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Professor Richard Grieve

BA MSc PhD

Professor
of Health Economics Methodology

Room
Room 144

LSHTM
15-17 Tavistock Place
London
WC1H 9SH
United Kingdom

Tel.
020 7927 2255

I lead a research team whose current research focuses on developing quantitative methods for the evaluation of health care programmes. Our expertise is in the design and analysis of observational studies as well as RCTs, and in methods for cost-effectiveness analyses. We are developing methods that address common methodological issues such as confounding due to treatment selection; non-compliance, missing data,  and external validity.

We undertake applied health economic evaluations predominately in the areas of adult and paediatric intensive care, emergency medicine, emergency and elective surgery, and to the evaluation of new health policies.

My current research interests are focused around methods for using large-scale observational data to provide estimates of effectiveness and cost-effectiveness that can relate directly to individual patients. This research programme includes NIHR funded studies evaluating emergency surgery (ESORT) and treatment intensification for patients with type 2 Diabetes Mellitus (PERMIT). We have been awarded funding by the MRC methodology research programme to investigate quantitative approaches for analysing electonic health records, to provide the evidence required to inform personalisation.

I am the co-director of the LSHTM centre for statistical methodology and was on the REF 2021 subpanel for Public Health, Health Services and primary care.

Affiliations

Department of Health Services Research and Policy

Centres

Centre for Statistical Methodology
Global Health Economics Centre

Teaching

I teach on the introductory module, introduction to health economics, and the economic evaluation module

Research

My main research interests are in developing analytical methods for cost-effectiveness analyses, in particular those that use non-randomised study designs. My work aims to develop more appropriate analytical methods for dealing with confounding due to treatment selection and missing data.

My current research agenda is to address statistical issues raised by moves to use electronic health records to provide the evidence required to inform personalised medicine.

I have received methodological grants from the ESRC on methods for reducing selection bias in health economic evaluation, and from the MRC for developing analytical methods for economic evaluations that use data from cluster randomised trials.

I have ongoing interests in applying the techniques of economic evaluation across a diverse range of clinical areas including adult and paediatric intensive care, hepatitis C, mental health, and for emergency and elective surgical procedures. 

I am interested in supervising PhD students in the general area of statistical methods and health economic evaluation.

Research Area
Clinical trials
Economic evaluation
Health policy
Health services research
Health technology assessment
Statistical methods
Critical care
Electronic health records
Methodology
Modelling
Discipline
Economics
Statistics
Disease and Health Conditions
Cardiovascular disease
Hepatitis

Selected Publications

Impact of the first wave of COVID-19 on outcomes following emergency admissions for common acute surgical conditions: analysis of a national database in England.
Hutchings A; Moonesinghe R; Moler Zapata S; Cromwell D; Bellingan G; Vohra R; Moug S; Smart N; Hinchliffe R; Grieve R
2022
British Journal of Surgery
Effectiveness of emergency surgery for five common acute conditions: an instrumental variable analysis of a national routine database.
Hutchings A; O'Neill S; Lugo-Palacios D; Moler Zapata S; Silverwood R; Cromwell D; Keele L; Bellingan G; Moonesinghe SR; Smart N
2022
Anaesthesia
Application of quantitative bias analysis for unmeasured confounding in cost-effectiveness modelling.
Leahy TP; Duffield S; Kent S; Sammon C; Tzelis D; Ray J; Groenwold RHH; Gomes M; Ramagopalan S; Grieve R
2022
Journal of Comparative Effectiveness Research
Unmeasured confounding in nonrandomized studies: quantitative bias analysis in health technology assessment.
Leahy TP; Kent S; Sammon C; Groenwold RHH; Grieve R; Ramagopalan S; Gomes M
2022
Journal of Comparative Effectiveness Research
Local Instrumental Variable Methods to Address Confounding and Heterogeneity when Using Electronic Health Records: An Application to Emergency Surgery.
Moler-Zapata S; Grieve R; Lugo-Palacios D; Hutchings A; Silverwood R; Keele L; Kircheis T; Cromwell D; Smart N; Hinchliffe R
2022
Medical decision making
A Machine-Learning Approach for Estimating Subgroup- and Individual-Level Treatment Effects: An Illustration Using the 65 Trial.
Sadique Z; Grieve R; Diaz-Ordaz K; Mouncey P; Lamontagne F; O'Neill S
2022
Medical decision making : an international journal of the Society for Medical Decision Making
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