Abstract
BackgroundThe prevention and treatment of coronary heart disease (CHD) is complex. A variety of models have therefore been developed to try and explain past trends and predict future possibilities. The aim of this systematic review was to evaluate the strengths and limitations of existing CHD policy models.MethodsA search strategy was developed, piloted and run in MEDLINE and EMBASE electronic databases, supplemented by manually searching reference lists of relevant articles and reviews. Two reviewers independently checked the papers for inclusion and appraisal. All CHD modelling studies were included which addressed a defined population and reported on one or more key outcomes (deaths prevented, life years gained, mortality, incidence, prevalence, disability or cost of treatment).ResultsIn total, 75 articles describing 42 models were included; 12 (29%) of the 42 models were micro-simulation, 8 (19%) cell-based, and 8 (19%) life table analyses, while 14 (33%) used other modelling methods. Outcomes most commonly reported were cost-effectiveness (36%), numbers of deaths prevented (33%), life-years gained (23%) or CHD incidence (23%). Among the 42 models, 29 (69%) included one or more risk factors for primary prevention, while 8 (19%) just considered CHD treatments. Only 5 (12%) were comprehensive, considering both risk factors and treatments. The six best-developed models are summarised in this paper, all are considered in detail in the appendices.ConclusionExisting CHD policy models vary widely in their depth, breadth, quality, utility and versatility. Few models have been calibrated against observed data, replicated in different settings or adequately validated. Before being accepted as a policy aid, any CHD model should provide an explicit statement of its aims, assumptions, outputs, strengths and limitations.
Highlights
The prevention and treatment of coronary heart disease (CHD) is complex
Clinical trials will never provide all the answers, since their study groups are restricted with inclusion and exclusion criteria; generalisation is always an issue [2]
In this paper we have systematically reviewed and evaluated the strengths and limitations of existing CHD policy models
Summary
The prevention and treatment of coronary heart disease (CHD) is complex. A variety of models have been developed to try and explain past trends and predict future possibilities. Improving population health through effective interventions remains a fundamental challenge for policy makers. Decision-makers at the population and individual levels each need to choose the 'best intervention' for a specific health problem. Limitations on resources, time and information can make this decision process difficult. This is true for cardiovascular disease, its diversity of manifestations and wealth of effective interventions are potentially complex and confusing. Weinstein has usefully defined a model as, "a logical mathematical framework that permits the integration of facts and values to produce outcomes of interest to clinicians and decision makers" or, alternatively as: "an analytical methodology that accounts for events over time and across populations based on data drawn from primary or secondary sources"[3]
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