Coorey GM, Neubeck L, Usherwood T, Peiris D, Parker S, Lau AY, Chow C, Panaretto K, Harris M, Zwar N. Implementation of a consumer-focused eHealth intervention for people with moderate-to-high cardiovascular disease risk: protocol for a mixed-methods process evaluation. BMJ Open. 2017; 7(1):e014353.

Introduction Technology-mediated strategies have potential to engage patients in modifying unhealthy behaviour and improving medication adherence to reduce morbidity and mortality from cardiovascular disease (CVD). Furthermore, electronic tools offer a medium by which consumers can more actively navigate personal healthcare information. Understanding how, why and among whom such strategies have an effect can help determine the

Lyell D, Magrabi F, Raban MZ, Pont LG, Baysari MT, Day RO, Coiera E: Automation bias in electronic prescribing. BMC Medical Informatics and Decision Making 2017, 17(1):28.

BACKGROUND: Clinical decision support (CDS) in e-prescribing can improve safety by alerting potential errors, but introduces new sources of risk. Automation bias (AB) occurs when users over-rely on CDS, reducing vigilance in information seeking and processing. Evidence of AB has been found in other clinical tasks, but has not yet been tested with e-prescribing. This

Nguyen AD, Baysari MT, Kannangara DR, Tariq A, Lau AY, Westbrook JI, Day RO. Mobile applications to enhance self-management of gout. International Journal of Medical Informatics. 2016; 94:67-74.

Abstract BACKGROUND: Gout is an arthritic condition that is characterised by extremely painful, debilitating acute attacks and eventual joint and organ damage if not controlled. Despite the availability of very effective therapies that, if adhered to, will prevent acute attacks and long-term damage, the disorder is increasingly prevalent. There is an urgent need to improve

Tiong S, Koh E, Delaney G, Lau A, Adams D, Bell V, Sapkota P, Harris T, Girgis A, Przezdziecki A. An e‐health strategy to facilitate care of breast cancer survivors: A pilot study. Asia‐Pacific Journal of Clinical Oncology. 2016.

Abstract AIM: Innovative e-health strategies are emerging, to tailor and provide convenient, systematic and high-quality survivorship care for an expanding cancer survivor population. This pilot study tests the application of an e-health platform, “Healthy.me,” in a breast cancer survivor cohort at Liverpool and Macarthur Cancer Therapy Centres, New South Wales, Australia. METHODS: Fifty breast cancer

Arguel A, Perez‐Concha O, Li SY, Lau A. Theoretical approaches of online social network interventions and implications for behavioral change: A systematic review. Journal of Evaluation in Clinical Practice. 2016; (Oct 6. doi: 10.1111/jep.12655. [Epub ahead of print]).

Abstract RATIONAL, AIMS AND OBJECTIVES: The aim of this review was to identify general theoretical frameworks used in online social network interventions for behavioral change. To address this research question, a PRISMA-compliant systematic review was conducted. METHODS: A systematic review (PROSPERO registration number CRD42014007555) was conducted using 3 electronic databases (PsycINFO, Pubmed, and Embase). Four

Magrabi F, Ammenwerth E, Hyppönen H, de Keizer N, Nykänen P, Rigby M, Scott P, Talmon J, Georgiou A. Improving evaluation to address the unintended consequences of health information technology. IMIA Yearbook. 2016:61-9

Abstract BACKGROUND AND OBJECTIVES: With growing use of IT by healthcare professionals and patients, the opportunity for any unintended effects of technology to disrupt care health processes and outcomes is intensified. The objectives of this position paper by the IMIA Working Group (WG) on Technology Assessment and Quality Development are to highlight how our ongoing

Rigby M, Magrabi F, Scott P, Doupi P, Hypponen H, Ammenwerth E. Steps in moving evidence-based health informatics from theory to practice. Healthcare Informatics Research. 2016; 22(4):255-60.

Abstract OBJECTIVES: To demonstrate and promote the importance of applying a scientific process to health IT design and implementation, and of basing this on research principles and techniques. METHODS: A review by international experts linked to the IMIA Working Group on Technology Assessment and Quality Development. RESULTS: Four approaches are presented, linking to the creation

Kim MO, Coiera E, Magrabi F. Problems with health information technology and their effects on care delivery and patient outcomes: a systematic review. Journal of the American Medical Informatics Association. 2016:ocw154.

Abstract Objective: To systematically review studies reporting problems with information technology (IT) in health care and their effects on care delivery and patient outcomes. Materials and methods: We searched bibliographic databases including Scopus, PubMed, and Science Citation Index Expanded from January 2004 to December 2015 for studies reporting problems with IT and their effects. A framework

Y. Wang, E. Coiera, B. Gallego, O. P. Concha, M. S. Ong, G. Tsafnat, D. Roffe, G. Jones and F. Magrabi. (2016). Measuring the effects of computer downtime on hospital pathology processes. J Biomed Inform (Vol. 59, pp. 308-15)

Abstract: Objective: To introduce and evaluate a method that uses electronic medical record (EMR) data to measure the effects of computer system downtime on clinical processes associated with pathology testing and results reporting. Materials and methods: A matched case-control design was used to examine the effects of five downtime events over 11-months, ranging from 5

U. Gurjav, P. Jelfs, G. A. Hill-Cawthorne, B. J. Marais and V. Sintchenko. (2015). Genotype heterogeneity of Mycobacterium tuberculosis within geospatial hotspots suggests foci of imported infection in Sydney, Australia. Infect Genet Evol.

Abstract: In recent years the State of New South Wales (NSW), Australia, has maintained a low tuberculosis incidence rate with little evidence of local transmission. Nearly 90% of notified tuberculosis cases occurred in people born in tuberculosis-endemic countries. We analyzed geographic, epidemiological and genotypic data of all culture-confirmed tuberculosis cases to identify the bacterial and

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