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Methods research to support the assessment of diagnostic health technologies and the development of guidelines for diagnostic services


For the purposes of this strategic opportunity notice, “diagnostics” refers to devices that can provide information on disease risk, diagnosis, prognosis or treatment response (including risk of adverse events). At an international level, the World Health Organization (WHO) has just published the first ever list of essential diagnostics, intended to serve as a reference for countries to update or develop their own list of essential diagnostics and ensure appropriate and quality-assured supplies for the tests in the list. At a national level in England, evidence to support the uptake of diagnostics is assessed by the National Institute for Health and Care Excellence (NICE). It is therefore important for NICE, and for other health-related agencies across the globe, to understand and overcome the challenges facing the health technology assessment (HTA) and the development of guidelines for diagnostic technologies and services. 

Currently, evidence generated by diagnostics manufacturers and publicly funded research projects is routinely used to inform economic models. These models directly influence diagnostic technology selection, with assurance provided by NICE’s Diagnostics Assessment Programme. There is now growing interest in new and increasingly complex types of diagnostic technologies. The nature of these tests means the preparation of methodologically robust submissions to HTA bodies, the definition of a scope for appraisals and the types of analyses that diagnostics assessments will demand are subject to increasing complexity. Consequently, both decision-makers and technology developers require new analytical techniques and methods to be developed that can more readily address this complexity.

There are unique features of diagnostic tests that add a layer of complexity to evidence generation, analysis and interpretation in this area. One challenge is the need to synthesise evidence about measures of test accuracy (for example, sensitivity and specificity). Another complexity is that the value of tests often relies on a combination of their clinical diagnostic utility, their prognostic ability, their ability to predict relative treatment effects, and their impact on clinical decisions (such as which patients will be offered treatment). A range of new types of trial designs, combined with more traditional randomised clinical trials and observational data sources, may enable the development of robust evidence to support the value propositions of diagnostic health technology innovators. These include: (i) randomise-all, (ii) enrichment, (iii) single-arm, and (iv) biomarker-strategy designs (Tajik et al. 2013). They offer new options to develop evidence but may also create additional methodological challenges to HTA. The goal will be to pair appropriate, HTA-relevant research questions with optimal assimilation of evidence.

Accordingly, this strategic opportunity calls for methods research and development to support the assessment of diagnostic technologies and the development of guidelines for diagnostic services.

Strategic opportunity

MRC and NIHR, through the Methodology Research Programme panel, are seeking to support the development of better methodologies for the assessment of diagnostic health technologies and the development of guidelines for diagnostic services for healthcare decision-making at the national level (such as by NICE).

Assessment of diagnostic technologies and services to inform decision-making

MRC, NIHR and NICE seek to support the development of methods for the assessment of diagnostic health technologies and services for healthcare decision-making, in two contexts:

  • the assessment of diagnostic health technologies and services to inform and add value to recommendations about their adoption
  • the assessment of diagnostic health technologies and services to inform and add value to recommendations about their development.

Applications should aim to deliver tools which could be implemented by NICE in the near-to-medium term, and should develop at least one of the following:

  • guidance on the study designs (such as the trial designs described by Tajik et al. (2013)) that are appropriate/informative for HTA and the pros/cons of each, focusing on evidence requirements for cost-effectiveness evaluations of diagnostic tests (as described by Shinkins et al. (2017))
  • frameworks for analysis and synthesis of data derived from different sources and study designs (such as observational studies and randomised controlled trials) specifically to inform decision-making in the assessment of diagnostic health technologies and in the production of guidelines for diagnostic services. For example, further develop methods for linking diagnostic test data to treatment use, recurrence and survival outcomes
  • methods for quantifying the impact of potential interdependency of multiple test combinations within the diagnostic pathway and how this can be incorporated into decision-making
  • a framework for the health economic evaluation of diagnostic health technologies. structural uncertainty in health economic modelling
  • methods for the synthesis of evidence on diagnostic test accuracy (for example, sensitivity and specificity).

Methodological learning must be generalisable and framed within a convincing pathway to optimise uptake and implementation into decision-making.

Proposals demonstrating engagement with developers and users of diagnostic technologies early in methodology development will be prioritised.

Longer term challenges may also be considered but are not the primary focus of the current opportunity. These include, but are not limited to, improvements in evidence quality informing CE marking, and HTA and regulatory approaches to accommodate diagnostic technologies for which accuracy is expected to vary over time (for example, diagnostics with deep learning components).

Applicants have the opportunity to benefit from discussion of their application with NICE prior to its submission.  See contacts and guidance below.

Application process and schedule

Applications for projects are invited through the Methodology Research Programme panel, to its regular deadlines and meetings. These will be in competition with other applications received, but the panel will be mindful of the strategic importance of this area.

In accordance with the remit of the MRP, applications should focus specifically on supporting methods development research where the proposed outputs are generalisable beyond an individual case study and where uptake and implementation of the developed method are the primary purposes of the research. Successful applications will apply new methods to a motivating example, with decisions fully justified in reference to the above aims.

Budget requests to the MRC of over £500,000 must receive written approval from the programme manager in advance of application.

Contacts and guidance

All applicants

The titles of all applications in response to this opportunity should be prefixed with 'HCD:' when filling out the Je-S form, for example “HCD: A method for…”

It is essential to discuss your proposals with MRC head office at an early stage. All applications must be approved by the Methodology Programme Manager prior to submission. Please contact:

Dr Samuel Rowley

Email: Samuel.Rowley@MRC.UKRI.org

NICE wishes to help improve the quality of applications submitted under this opportunity, and is able to offer advice and guidance on improving the scientific quality of proposals and their pathways to impact. Applicants are encouraged to contact the Science Policy and Research Programme at NICE by emailing research@nice.org.uk. Please get in touch as early as possible.

This opportunity is only available to applicants who have already received confirmation from Dr Samuel Rowley that their proposal falls under this opportunity notice.

More information is available on the NICE website.


Tajik, P., Zwinderman, A. H., Mol, B. W., & Bossuyt, P. M. (2013). Trial designs for personalizing cancer care: a systematic review and classification. Clinical Cancer Research, 19(17), 4578-4588.

Shinkins, B., Yang, Y., Abel, L., & Fanshawe, T. R. (2017). Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological review of health technology assessments. BMC medical research methodology, 17(1), 56.