Professor Paul Aylin, MBChB, FFPH, FRCPE, trained in Public Health after studying medicine at the University of Dundee. He spent three years at the Office for National Statistics as a Medical Statistician before coming to Imperial in 1997.
He was appointed Professor of Epidemiology and Public Health at Imperial College London in 2014, and is principal investigator leading and managing a team of researchers investigating variations in performance and safety in healthcare delivery. He leads a research theme within the NIHR funded Patient Safety Translational Research Centre around use of information, with a focus on primary care and mental health. He leads a work stream on data linkage and surveillance within the NIHR funded Imperial Health Protection Research Unit for Healthcare Associated Infection (HCAI) and Antimicrobial Resistance (AMR). He leads a research theme within NIHR North West London Applied Research Collaborative on Information and Intelligence, providing research expertise in measurement methods, public health informatics, and advanced statistics. He was a recent principal investigator on two further NIHR grants looking at the impact of a mortality surveillance system on UK hospitals and examining the association of surgical procedures during pregnancy with birth outcomes. He is a member of the Directorate of Public Health and Primary Care management board and contributes to the trust Surgical Outcomes Group as well as other projects around patient safety and quality of care.
He is a non-executive director on the board of the West London NHS Trust.
I have used routinely collected clinical and administrative data to examine variations in quality and safety in healthcare. My research has increased the use of data in the management and monitoring of healthcare in the UK and internationally. My work has led to the development of innovative statistical and computational methods for processing large data sets derived from electronic medical records and NHS databases. In my work examining paediatric cardiac surgical outcomes for the Bristol Royal Infirmary Inquiry, I confirmed serious concerns around the surgical outcomes at Bristol and established the usefulness of routine administrative data (Hospital Episode Statistics) in helping to identify quality of care issues. In further research commissioned by the Shipman Inquiry and published in 2003, I established the role that statistical process control charts (specifically log likelihood CUSUM charts), and other routinely collected data (from death certificates) could play in the continuous surveillance of healthcare outcomes, and in this specific case, the detection of unusual patterns of patient mortality within General Practices. I have demonstrated comparable (or better) coverage and completeness of routinely collected administrative data compared to clinical audit data. I have also demonstrated the strength of risk prediction models based on hospital administrative data compared to clinical data. I have developed indicators of healthcare performance based on hospital mortality patient safety indicators,and more recently stroke care and returns to theatre. I have also led the development of a national surveillance tool, the Real-Time Monitoring System (RTM as it is known), designed to monitor hospital outcomes across a range of diagnosis and procedure groups in near real time with data updated monthly. More recent research carried out by the unit since 2007 has refined this system, setting thresholds based on false alarm rates within CUSUM charts for multiple institutions, the automation of multiple risk adjustment models, the incorporation of hierarchical modelling techniques, the refinement of co-morbidity indices and the development of new indicators with potentially greater sensitivity than mortality. Other work on out of hours healthcare outcomes, most recently my work on elective procedures and mortality by day of the week have resulted in policy changes towards increasing clinical cover at weekends within the NHS.
RECENT PHD STUDENT PROJECTS
Analysis of integrated cancer care pathways using routinely collected data, Passed 2017. Lead supervisor.
Innovative analyses of variation in quality of care and resource utilisation using patient journey, Passed 2016. Lead supervisor.
Evaluating the quality and safety of hospital care using specialty-specific indicators based on administrative data, passed 2014. Lead supervisor.
Patient Safety in Primary Care: improving safety through the use of indicators, passed 2013. Lead supervisor.
Investigating the use of Hospital Episode Statistics data to measure variation in Performance and Quality in Colorectal Surgery, passed 2012. Co-supervisor.
Developing syndromic surveillance for existing and emerging healthcare associated infections using linked local databases and risk monitoring, passed 2013, Lead supervisor.
Development and use of methods to estimate chronic disease prevalence in small populations, passed 2011. Co-supervisor
I am Director of Post-Graduate Taught Courses within the School of Public Health, responsible for ensuring the quality of three Masters courses within the School. I am Co-Director of the new online Global MPH, launched in 2019.
et al., 2019, Antibiotic management of urinary tract infection in the elderly in primary care and its association with bloodstream infections and all-cause mortality: a population-based cohort study, Bmj, Vol:365, ISSN:0959-8138
et al., 2016, The risk of adverse pregnancy outcomes following non-obstetric surgery during pregnancy: An observational study, Bjog-an International Journal of Obstetrics and Gynaecology, Vol:123, ISSN:1471-0528, Pages:84-84
et al., 2016, Investigating adverse event free admissions in Medicare inpatients as a patient safety indicator, Annals of Surgery, Vol:265, ISSN:1528-1140, Pages:910-915
Palmer WL, Bottle A, Aylin PP, 2015, The association between day of delivery and obstetric outcomes: an observational study, The Bmj, Vol:351, ISSN:0959-8138
et al., 2013, Global Comparators Project: International Comparison of Hospital Outcomes Using Administrative Data, Health Services Research, Vol:48, ISSN:0017-9124, Pages:2081-2100
et al., 2013, Adverse events recorded in English primary care: observational study using the General Practice Research Database, British Journal of General Practice, Vol:63, ISSN:0960-1643, Pages:E534-E542
et al., 2013, Day of week of procedure and 30 day mortality for elective surgery: retrospective analysis of hospital episode statistics, British Medical Journal, Vol:346, ISSN:1756-1833
et al., 2012, Dying for the Weekend A Retrospective Cohort Study on the Association Between Day of Hospital Presentation and the Quality and Safety of Stroke Care, Archives of Neurology, Vol:69, ISSN:0003-9942, Pages:1296-1302
et al., 2012, Association between patient and general practice characteristics and unplanned first-time admissions for cancer: observational study, Br J Cancer, Vol:107, ISSN:1532-1827
et al., 2010, Weekend mortality for emergency admissions. A large, multicentre study, Quality & Safety in Health Care, Vol:19, ISSN:1475-3898, Pages:213-217
et al., 2009, Early in-hospital mortality following trainee doctors' first day at work, PLOS One, Vol:4, ISSN:1932-6203
Bottle A, Aylin P, 2008, Intelligent information: A national system for monitoring clinical performance, Health Services Research, Vol:43, ISSN:0017-9124, Pages:10-31
Aylin P, Bottle A, Majeed A, 2007, Use of administrative data or clinical databases as predictors of risk of death in hospital: comparison of models, British Medical Journal, Vol:334, ISSN:1756-1833, Pages:1044-1047
Bottle A, Aylin P, 2006, Mortality associated with delay in operation after hip fracture: Observational study., Bmj, Vol:332, Pages:947-951
et al., 2003, Following Shipman: a pilot system for monitoring mortality rates in primary care, The Lancet, Vol:362, ISSN:0140-6736, Pages:485-491
et al., 2001, Comparison of UK paediatric cardiac surgical performance by analysis of routinely collected data 1984-96: was Bristol an outlier?, The Lancet, Vol:358, ISSN:0140-6736, Pages:181-187