Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.
Evangelos Kontopantelis.jpg

Senior Research Fellow 

I am originally from Piraeus, Greece. I completed my bachelor in Statistics in Piraeus and my interest in computer programming led to a scholarship in the National Technical University of Athens, where I completed an MSc and a PhD in computer engineering and a PhD.

Immediately after this I presented myself for compulsory military service and served 17 months as a reserve officer in the Signals Corps, with a speciality in informatics. I completed my service in Athens, after spending 7 months in the northern city of Alexandroupoli.

After a traumatic telephone interview I was offered a post in Manchester in 2005, to work as a research associate with primary care data, specifically with the Quality Management and Analysis System (QMAS) in the context of an incentivisation programme, the Quality and Outcomes Framework (QOF). Over the years I have used my computational background to delve deep into the torrent of data that is fast becoming available in health care, especially in UK primary care, and have been using even larger databases with patient level data, like the Clinical Practice Research Datalink (CPRD, formerly General Practice Research Datalink or GPRD).

Although I have built a career as a health services researcher supported by a Fellowship from the NIHR School for Primary Care Research and various research grants, I still am a biostatistician and health informatician at heart. This enables me to investigate existing statistical methods, generate new approaches and implement them in advanced statistical software platforms, mainly in Stata.

My methodological interests include computational statistics and simulation approaches, meta-analysis, structural equation modelling, data mining techniques, (interrupted) time-series analyses and validity in large health care databases. You can access Stata commands I have generated by typing net from http://statanalysis.co.uk/ within the Stata environment.