Resources Repository
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ReviewPublication 2015Decision-Analytic Modeling Studies of Multiple Myeloma
This review provides an overview of decision-analytic models evaluating different treatment strategies for multiple myeloma …
This review provides an overview of decision-analytic models evaluating different treatment strategies for multiple myeloma and is based on a systematic literature search to identify studies evaluating treatment strategies using mathematical decision-analytic models. Studies were included that assessed relevant clinical endpoints, and summarized methodological characteristics (e.g., modeling approaches, simulation techniques, health outcomes, perspectives). Eleven decision-analytic modeling studies met inclusion criteria. Five different modeling approaches were adopted: decision-tree modeling, Markov state-transition modeling, discrete event simulation, partitioned-survival analysis and…
State-Transition | Mathematical Models | Microsimulation | Dynamic Simulation | Chronic Disease/Risk | Health/Medicine -
ReviewPublication 2015Agent-Based Models and Microsimulation
This article reviews the principles and applications of agent-based models (ABMs). ABMs are computational models …
This article reviews the principles and applications of agent-based models (ABMs). ABMs are computational models used to simulate the actions and interactions of “agents” within a system. Usually, each agent has a set of rules for how he or she responds to the environment and to other agents. These models are used to gain insight into the emergent behavior of complex systems with many agents, in which the emergent behavior depends upon the micro-level behavior…
State-Transition | Mathematical Models | Microsimulation | Dynamic Simulation | Energy/Engineering | Health/Medicine | Military/Defense | Science/Technology -
ReviewPublication 2014Markov Modeling & Discrete Event Simulation in Health Care: Systematic Comparison
This review assesses whether the use of Markov modeling (MM) or discrete event simulation (DES) …
This review assesses whether the use of Markov modeling (MM) or discrete event simulation (DES) for cost-effectiveness analysis (CEA) may alter healthcare resource allocation decisions. A systematic literature search and review of empirical and non-empirical studies comparing MM and DES techniques used in the CEA of healthcare technologies was conducted. The primary advantages described for DES over MM were the ability to model queuing for limited resources, capture individual patient histories, accommodate complexity and uncertainty,…
State-Transition | Mathematical Models | Microsimulation | Health Systems | Clinical Care | Health/Medicine -
ReviewPublication 2011Dynamic Microsimulation Models for Health Outcomes: A Review
This review article presents an overview of microsimulation modeling, focusing on the development and application …
This review article presents an overview of microsimulation modeling, focusing on the development and application of these models for health policy questions. Microsimulation models for health outcomes simulate individual event histories associated with key components of a disease process; these simulated life histories can be aggregated to estimate population-level effects of treatment on disease outcomes and the comparative effectiveness of treatments. The authors argue that methodological improvements in modeling approaches have been slowed by the…
Calibration/Validation | Health Outcomes | Microsimulation | 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