Imperial College London


Faculty of MedicineDepartment of Surgery & Cancer

Visiting Professor



+44 (0)20 8846 7312j.powell




4N17Charing Cross HospitalCharing Cross Campus






BibTex format

author = {Glover, MJ and Jones, E and Masconi, KL and Sweeting, MJ and Thompson, SG and Powell, JT and Ulug, P and Bown, MJ},
doi = {10.1177/0272989X17753380},
journal = {Medical Decision Making},
pages = {439--451},
title = {Discrete Event Simulation for Decision Modeling in Health Care: Lessons from Abdominal Aortic Aneurysm Screening},
url = {},
volume = {38},
year = {2018}

RIS format (EndNote, RefMan)

AB - Markov models are often used to evaluate the cost-effectiveness of new healthcare interventions but they are sometimes not flexible enough to allow accurate modeling or investigation of alternative scenarios and policies. A Markov model previously demonstrated that a one-off invitation to screening for abdominal aortic aneurysm (AAA) for men aged 65 y in the UK and subsequent follow-up of identified AAAs was likely to be highly cost-effective at thresholds commonly adopted in the UK (£20,000 to £30,000 per quality adjusted life-year). However, new evidence has emerged and the decision problem has evolved to include exploration of the circumstances under which AAA screening may be cost-effective, which the Markov model is not easily able to address. A new model to handle this more complex decision problem was needed, and the case of AAA screening thus provides an illustration of the relative merits of Markov models and discrete event simulation (DES) models. An individual-level DES model was built using the R programming language to reflect possible events and pathways of individuals invited to screening v. those not invited. The model was validated against key events and cost-effectiveness, as observed in a large, randomized trial. Different screening protocol scenarios were investigated to demonstrate the flexibility of the DES. The case of AAA screening highlights the benefits of DES, particularly in the context of screening studies.
AU - Glover,MJ
AU - Jones,E
AU - Masconi,KL
AU - Sweeting,MJ
AU - Thompson,SG
AU - Powell,JT
AU - Ulug,P
AU - Bown,MJ
DO - 10.1177/0272989X17753380
EP - 451
PY - 2018///
SN - 0272-989X
SP - 439
TI - Discrete Event Simulation for Decision Modeling in Health Care: Lessons from Abdominal Aortic Aneurysm Screening
T2 - Medical Decision Making
UR -
UR -
VL - 38
ER -