I am an Australian physician (MD, PhD) currently working as a Post-Doctoral Research Fellow at Stanford University. I am jointly supervised by Professor Euan Ashley and Professor John Ioannidis and am an active member of both labs: the Ashley Lab and Meta-Research Innovation Center at Stanford (METRICS, Ioannidis).
My fellowship concerns the diagnosis and risk prediction of cardiovascular disease. I employ a variety of statistical methods to assess new diagnostic technologies, such as smart phones and smart wearables, and my work also extends to computational cardiac genetics. The data sources I utilize to conduct my research are numerous, but include large datasets such as the UK Biobank, as well as publicly available dataset (meta-analysis and meta-research). I have also previously used large electronic health records (>250 million EHRs).
Aside from my own research prioritizes (above), I also work on studies conducted collaboratively within the Ashley Lab, the Division of Cardiovascular Medicine and METRICS. These studies broadly include digital health randomized controlled trials (RCTs) and meta-research (including statistical methods such as meta-analysis, meta-regression etc).
I previously completed a DPhil (PhD) in clinical epidemiology at the University of Oxford as a Clarendon Scholar. The title of My DPhil thesis was: “Biostatistical and meta-research approaches to assess diagnostic tests”. My published research is available at my google scholar page (https://scholar.google.co.uk/citations?user=n5l7tL8AAAAJ&hl=en) and some of my code is publicly available at my GitHub (https://github.com/jackosullivanoxford).
Beyond academic institutions, I also consult to the World Health Organization (WHO); including on WHO guidelines, where I am currently the methodological chair for a WHO guideline concerning the early(ier) detection of disease in adults. I also work as an associate editor at one of the BMJ sub-journals: BMJ EBM. During my DPhil I worked clinically at Oxford University Hospitals (John Radcliffe Hospital) and intend to return to clinical practice as a Physician-Scientist at Stanford upon the completion of my research Fellowship.
You can follow me on twitter (https://twitter.com/DrJackOSullivan): where you will find me tweeting about statistics, surfing, cardiology, medicine, epidemiology, health policy, and, occasionally, politics.
Aspirin for the primary prevention of cardiovascular disease in the elderly.
BMJ evidence-based medicine
View details for PubMedID 30733220
Introducing the EBM Verdict: research evidence relevant to clinical practice.
BMJ evidence-based medicine
View details for PubMedID 30700435
Temporal trends in use of tests in UK primary care, 2000-15: retrospective analysis of 250 million tests.
BMJ (Clinical research ed.)
2018; 363: k4666
OBJECTIVES: To assess the temporal change in test use in UK primary care and to identify tests with the greatest increase in use.DESIGN: Retrospective cohort study.SETTING: UK primary care.PARTICIPANTS: All patients registered to UK General Practices in the Clinical Practice Research Datalink, 2000/1 to 2015/16.MAIN OUTCOME MEASURES: Temporal trends in test use, and crude and age and sex standardised rates of total test use and of 44 specific tests.RESULTS: 262974099 tests were analysed over 71436331 person years. Age and sex adjusted use increased by 8.5% annually (95% confidence interval 7.6% to 9.4%); from 14869 tests per 10000 person years in 2000/1 to 49267 in 2015/16, a 3.3-fold increase. Patients in 2015/16 had on average five tests per year, compared with 1.5 in 2000/1. Test use also increased statistically significantly across all age groups, in both sexes, across all test types (laboratory, imaging, and miscellaneous), and 40 of the 44 tests that were studied specifically.CONCLUSION: Total test use has increased markedly over time, in both sexes, and across all age groups, test types (laboratory, imaging, and miscellaneous) and for 40 of 44 tests specifically studied. Of the patients who underwent at least one test annually, the proportion who had more than one test increased significantly over time.
View details for PubMedID 30487169