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Richard Grieve

Professor

London School of Hygiene & Tropical Medicine

United Kingdom

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Research Interests

Epidemiology

40%

Health Economics

70%

Comparative Effectiveness Research

40%

Causal Inference

20%

Pharmacoepidemiology

20%

Acute Care

20%

Covid-19

20%

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Recent Grants

Grant: Close

HOD2: Instrumental Variable approaches for estimating heterogeneity of treatment effects to inform personalisation using electronic health records

Open Date: 2021-04-30

Close Date: 2024-04-29

Grant: Close

Prioritising patients for emergency surgery or not: the impact of COVID-19 (ESORT-C19)

Open Date: 2021-03-15

Close Date: 2022-04-15

Grant: Close

PERsonalised Medicine for Intensification of Treatment (PERMIT): the case of type 2 Diabetes Mellitus

Open Date: 2020-01-01

Close Date: 2022-09-30

Grant: Close

Emergency Surgery Or noT (ESORT)

Open Date: 2019-10-01

Close Date: 2021-09-30

Grant: Close

Development of a fully Bayesian framework for the identification and estimation of subgroup effects in Randomised Controlled Trials

Open Date: 2017-03-31

Close Date: 2021-03-30

Articles17

Comparative effectiveness of alternative second-line oral glucose-lowering therapies for type 2 diabetes: a precision medicine approach applied to routine data

Article Link

Year:

2025

Long‐term outcomes following alternative second‐line oral glucose‐lowering treatments: Results from the real‐world progression in type 2 diabetes mellitus United Kingdom (RAPIDS‐UK) model

Article Link

Year:

2025

Surgery or radiotherapy for early-stage cancer study (SORT) target trial protocol: stereotactic ablative radiotherapy (SABR) with curative intent versus surgical resection for early-stage non-small cell lung cancer (NSCLC)

Article Link

Year:

2025

Variation in acute myocardial infarction management by kidney function across hospitals in England: a cross-sectional study using the Myocardial Ischaemia National Audit Project (MINAP)

Article Link

Year:

2025

Going beyond randomised controlled trials to assess treatment effect heterogeneity across target populations

Article Link

Year:

2024

An Approach for Combining Clinical Judgment with Machine Learning to Inform Medical Decision Making: Analysis of Nonemergency Surgery Strategies for Acute Appendicitis in Patients with Multiple Long-Term Conditions

Article Link

Year:

2024

How does a local instrumental variable method perform across settings with instruments of differing strengths? A simulation study and an evaluation of emergency surgery

Article Link

Year:

2023

Adapting Patient and Public Involvement processes in response to the Covid‐19 pandemic

Article Link

Year:

2023

A Comparison of Ordered Categorical versus Discrete Choices within a Stated Preference Survey of Whole-Blood Donors

Article Link

Year:

2023

Clinical effectiveness and cost-effectiveness of emergency surgery for adult emergency hospital admissions with common acute gastrointestinal conditions: the ESORT study

Article Link

Year:

2023

The importance of investing in data, models, experiments, team science, and public trust to help policymakers prepare for the next pandemic

Article Link

Year:

2023

Local Instrumental Variable Methods to Address Confounding and Heterogeneity when Using Electronic Health Records: An Application to Emergency Surgery

Article Link

Year:

2022

A Machine-Learning Approach for Estimating Subgroup- and Individual-Level Treatment Effects: An Illustration Using the 65 Trial

Article Link

Year:

2022

Effect of High-Flow Nasal Cannula Therapy vs Continuous Positive Airway Pressure Therapy on Liberation From Respiratory Support in Acutely Ill Children Admitted to Pediatric Critical Care Units: A Randomized Clinical Trial.

Article Link

Year:

2022

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.

Article Link

Year:

2022

Application of quantitative bias analysis for unmeasured confounding in cost-effectiveness modelling.

Article Link

Year:

2022

Unmeasured confounding in nonrandomized studies: quantitative bias analysis in health technology assessment.

Article Link

Year:

2022

Collaborators15

Andrew Hutchings

Assistant Professor

London School of Hygiene & Tropical Medicine

UNITED KINGDOM

Woojoo Lee

Seoul National University

SOUTH KOREA

Karla DiazOrdaz

Professor

University College London

UNITED KINGDOM

Amanda Adler

University of Oxford

UNITED KINGDOM

Padmanabhan Ramnarayan

Reader in Paediatric Critical Care

Imperial College London

UNITED KINGDOM

Anirban Basu

Fred Hutchinson Cancer Research Center

UNITED STATES

Kamlesh Khunti

University of Leicester Diabetes Research Centre

UNITED KINGDOM

Zia Sadique

Associate Professor

London School of Hygiene & Tropical Medicine

UNITED KINGDOM

Luke Keele

University of Pennsylvania

UNITED STATES

Claire Snowdon

Assistant Professor

London School of Hygiene and Tropical Medicine Population Studies Group

UNITED KINGDOM

Nazima Pathan

University of Cambridge

UNITED KINGDOM

Richard Silverwood

University College London

UNITED KINGDOM

Mark Peters

Professor of Paediatric Intensive Care

University College London Great Ormond Street Institute of Child Health

UNITED KINGDOM

David Cromwell

Professor of Health Services Research

London School of Hygiene & Tropical Medicine

UNITED KINGDOM

R. J. Hinchliffe

UNITED KINGDOM

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