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A cross-cutting theme

This theme has two main objectives – to provide ongoing methodological support (including particular expertise in statistics and health economics) underpinning the projects outlined in the other research themes, and to deliver novel methodological research in care pathway analysis, early modelling, and sequential incorporation of IVDs.

The methods for the generation of evidence for In Vitro Diagnostics (IVDs) have focused only on the diagnostic accuracy of the test. Appropriate methods to determine the relevance and impact to patient care and adoption in the healthcare system are currently lacking or tend to be too specific (e.g. full cost economic models). Our work over the last four years in IVDs (NIHR DEC) has identified three critical strands of methodological research that we aim to solve as part of this work stream:

  1. care pathway analysis,
  2. early (statistical/economic) modelling,
  3. sequential incorporation of IVDs to aid diagnosis.

The overall aim of this methodology theme is to develop more effective ways to determine and evaluate the most clinically and cost-effective place in the diagnostic pathway of a new diagnostic device, with a focus on commercially supplied IVDs for use in primary care and wider community care. This theme includes statistical and health economic projects, with statistical developments being used to inform new applied modelling methods for economic evaluation, applicable to IVDs in both early and late stages of development.

Theme lead:

Explore our research publications

Our publications

Research news:

Are diagnostic tests cost effective modified assessment checklist produced

Are diagnostic tests cost-effective? Modified assessment checklist produced

A diagnostic test-specific checklist to assess decision modelling has been developed and piloted.

Analysis of community blood test requests highlights potential demand for multiplex platforms

Analysis of community blood test requests highlights potential demand for multiplex platforms

A team from the NIHR Community Healthcare MIC analysed data from over 11.7 million laboratory blood tests.