Resources Repository
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GuidelinesPublication 2012State-Transition Modeling: A Report of the ISPOR-SMDM Modeling Task Force-3
State-transition modeling includes both Markov model cohort simulation as well as individual-based (first-order Monte Carlo) …
State-transition modeling includes both Markov model cohort simulation as well as individual-based (first-order Monte Carlo) microsimulation. These models have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs. Recommendations are made on choice of model type (cohort vs. individual-level model), model…
Microsimulation | Mathematical Models | State-Transition | Health/Medicine -
GuidelinesPublication 2012Modeling Using Discrete Event Simulation: A Report of the ISPOR-SMDM Modeling Task Force-4
This paper reports on consensus-based guidelines on the application of DES in a health care …
This paper reports on consensus-based guidelines on the application of DES in a health care setting, covering the range of issues to which DES can be applied. Discrete event simulation (DES) is a form of computer-based modeling that provides an intuitive and flexible approach to representing complex systems. The article works through the different stages of the modeling process: structural development, parameter estimation, model implementation, model analysis, and representation and reporting. Recommendations are made for…
Calibration/Validation | Evidence Synthesis | Mathematical Models | Dynamic Simulation | Health/Medicine -
GuidelinesPublication 2012Model Parameter Estimation and Uncertainty Analysis: A Report of the ISPOR-SMDM Modeling Task Force-6
This paper discusses methods for the reporting of uncertainty, both in terms of deterministic sensitivity …
This paper discusses methods for the reporting of uncertainty, both in terms of deterministic sensitivity analysis techniques and probabilistic methods. Stochastic (first-order) uncertainty is distinguished from both parameter (second-order) uncertainty and from heterogeneity, with structural uncertainty relating to the model itself forming another level of uncertainty. The article describes the process of estimating model inputs, whether these are point estimates or distributions. It also explores the link between parameter uncertainty, decision uncertainty, and value-of-information analysis.…
Calibration/Validation | Value of Information | Mathematical Models | Health/Medicine -
GuidelinesPublication 2011Calibrating Models in Economic Evaluation
This article provides guidance on the theoretical underpinnings of different calibration methods used for mathematical …
This article provides guidance on the theoretical underpinnings of different calibration methods used for mathematical models for economic evaluations. The calibration process is divided into seven steps and different potential methods at each step are discussed, focusing on the particular features of disease models in economic evaluation. The seven steps are (i) Which parameters should be varied in the calibration process? (ii) Which calibration targets should be used? (iii) What measure of goodness of fit…
Calibration/Validation | Mathematical Models | Health/Medicine -
ReviewPublication 2010Validation of Population-Based Disease Simulation Models: A Review
This article develops a framework for validating population-based chronic disease simulation models, and reviews the …
This article develops a framework for validating population-based chronic disease simulation models, and reviews the principles and methods for such models. While computer simulation models are used increasingly to support public health research and policy, questions about their quality persist. Based on the review, the authors formulated a set of recommendations for gathering evidence of model credibility. They find that evidence of model credibility derives from examining: 1) the process of model development, 2) the…
Calibration/Validation | Mathematical Models | Chronic Disease/Risk | Social Determinants | Health/Medicine -
ReviewPublication 2006Ethical Issues in Resource Allocation, Research, and New Product Development
Ethical dilemmas arising in setting priorities among interventions and among individuals in need of care …
Ethical dilemmas arising in setting priorities among interventions and among individuals in need of care are most acute when needs are great and resources few. This chapter from the Disease Control Priorities in Developing Countries 2nd edition addresses some of these concerns, identifying some of the principal ethical issues that arise in the development and allocation of effective interventions for developing countries and discussing some alternative resolutions. Resource allocation in health and elsewhere should satisfy two main…
Cost-Effectiveness Analysis | Preferences/Values | Priority Setting/Ethics | Culture/Society | Government/Law | Health/Medicine | Science/Technology -
ReviewPublication 2006Public Health Policy for Cervical Cancer Prevention: Decision Science, Economic Evaluation, & Mathematical Modeling
Several factors are changing the landscape of cervical cancer control, including a better understanding of …
Several factors are changing the landscape of cervical cancer control, including a better understanding of the natural history of human papillomavirus (HPV), reliable assays for detecting high-risk HPV infections, and a soon to be available HPV-16/18 vaccine. There are important differences in the relevant policy questions for different settings. By synthesizing and integrating the best available data, the use of modeling in a decision analytic framework can identify those factors most likely to influence outcomes,…
Cost-Effectiveness Analysis | Mathematical Models | Decision Analysis | Infectious Diseases | Chronic Disease/Risk | Economics/Finance | Health/Medicine | Science/Technology | Global -
ReviewPublication 2003Public Health Policy and Cost-Effectiveness Analysis
This chapter presents an overview of the uses for cost-effectiveness analysis and disease-simulation modeling to …
This chapter presents an overview of the uses for cost-effectiveness analysis and disease-simulation modeling to rigorously evaluate alternatives to reduce mortality from cervical cancer. Scientific advances have provided opportunities over time to revisit strategies for cervical cancer prevention. How to invest health resources wisely, such that public health benefits are maximized-and opportunity costs are minimized-is a critical question in the setting of enhanced cytologic screening methods, human papillomavirus DNA testing, and vaccine development. Developing sound…
Cost-Effectiveness Analysis | Mathematical Models | Infectious Diseases | Chronic Disease/Risk | Health Systems | Policy/Regulation | Health/Medicine | Global