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Headline
This study suggests that developing a computer model with end-users leads to a more user-friendly and relevant model to improve the delivery of the NHS Health Check programme.
Abstract
Background:
Local authorities in England commission the NHS Health Check programme to invite everyone aged 40–74 years without pre-existing conditions for risk assessment and eventual intervention, if needed. However, the programme’s effectiveness, cost-effectiveness and equity impact remain uncertain.
Aim:
To develop a validated open-access flexible web-based model that enables local commissioners to quantify the cost-effectiveness and potential for equitable population health gain of the NHS Health Check programme.
Objectives:
The objectives were as follows: (1) co-produce with stakeholders the desirable features of the user-friendly model; (2) update the evidence base to support model and scenario development; (3) further develop our computational model to allow for developments and changes to the NHS Health Check programme and the diseases it addresses; (4) assess the effectiveness, cost-effectiveness and equity of alternative strategies for implementation to illustrate the use of the tool; and (5) propose a sustainability and implementation plan to deploy our user-friendly computational model at the local level.
Design:
Co-production workshops surveying the best-performing local authorities and a systematic literature review of strategies to increase uptake of screening programmes informed model use and development. We then co-produced the workHORSE (working Health Outcomes Research Simulation Environment) model to estimate the health, economic and equity impact of different NHS Health Check programme implementations, using illustrative-use cases.
Setting:
Local authorities in England.
Participants:
Stakeholders from local authorities, Public Health England, the NHS, the British Heart Foundation, academia and other organisations participated in the workshops. For the local authorities survey, we invited 16 of the best-performing local authorities in England.
Interventions:
The user interface allows users to vary key parameters that represent programme activities (i.e. invitation, uptake, prescriptions and referrals). Scenarios can be compared with each other.
Main outcome measures:
Disease cases and case-years prevented or postponed, incremental cost-effectiveness ratios, net monetary benefit and change in slope index of inequality.
Results:
The survey of best-performing local authorities revealed a diversity of effective approaches to maximise the coverage and uptake of NHS Health Check programme, with no distinct ‘best buy’. The umbrella literature review identified a range of effective single interventions. However, these generally need to be combined to maximally improve uptake and health gains. A validated dynamic, stochastic microsimulation model, built on robust epidemiology, enabled service options analysis. Analyses of three contrasting illustrative cases estimated the health, economic and equity impact of optimising the Health Checks, and the added value of obtaining detailed local data. Optimising the programme in Liverpool can become cost-effective and equitable, but simply changing the invitation method will require other programme changes to improve its performance. Detailed data inputs can benefit local analysis.
Limitations:
Although the approach is extremely flexible, it is complex and requires substantial amounts of data, alongside expertise to both maintain and run.
Conclusions:
Our project showed that the workHORSE model could be used to estimate the health, economic and equity impact comprehensively at local authority level. It has the potential for further development as a commissioning tool and to stimulate broader discussions on the role of these tools in real-world decision-making.
Future work:
Future work should focus on improving user interactions with the model, modelling simulation standards, and adapting workHORSE for evaluation, design and implementation support.
Study registration:
This study is registered as PROSPERO CRD42019132087.
Funding:
This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 35. See the NIHR Journals Library website for further project information.
Contents
- Plain English summary
- Scientific summary
- Chapter 1. Background and aims
- Chapter 2. Co-producing the specifications of the workHORSE model
- Chapter 3. Updating the evidence base to inform scenario design and model
- Chapter 4. The workHORSE model
- Chapter 5. Using the workHORSE model to explore and compare the effectiveness, cost-effectiveness and equity impact of different implementations of the NHS Health Check programme
- Chapter 6. Implementation plan
- Chapter 7. Discussion, next steps and conclusions
- Acknowledgements
- References
- Appendix 1. Best-performing local authorities survey methodology
- Appendix 2. A PRISMA flow chart for the umbrella review on invitation methods to increase uptake in screening programmes
- Appendix 3. Summary table of individual studies included in the umbrella review on invitation methods to increase uptake in screening programmes
- Appendix 4. workHORSE methods
- Appendix 5. workHORSE validation plots
- Appendix 6. Health economics methods
- Appendix 7. Detailed inputs to inform analysis 3 scenarios (see Chapter 5)
- Appendix 8. workHORSE installation instructions
- Appendix 9. Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist
- Glossary
- List of abbreviations
About the Series
Declared competing interests of authors: Brendan Collins is a member of the Health Services and Delivery Research Research Led Panel.
Article history
The research reported in this issue of the journal was funded by the HTA programme as project number 16/165/01. The contractual start date was in November 2017. The draft report began editorial review in February 2020 and was accepted for publication in December 2020. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The HTA editors and publisher have tried to ensure the accuracy of the authors’ report and would like to thank the reviewers for their constructive comments on the draft document. However, they do not accept liability for damages or losses arising from material published in this report.
Last reviewed: February 2020; Accepted: December 2020.
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