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31 Assessing the long-term cost-effectiveness of natriuretic peptide-based screening and collaborative care in at risk population: analysis from the STOP-HF (St Vincent’s screening to prevent heart failure) study
  1. T Murphy1,
  2. M Ledwidge1,
  3. G Hopkins2,
  4. K McDonald1
  1. 1St Vincent’s University Hospital, Dublin, Ireland
  2. 2London School of Economics – Department of Health Policy, London, United Kingdom


Background Cardiovascular disease (CVD) and heart failure (HF) are associated with significant morbidity, mortality and costs in the developed world. Ischemic heart disease is the leading cause of death in the USA and combined with HF is predicted to cost >$320 billion per annum by 2030. Whilst there is evidence to suggest that secondary preventative strategies are cost effective, there is little research addressing primary cardiovascular prevention strategies in at risk populations. The St Vincent’s Screening TO Prevent Heart Failure (STOP-HF) study was the first study to demonstrate the benefits of screening and collaborative primary and secondary care of an at risk population using naturetic peptide. A detailed cost effectiveness analysis using the timeframe of the study and direct costs from the perspective of the healthcare provider has shown that the intervention is cost effective. However, the long-term outcomes and associated costs have not been modeled in a large population. The purpose of this study is to establish the costs, benefits and cost-effectiveness of implementing a STOP-HF program in a large population over a 20 year timeframe.

Methods and results A Markov state-transition model was used to extrapolate results beyond the follow-up period of the STOP-HF trial to a horizon of 20 years from the Irish health service perspective. The model included four states, which provided for progression from an ‘At risk’ status to progressively worsening stages of heart failure. Figure 1. Transition probabilities were derived from the STOP-HF trial, a comprehensive meta-analysis and Irish life tables. Costs were calculated using a micro costing approach. A sensitivity analysis was performed using a second order probabilistic sensitivity analysis based on 1000 iterations using distributions appropriate to the variable, log-normal distributions for the ORs, and gamma distributions for the costs. Table 1. In our model, the age of enrolment was 60 years old, with a 20 year life span simulation. Preliminary results suggest that for every 1000 patients enrolled in STOP HF, approximately 418 life years (±6.8 years 95% CI) are gained over a 20 year period. Enrolling 1000 patients in STOP HF and following that population over 20 years results in a cost saving of $2.4 million (±0.22 million 95% CI). 91.1% of trials in the probabilistic sensitivity analysis supported this finding suggesting a high level of certainty in this interpretation. Table 2. Figure 2.

Abstract 31 Table 1

Transition probabilities and costs

Abstract 31 Table 2

Cost effectiveness results

Abstract 31 Figure 1

Demonstrating 4 stage markov model

Abstract 31 Figure 2

Results of probabilistic sensitivity analysis

Conclusion These findings suggest that the STOP-HF program is both cost saving and life prolonging. The majority of the savings are from maintaining patients in better health states by predicting those who would benefit most from collaborative care; enrolling them in the program; protecting them from developing Stage B heart failure or hospitalization and preventing increased morbidity and mortality.

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