Related Experiment Video
Updated: Jul 16, 2026
20:24
Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Published on: January 31, 2014
Applications of modelling studies
1Lewin Group, Hoofddorp, The Netherlands. mnuyten@qbnt.quintiles.com
Pharmacoeconomics
|February 6, 1998
Summary
Economic evaluation and decision-analytical models aid healthcare resource allocation. These models supplement clinical data for reimbursement, program development, and disease management strategies.
Area of Science:
- Health economics
- Decision science
- Health services research
Background:
- Economic evaluations are crucial for allocating limited healthcare resources.
- Prospective clinical studies may not provide all necessary economic data.
- Decision-analytical models offer a solution to bridge information gaps.
Purpose of the Study:
- To discuss the applications of decision-analytical models in healthcare.
- To highlight the utility of these models beyond clinical trials.
- To inform decision-makers on leveraging models for resource allocation.
Main Methods:
- Review and discussion of various applications of decision-analytical models.
- Exploration of model use in reimbursement submissions.
- Analysis of model integration into pharmacoeconomic development.
Main Results:
- Decision-analytical models support reimbursement authority submissions.
- Models are valuable for pharmacoeconomic program development.
- Applications extend to portfolio investment and marketing strategies.
Conclusions:
- Decision-analytical models are versatile tools in health services.
- They enhance resource allocation decisions by providing missing economic information.
- Model applications span from reimbursement to disease management.
Related Concept Videos
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
01:12Modeling and Similitude
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
01:30Typical Model Studies
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
01:26Modeling in Therapy
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in situations...
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in situations...
01:29Mathematical Modeling: Problem Solving
Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...