Forecasting coronary heart disease incidence, mortality, and cost: the Coronary Heart Disease Policy Model.

Weinstein, Milton C.; Coxson, Pam; Williams, Larry W.; Pass, Theodore M.; Stason, William B.; Goldman, Lee

doi:10.2105/ajph.77.11.1417

Cited by 333 publications

(201 citation statements)

References 33 publications

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“…Cholesterol reductions of 1% to 4% at per capita costs of $4.95 to $16.55 were obtained. Tosteson et al (66) used these findings as inputs to the CHD Policy Model, a computerized, state-transition model of CHD in the US population (32,74). The CHD Policy Model employs logistic regression equations linking risk factors including cholesterol to CHD incidence, based on data from the Framingham Heart Study and other sources.…”

Section: Coronary Heart Diseasementioning

confidence: 99%

Evaluating the Cost-Effectiveness of Clinical and Public Health Measures

Graham

Corso

Morris

et al. 1998

Annu. Rev. Public Health

133

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Cost-effectiveness analysis, an analytic tool that expresses as a ratio the cost of obtaining an additional unit of health outcome, can help decision makers achieve more health protection for the same or less cost. We characterize the state of the cost-effectiveness analysis literature by reviewing how this technique is applied to various clinical and public health interventions. We describe the results of cost-effectiveness analyses for over 40 interventions to reduce cancer, heart disease, trauma, and infectious disease. The cost-effectiveness ratios for these interventions vary enormously, from interventions that save money to those that cost more than $1 million per year of life gained. The methods used to derive the cost-effectiveness ratios also vary considerably, and we summarize this variation within each health area. Greater uniformity of analytical practice will be necessary if cost-effectiveness analysis is to become a more influential tool in debates about resource allocation.

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Section: Coronary Heart Diseasementioning

confidence: 99%

Evaluating the Cost-Effectiveness of Clinical and Public Health Measures

Graham

Corso

Morris

et al. 1998

Annu. Rev. Public Health

133

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“…81% of patients were older than 60 years of age. This goes against published by Weinstein et al [7], reporting the progressive increase in the number of elderly patients who present to the Department of cardiac surgery (Table 3).…”

Section: Fig 1 -Distribution Of the Population Who Had Surgical Site mentioning

confidence: 56%

Prevalência de infecções em suturas de cirurgias de revascularização do miocárdio

Assunção

Pontes²,

Damasceno³

2011

Rev Bras Cir Cardiovasc

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“…A special type of state-transition model, in which the transition probabilities depend only on the current state (and not, for example, on the previous states or the path by which the current state was entered), is called a Markov model. 46 State-transition models have been used to estimate outcomes in a large number of cost-effectiveness studies, including coronary heart disease prevention 47 and treatment 48 ; breast, 49 cervical, 50 and prostate cancer screening 51 ; and hormone replacement therapy. 52 Decision tree models can also be augmented to include "Markov nodes," or …”

Section: Analytic Methodologymentioning

confidence: 99%

“…The model CAN*TROL and the Coronary Heart Disease Policy Model are examples of crosssectional population models. 47,56 The choice of a cross-sectional or longitudinal model is determined by the problem being studied. For instance, a cross-sectional model may be used to ask public health questions about interventions that are to be applied population-wide to groups of varying ages; a longitudinal model may be used to ask questions about the long-term effects of an intervention on an age-specific group.…”

Section: Longitudinal and Cross-sectional Modelsmentioning

confidence: 99%

Assessing the effectiveness of health interventions for cost-effectiveness analysis

Mandelblatt¹,

Fryback²,

Weinstein³

et al. 1997

J Gen Intern Med

101

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C ost-effectiveness analysis (CEA) is an analytic tool in which the costs and effects of an intervention designed to prevent, diagnose, or treat disease are calculated and compared with an alternative strategy to achieve the same goals. The results of a CEA are presented as a ratio of costs to effects, where the effects are health outcomes such as cases of disease prevented, years of life gained, or qualityadjusted life years gained, rather than monetary measures, as in cost-benefit analysis. Conducting a CEA requires a framework for portraying the cascade of events that occur as a consequence of the decision to intervene, for describing the probability that each event will occur, for accounting how long each event will last, and describing how much each event costs and is valued by the population or individuals targeted by the intervention. Mathematical models are well suited to these purposes.The purpose of this article is to provide an overview of modeling to estimate net effectiveness in a CEA (the difference in effectiveness between an intervention and the alternative to which it is being compared). Many of the principles described for estimating effectiveness apply equally to determining costs in a CEA. The main difference is that health events are weighted by costs in the numerator of the cost-effectiveness ratio, while they are often weighted by preference values in the denominator. Preference values, or utilities, reflect the fact that individuals or populations with similar ability (or disability) to function may regard that level of functioning differently. When preferences are incorporated into CEAs, the results are generally expressed as costs per quality-adjusted life years. 1,2 A discussion of measurement of costs and valuing outcomes is beyond the scope of this article; for further information on these, and other components of a CEA, the reader is referred elsewhere. [3][4][5] Following some definitions of terms, this article is organized into two sections describing the process of estimating effectiveness in a CEA: the first presents a review of the sources of event probabilities, and the second describes the use of modeling to estimate effectiveness. DEFINITIONSEffectiveness, which reflects the impact of an intervention of health in real practice settings, should be distin-

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Forecasting coronary heart disease incidence, mortality, and cost: the Coronary Heart Disease Policy Model.

Cited by 333 publications

References 33 publications

Evaluating the Cost-Effectiveness of Clinical and Public Health Measures

Evaluating the Cost-Effectiveness of Clinical and Public Health Measures

Prevalência de infecções em suturas de cirurgias de revascularização do miocárdio

Assessing the effectiveness of health interventions for cost-effectiveness analysis

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