015). Whole genome sequencing in clinical and public health microbiology. Pathology (Vol. 47, pp. 199-210).

Abstract: Genomics and whole genome sequencing (WGS) have the capacity to greatly enhance knowledge and understanding of infectious diseases and clinical microbiology. The growth and availability of bench-top WGS analysers has facilitated the feasibility of genomics in clinical and public health microbiology. Given current resource and infrastructure limitations, WGS is most applicable to use in

T. Hodgson and E. Coiera. (2015). Risks and benefits of speech recognition for clinical documentation: a systematic review. J Am Med Inform Assoc.

Abstract: OBJECTIVE: To review literature assessing the impact of speech recognition (SR) on clinical documentation. METHODS: Studies published prior to December 2014 reporting clinical documentation using SR were identified by searching Scopus, Compendex and Inspect, PubMed, and Google Scholar. Outcome variables analyzed included dictation and editing time, document turnaround time (TAT), SR accuracy, error rates

A. G. Dunn, J. Leask, X. Zhou, K. D. Mandl and E. Coiera. (2015). Associations Between Exposure to and Expression of Negative Opinions About Human Papillomavirus Vaccines on Social Media: An Observational Study. J Med Internet Res (Vol. 17, pp. e144).

Abstract: BACKGROUND: Groups and individuals that seek to negatively influence public opinion about the safety and value of vaccination are active in online and social media and may influence decision making within some communities. OBJECTIVE: We sought to measure whether exposure to negative opinions about human papillomavirus (HPV) vaccines in Twitter communities is associated with

X. Cai, O. Perez-Concha, E. Coiera, F. Martin-Sanchez, R. Day, D. Roffe and B. Gallego. (2015). Real-time prediction of mortality, readmission, and length of stay using electronic health record data. J Am Med Inform Assoc.

Abstract: OBJECTIVE: To develop a predictive model for real-time predictions of length of stay, mortality, and readmission for hospitalized patients using electronic health records (EHRs). MATERIALS AND METHODS: A Bayesian Network model was built to estimate the probability of a hospitalized patient being “at home,” in the hospital, or dead for each of the next

K. A. Robinson, A. G. Dunn, G. Tsafnat and P. Glasziou. (2014). Citation networks of related trials are often disconnected: implications for bidirectional citation searches. J Clin Epidemiol (Vol. 67, pp. 793-9).

Abstract: BACKGROUND AND OBJECTIVES: Reports of randomized controlled trials (RCTs) should set findings within the context of previous research. The resulting network of citations would also provide an alternative search method for clinicians, researchers, and systematic reviewers seeking to base decisions on all available evidence. We sought to determine the connectedness of citation networks of

G. Tsafnat, P. Glasziou, M. K. Choong, A. Dunn, F. Galgani and E. Coiera. (2014). Systematic review automation technologies. Syst Rev (Vol. 3, pp. 74).

Abstract: Systematic reviews, a cornerstone of evidence-based medicine, are not produced quickly enough to support clinical practice. The cost of production, availability of the requisite expertise and timeliness are often quoted as major contributors for the delay. This detailed survey of the state of the art of information systems designed to support or automate individual

O. P. Concha, B. Gallego, K. Hillman, G. P. Delaney and E. Coiera. (2014). Do variations in hospital mortality patterns after weekend admission reflect reduced quality of care or different patient cohorts? A population-based study. BMJ Qual Saf (Vol. 23, pp. 215-22).

Abstract: BACKGROUND: Proposed causes for increased mortality following weekend admission (the ‘weekend effect’) include poorer quality of care and sicker patients. The aim of this study was to analyse the 7 days post-admission time patterns of excess mortality following weekend admission to identify whether distinct patterns exist for patients depending upon the relative contribution of

E. Coiera, Y. Wang, F. Magrabi, O. P. Concha, B. Gallego and W. Runciman. (2014). Predicting the cumulative risk of death during hospitalization by modeling weekend, weekday and diurnal mortality risks. BMC Health Serv Res (Vol. 14, pp. 226).

Abstract: BACKGROUND: Current prognostic models factor in patient and disease specific variables but do not consider cumulative risks of hospitalization over time. We developed risk models of the likelihood of death associated with cumulative exposure to hospitalization, based on time-varying risks of hospitalization over any given day, as well as day of the week. Model

M. K. Choong, F. Galgani, A. G. Dunn and G. Tsafnat. (2014). Automatic evidence retrieval for systematic reviews. J Med Internet Res (Vol. 16, pp. e223).

Abstract: BACKGROUND: Snowballing involves recursively pursuing relevant references cited in the retrieved literature and adding them to the search results. Snowballing is an alternative approach to discover additional evidence that was not retrieved through conventional search. Snowballing’s effectiveness makes it best practice in systematic reviews despite being time-consuming and tedious. OBJECTIVE: Our goal was to

T. Bowden and E. Coiera. (2013). Comparing New Zealand’s ‘Middle Out’ health information technology strategy with other OECD nations. Int J Med Inform (Vol. 82, pp. e87-95).

Abstract: Implementation of efficient, universally applied, computer to computer communications is a high priority for many national health systems. As a consequence, much effort has been channelled into finding ways in which a patient’s previous medical history can be made accessible when needed. A number of countries have attempted to share patients’ records, with varying

M. S. Ong, F. Magrabi and E. Coiera. (2012). Automated identification of extreme-risk events in clinical incident reports. J Am Med Inform Assoc (Vol. 19, pp. e110-8).

Abstract: OBJECTIVES: To explore the feasibility of using statistical text classification to automatically detect extreme-risk events in clinical incident reports. METHODS: Statistical text classifiers based on Naive Bayes and Support Vector Machine (SVM) algorithms were trained and tested on clinical incident reports to automatically detect extreme-risk events, defined by incidents that satisfy the criteria of