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Getting cost-effective technologies into practice: the value of implementation. An application to b-type natriuretic peptide (BNP) testing in diagnosing chronic heart failure

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posted on 2024-02-15, 23:21 authored by Sophie WhyteSophie Whyte, Simon DixonSimon Dixon, Rita Faria, Simon Walker, Stephen Palmer, Mark Sculpher

In 2010 NICE released a clinical guideline recommending that natriuretic peptide (NP) testing in patients with suspected heart failure without previous myocardial infarction can accelerate diagnosis of heart failure and also avoid unnecessary echocardiography. A framework for the evaluation of the value of implementation activities is applied to this recommendation for NP testing.

1.2 Methods

The following quantities were estimated: expected value of perfect implementation (the maximum the NHS can invest on implementation activities whilst still accruing some positive value from the intervention); expected value of actual implementation (the maximum the NHS can invest on implementation activities for specific increases in utilisation); and value of the implementation activity (the additional value of the specific implementation activity given its expected costs and effectiveness).

Data sources used to inform the model included: published data on disease incidence; cost-effectiveness data from a published Health Technology Assessment (HTA) which informed the clinical guidelines; cost and effectiveness evidence from an intervention designed to increase NP utilisation in London; data on utilisation and disease incidence from a clinical expert; audit data on NP testing utilisation; and a systematic review of implementation initiatives. Diffusion curves were estimated based on historic data to produce predictions of future utilisation. Incremental costs and quality-adjusted life years (QALYs) of N testing compared to ‘do nothing’ were estimated to be -£3.88 and 0.08 respectively. The annual suspected Heart Failure (HF) population in England and Wales was estimated to be 210,000. Current utilisation and optimal maximum utilisation of NP testing were estimated to be 4.4 and 8.6 per 1,000 population respectively. The implementation intervention was estimated to cost approximately £24K and assumed to result in an absolute increase in utilisation of 5%. Both a static population analysis and multi-period analysis were undertaken and results are presented for cost-effectiveness thresholds of £20,000 and £30,000 per QALY gained.

1.3 Results

There appeared to be considerable value in additional implementation efforts directed towards encouraging the utilisation of NP testing for persons with suspected HF. At a threshold of £20,000 per QALY gained, additional investment in an activity that increases utilisation by 5% (absolute increase in utilisation rates) would generate an additional 799 QALYs (£16 million in terms of monetary equivalent) across England and Wales, compared to the use of these resources in other (health generating) National Health Service (NHS) activities. Scenario analyses demonstrated that value to the NHS was sensitive to uncertain model inputs such as the size of the eligible population and the efficacy of the implementation intervention. The analysis highlighted a lack of evidence on: cost effectiveness, effectiveness of implementation intervention, utilisation, and population size.

1.4 Conclusions

This framework can be applied to any existing cost effectiveness analysis, thus helping a decision maker to quantify the value of investing resources into increasing utilisation in a manner consistent with the value assessment of new interventions conducted by the National Institute for Health and Care Excellence (NICE). This case study provides a useful demonstration of the practical challenges faced in populating such a model. In particular, the importance of publishing incremental costs and QALYs related to clinical guidelines compared to current care is highlighted. Data on diffusion of utilisation is crucial for such evaluations.

Funding

NIHR Policy Research Unit - Economic Methods of Evaluation in Health and Care Interventions

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