Evangelos (Evan) Kontopantelis, PhD.

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Personal profile

Overview

I am based in the Division of Population Health, Health Services Research and Primary Care, and work across numerous centres within the Division.

Honourary Research Fellow for the University of Erlangen, Germany

Biography

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.

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.

Research interests

I work with large-scale primary care databases (PCDs) to investigate important health care issues: the effect of monetary incentives on quality of care, predictors of cancer, cancer screening utilisation, care for people with severe mental illnesses.

From a methodological perspective I am mainly interested in computational statistics and simulations, meta-analysis, data mining techniques, structural equation modelling, interrupted time series analysis, statistical software and the validity issues around large databases in health care.

Memberships of committees and professional bodies

Fellow of the Royal Statistical Society (RSS)

RSS Manchester Local Group Secretary

Methodological knowledge

Biostatistics

Computational statistics / simulations

Meta-analysis

Bootstrapping methods

Structural Equation Modelling

Data mining techniques

Applied mathematics

Interrupted time series analysis

Artificial Neural networks

Algorithms (theory, applications)

Large databases in health care

type net from http://statanalysis.co.uk/ within the Stata environment for a list of software contributions

Qualifications

PhD in Computer Engineering, National Technical University of Athens, Department of Electrical & Computer Engineering, Information Technology Section. Thesis: An application of statistics, artificial neural networks and dynamic measures in psychiatric diagnosis

MSc in Computer Engineering, N.T.U.A., Department of Electrical & Computer Engineering, Information Technology Section

Degree in Statistical Science, University of Piraeus

Teaching

Supervising up to five PhD students, at any time

Supporting Centre for Biostatistics with the “biostats clinics”, guiding medical students with their fourth year project option.

Writing or contributing to blogs:

http://blog.policy.manchester.ac.uk/featured/2015/03/can-performance-pay-in-primary-care-reduce-mortality/

https://theconversation.com/health-database-could-help-avoid-another-pharma-scandal-23730

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 10 - Reduced Inequalities

Areas of expertise

  • QA75 Electronic computers. Computer science
  • QA76 Computer software
  • Q Science (General)
  • HA Statistics

Research Beacons, Institutes and Platforms

  • Digital Futures
  • Christabel Pankhurst Institute

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