Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 853

The DOI matches its Crossref record; 112 of the 112 references it cites were found in a registry or an index.

Methods for the estimation of the National Institute for Health and Care Excellence cost-effectiveness threshold

Open access
Claxton, Karl, Martin, Steve, Soares, Marta, Rice, Nigel, Spackman, Eldon, Hinde, Sebastian, Devlin, Nancy, Smith, Peter C, Sculpher, Mark·2015·Health Technology Assessment

Abstract

Background: Cost-effectiveness analysis involves the comparison of the incremental cost-effectiveness ratio of a new technology, which is more costly than existing alternatives, with the cost-effectiveness threshold. This indicates whether or not the health expected to be gained from its use exceeds the health expected to be lost elsewhere as other health-care activities are displaced. The threshold therefore represents the additional cost that has to be imposed on the system to forgo 1 quality-adjusted life-year (QALY) of health through displacement. There are no empirical estimates of the cost-effectiveness threshold used by the National Institute for Health and Care Excellence. Objectives: (1) To provide a conceptual framework to define the cost-effectiveness threshold and to provide the basis for its empirical estimation. (2) Using programme budgeting data for the English NHS, to estimate the relationship between changes in overall NHS expenditure and changes in mortality. (3) To extend this mortality measure of the health effects of a change in expenditure to life-years and to QALYs by estimating the quality-of-life (QoL) associated with effects on years of life and the additional direct impact on QoL itself. (4) To present the best estimate of the cost-effectiveness threshold for policy purposes. Methods: Earlier econometric analysis estimated the relationship between differences in primary care trust (PCT) spending, across programme budget categories (PBCs), and associated disease-specific mortality. This research is extended in several ways including estimating the impact of marginal increases or decreases in overall NHS expenditure on spending in each of the 23 PBCs. Further stages of work link the econometrics to broader health effects in terms of QALYs. Results: The most relevant ‘central’ threshold is estimated to be £12,936 per QALY (2008 expenditure, 2008–10 mortality). Uncertainty analysis indicates that the probability that the threshold is < £20,000 per QALY is 0.89 and the probability that it is < £30,000 per QALY is 0.97. Additional ‘structural’ uncertainty suggests, on balance, that the central or best estimate is, if anything, likely to be an overestimate. The health effects of changes in expenditure are greater when PCTs are under more financial pressure and are more likely to be disinvesting than investing. This indicates that the central estimate of the threshold is likely to be an overestimate for all technologies which impose net costs on the NHS and the appropriate threshold to apply should be lower for technologies which have a greater impact on NHS costs. Limitations: The central estimate is based on identifying a preferred analysis at each stage based on the analysis that made the best use of available information, whether or not the assumptions required appeared more reasonable than the other alternatives available, and which provided a more complete picture of the likely health effects of a change in expenditure. However, the limitation of currently available data means that there is substantial uncertainty associated with the estimate of the overall threshold. Conclusions: The methods go some way to providing an empirical estimate of the scale of opportunity costs the NHS faces when considering whether or not the health benefits associated with new technologies are greater than the health that is likely to be lost elsewhere in the NHS. Priorities for future research include estimating the threshold for subsequent waves of expenditure and outcome data, for example by utilising expenditure and outcomes available at the level of Clinical Commissioning Groups as well as additional data collected on QoL and updated estimates of incidence (by age and gender) and duration of disease. Nonetheless, the study also starts to make the other NHS patients, who ultimately bear the opportunity costs of such decisions, less abstract and more ‘known’ in social decisions. Funding: The National Institute for Health Research-Medical Research Council Methodology Research Programme.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3310/hta19140

Cites

112 of 112 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 112 references

Research works printed but not linked: 71

  1. 2008, Guide to the Methods of Technological Appraisal
  2. 2008, NICE: First report of the Health Committee 2007–2008
  3. 2004, Guide to the Methods of Technological Appraisal
  4. Williams, 2004, What Could be Nicer than NICE? OHE Annual Lecture
  5. Birch, 1993, Changing the problem to fit the solution: Johannesson and Weinstein’s (mis) application of economics to real world problems, J Health Econ, 12, 469, 10.1016/0167-6296(93)90006-Z · doi:10.1016/0167-6296(93)90006-z
  6. 2010, A New Value-Based Approach to the Pricing of Branded Medicines – a Consultation
  7. 2008, First Report of the Health Committee 2007–2008
  8. Abelson, 2003, The value of life and health for public policy, Econ Record, 79, S2, 10.1111/1475-4932.00087 · doi:10.1111/1475-4932.00087
  9. Johnson, 2006, Eliciting stated preferences for health-technology adoption criteria using paired comparisons and recommendation judgments, Value Health, 9, 303, 10.1111/j.1524-4733.2006.00119.x · doi:10.1111/j.1524-4733.2006.00119.x
  10. Mason, 2009, Modelling the monetary value of a qaly: a new approach based on UK data, Health Econ, 18, 933, 10.1002/hec.1416 · doi:10.1002/hec.1416
  11. Haninger, 2006, Willingness to Pay for Quality-Adjusted Life Years: Empirical Inconsistency Between Cost-effectiveness Analysis and Economic Welfare Theory
  12. Claxton, 2010, Appropriate Perspectives for Heath Care Decisions. CHE Research Paper 54
  13. Tappenden, 2007, A stated preference binary choice experiment to explore NICE decision making, Pharmacoeconomics, 25, 685, 10.2165/00019053-200725080-00006 · doi:10.2165/00019053-200725080-00006
  14. 2009, Appraising Life Extending End-of-Life Treatments
  15. 2012, Draft Guide to the Methods of Technology Appraisal
  16. 2008, NICE Response to the First Report of Session 2007–2008
  17. 2008, The Government’s Response to the Health Select Committee’s First Report of Session 2007–08 on the National Institute for Health and Care Excellence
  18. Collier, 2008, Parliamentary review asks NICE to do better still, BMJ, 336, 53, 10.1136/bmj.39454.496748.80 · doi:10.1136/bmj.39454.496748.80
  19. Martin, 2007, The Link Between Health Care Spending and Health Outcomes: Evidence from English Programme Budgeting Data. CHE Research Paper 24
  20. Martin, 2007, Further Evidence on the Link Between Health Care Spending and Health Outcomes in England. CHE Research Paper 32
  21. Martin, 2008, The Link Between Health Care Spending and Health Outcomes for the New English Primary Care Trusts. CHE Research Paper 42
  22. Martin, 2009, How Good at Commissioning Health are English Primary Care Trusts? A Preliminary Statistical Analysis. Report to the Health Foundation
  23. Martin, 2010, Panel Data Estimates of the Link Between Health Care Spending and Health Outcomes for English Primary Care Trusts
  24. Cochrane, 1997, Health service ‘input’ and mortality ‘output’ in developed countries, J Epidemiol Community Health, 51, 344, 10.1136/jech.51.4.344 · doi:10.1136/jech.51.4.344
  25. Young, 2001, An explanation of the persistent doctor–mortality association, J Epidemiol Community Health, 55, 80, 10.1136/jech.55.2.80 · doi:10.1136/jech.55.2.80
  26. St Leger, 2001, The anomaly that finally went away?, J Epidemiol Community Health, 55, 79, 10.1136/jech.55.2.79 · doi:10.1136/jech.55.2.79
  27. Nolte, 2004, Does Health Care Save Lives
  28. Gravelle, 1987, International cross-section analysis of the determination of mortality, Soc Sci Med, 25, 427, 10.1016/0277-9536(87)90167-5 · doi:10.1016/0277-9536(87)90167-5
  29. Moreno-Serra, 2011, The Effects of Health Coverage on Population Outcomes: A Country-Level Panel Data analysis
  30. 2009, PCT Recurrent Revenue Allocations Exposition Book: 2009/10 and 2010/11
  31. Smith, 2001, Capitation funding in the public sector, J R Stat Soc Series A, 164, 217, 10.1111/1467-985X.00200 · doi:10.1111/1467-985x.00200
  32. 2005, Recurrent Resource Allocations: 2006/07, 2007/08
  33. 2008, Good Governance Report: Review of Programme Budgeting
  34. Appleby, 2011, Explaining Variations in Primary Care Trusts’ Spending on Cancer Services
  35. Lakhani, 2006, Compendium of Clinical and Health Indicators: Data Definitions and User Guide for Computer Files
  36. 2005, Census 2001: General Report for England and Wales
  37. Dixon, 2011, A person based formula for allocating commissioning funds to general practices in England: development of a statistical model, BMJ, 343, d6608, 10.1136/bmj.d6608 · doi:10.1136/bmj.d6608
  38. Curtis, 2011, Unit Costs of Health and Social Care 2011
  39. Wailoo, 2010, The Incorporation of Health Benefits in Cost Utility Analysis Using the EQ-5D: Report by the Decision Support Unit
  40. Claxton, 2011, Value-based Pricing for Pharmaceuticals: Its Role, Specification and Prospects in a Newly Devolved NHS. CHE Research Paper 60
  41. Maynard, 2006, Seven years of feast, seven years of famine: boom to bust in the NHS?, BMJ, 332, 906, 10.1136/bmj.332.7546.906 · doi:10.1136/bmj.332.7546.906
  42. 2007, The Pharmaceutical Price Regulation Scheme. An OFT Market Study. VBP Report 2007
  43. 2011, TA237: Ranibizumab for the Treatment of Diabetic Macular Oedema
  44. 2012, Macular Oedema (Diabetic) – Ranibizumab (Rapid Review of TA237): Appraisal Consultation Document
  45. 2010, Single Technology Appraisal (STA) Manufacturer Submission: Lucentis® (Ranibizumab) for the Treatment of Visual Impairment due to Diabetic Macular Oedema (DMO)
  46. Broome, 1978, Trying to value a life, J Public Econ, 9, 91, 10.1016/0047-2727(78)90029-4 · doi:10.1016/0047-2727(78)90029-4
  47. Brock, 2006, How much is more life worth?, Hastings Cent Rep, 36, 17, 10.1353/hcr.2006.0036 · doi:10.1353/hcr.2006.0036
  48. Brouwer, 2008, The new myth – the social value of the QALY, Pharmacoeconomics, 26, 1, 10.2165/00019053-200826010-00001 · doi:10.2165/00019053-200826010-00001
  49. Maynard, 2010, The future role of NICE, BMJ, 341, 1006, 10.1136/bmj.c6286 · doi:10.1136/bmj.c6286
  50. Towse, 2002, Cost-Effectiveness Thresholds: Economic and Ethical Issues
  51. Speight, 2009, Wouldn’t it be NICE to consider patients’ views when rationing health care?, BMJ, 338, 297, 10.1136/bmj.b85 · doi:10.1136/bmj.b85
  52. Mason, 2009, Public funding of new cancer drugs: is NICE getting nastier?, Eur J Cancer, 45, 1188, 10.1016/j.ejca.2008.11.040 · doi:10.1016/j.ejca.2008.11.040
  53. Wooldridge, 2002, Econometric Analysis of Cross Section and Panel Data
  54. 2007, Payment by Results: Tariff Information
  55. 2005, Unified Exposition Book: 2003/04, 2004/05 and 2005/06 PCT Revenue Resource Limits
  56. Dixon, 2011, A person based formula for allocating commissioning funds to general practices in England: development of a statistical model, BMJ, 343, d6608, 10.1136/bmj.d6608 · doi:10.1136/bmj.d6608
  57. Kovandic, 2008, Estimating the Causal Effect of Gun Prevalence on Homicide Rates: A Local Average Treatment Effect Approach
  58. 2011, Provisional Monthly Patient Reported Outcome Measures (PROMs) in England: A Guide to PROMs Methodology
  59. 2012, Guide to the Methods of Technological Appraisal
  60. Murray, 1996, The Global Burden of Disease
  61. 2008, The Global Burden of Disease: 2004 Update
  62. Mathers, 2003, Global Burden of Disease in 2002: Data Sources, Methods and Results
  63. Gutacker, 2013, Truly inefficient or providing better quality of care? Analysing the relationship between risk-adjusted hospital costs and patients’ health outcomes, Health Econ, 22, 931, 10.1002/hec.2871 · DOI
  64. 2012, Provisional Monthly Patient Reported Outcome Measures (PROMs) in England
  65. 2009, CG82: Core Interventions in the Treatment and Management of Schizophrenia in Primary and Secondary Care
  66. 2009, CG90: Depression the Treatment and Management of Depression in Adults
  67. Mears, 2008, Progress on NICE guideline implementation in mental health trusts: meta-analyses, Psychiatrist, 32, 383
  68. Jarbrink, 2009, Quality of life and drug costs associated with switching antipsychotic medication to once-daily extended release quetiapine fumarate in patients with schizophrenia, Curr Med Res Opin, 25, 709, 10.1185/03007990902738810 · doi:10.1185/03007990902738810
  69. 2009, CG82: Schizophrenia (Update)
  70. 2007, CG90: Depression in Adults: The Treatment and Management of Depression in Adults
  71. 2011, A New Value-Based Approach to the Pricing of Branded Medicines: Government Response to Consultation

Cited by

See all 853

Metadata

Authors
Claxton, K., Martin, S., Soares, M., Rice, N., Spackman, E., Hinde, S., Devlin, N., Smith, P. C., & Sculpher, M.
Venue
Health Technology Assessment
Published
2015-02
Volume
19
Issue
14
Pages
1-504
ISSN
  • 1366-5278 (ISSN-L)
  • 2046-4924
OpenAlex
W166560170
Cited by
853
References
112
FWCI
204.22
Type
journal article
Language
en
Open access
diamond
Funders
National Institute for Health Research (06/92/54)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Methods for the estimation of the National Institute for Health and Care Excellence cost-effectiveness threshold. https://app.cochat.ai/papers/10.3310/hta19140
The paper
Claxton, K., Martin, S., Soares, M., Rice, N., Spackman, E., Hinde, S., Devlin, N., Smith, P. C., & Sculpher, M. (2015). Methods for the estimation of the National Institute for Health and Care Excellence cost-effectiveness threshold. Health Technology Assessment. https://doi.org/10.3310/hta19140

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.