Monitoring and management of chronic heart failure in primary care: an overview of economic models

Conference:

SAPC ASM 2019 - Exeter

Talk Code:

P2.42

Presenter:

Claire Simons

Co-authors:

Amitava Banerjee, Carl Heneghan, Clare Taylor, Richard Hobbs, Rafael Perera, Borislava Mihaylova

Author institutions:

Health Economics Research Centre Nuffield Department of Population Health University of Oxford, Farr Institute of Health Informatics Research Institute of Health Informatics University College London, Nuffield Department of Primary Care Science University of Oxford, Centre for Primary Care and Public Health Queen Mary University of London

Problem

There is a growing interest in strengthening the evidence for heart failure management in primary care. We aimed to review health economic models used to answer research questions related to the cost-effectiveness of heart failure monitoring and management strategies and interventions in primary care with a focus on model structures and data used.

Approach

We updated a previous review of cost-effectiveness models in heart failure by Goehler et al. (2011) with 8 further years of data up to August 2018. Analytical frameworks used to evaluate heart failure treatments and management programmes in primary care were identified. Models were excluded if they were exclusively within secondary care or if they presented local non-UK adaptations of already included models.

Findings

Forty-three studies were identified of which three studied heart failure diagnosis; 11 management strategies and 29 drug interventions. The severity of heart failure was mostly based on New York Heart Association stages (with or without cardiovascular event history) or number of hospital admissions for heart failure. 34 models used a Markov model structure with the remaining using decision trees, mathematical equations or discrete event simulations. There was limited use on individual patient characteristics in the models with 13 (30%) models incorporating such information though this approach is more frequently considered in recent models (43% of those published since 2010). The data used to inform the parameters in the models (disease risks, quality of life and costs) were sourced predominantly from randomised trials in chronic heart failure patients in secondary care. All studies used some data from randomised trial data, with 31 (72%) of models fully developed using trials’ data. These trials were frequently completed some years previously and were unlikely representative of the chronic heart failure population seen in primary care in primary care in terms of the current prognosis of contemporary patients with heart failure or the range of stages of heart failure observed in the community.

Consequences

Future models should aim to employ primary care data, include individual patient characteristics and consider important markers of progression of chronic heart failure in patients typically seen in primary care.

Submitted by:

Claire Simons

Funding acknowledgement:

Funded by the NIHR PGfAR programme (RP-PG-1210-12003) and NIHR Biomedical Research Centre, Oxford. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.