> Research

In this section

Health-Economics    

Epidemiology and
Population Health

Risk Assessment

Methodological
Development

Publications

Intelligence, Research, and Optimization

GLOBMOD activities focuses on the science and on the economics of health, providing analyses, and developing methods and tools to address questions such as:

What is the optimal way to improve population health with the available economic resources?

How do we measure the health and economic impact of individual technologies, programs, and policies? 

How much health can be gained by investing in a specific treatment, vaccine, or medical device?

How much health can be gained by implementing a given intervention, program, or policy, at the national or sub-national level?

Which segments of the populations are most likely to benefit from the adoption of a given health technology or from the implementation of a program?

Which environmental and behavioral factors can cause and which can prevent diseases? And to what extent?

What is the risk, and the likely impact, of a pandemic or of a natural disaster?

How can we improve measurement and understanding of determinants of health?

What is the cost of poor health to individual patients and to health-systems?

How can we ensure a more efficient and equitable access to healthcare?

To answer these questions:

1. We search, retrieve, analyze, and appraise data obtained from surveys, clinical studies, economic studies, or recorded by service-providers, e.g. providers of Healthcare, IT, Media, etc., and we also elicit information from experts and healthcare professionals > Evidence;
2. We identify the variables having the greatest impact, and their dynamical inter-connection and connection to the outcomes of interest (e.g. cost, savings, mortality, QALYs, DALYs, HALYs, etc.) > Model Design;
3. We then conceptualize the problem mathematically and build an algorithm that is implemented in an appropriate software environment > Model Implementation;
4. We ensure that the software performs according to the model and produces results that are internally consistent. Whenever possible, we use independent real world data to validate the model > Software Debugging and Model Validation;
5. We run the software to simulate possible scenarios, to quantify the likelihood of different outcomes, and to quantify and analyze the uncertainty surrounding model estimates > Simulation;
6. We interpret and compare the results and identify the most useful and effective tools to share assumptions, results, and conclusions with potential users (e.g. decision makers) and with any other relevant party > Analysis and Dissemination.

In particular we cover the following areas:

  - Health-Technology Assessment;
  - Modeling and Simulation of:
      Disease Dynamics;
      Health Interventions;
      Health Programs;
      Instruments of Health Policy;
  - Burden of Illness Studies;
  - Design and Interpretation of Studies;
  - Epidemiological Risk Analysis;
  - Modeling of Rare or Extreme Events.

We produce software solutions for:

  - Priority-Setting in Public Health;
  - Burden of Illness Studies;
  - Risk Assessment.

Methods
We extract evidence using one or more of the following techniques:

  - Machine Learning;
  - Statistical Data Analysis;
  - In-depth Literature Review;
  - Systematic Literature Review;
  - Meta-analysis of Literature Review.

Depending on need, we implement models using one or more of the following techniques:

  - Agent-Based Simulation;
  - Discrete-Time Simulation;
  - Markov Cohorts;
  - Markov-Chain Montecarlo Simulation;
  - Ordinary Differential Equations;
  - Stochastic Differential Equations;
  - Decision Trees;
  - Multi-Level Regressions
  - Bayesian Networks.

Software
We work with the following software packages:

  - In-house produced code in C/C++
  - MS Excel + VBA;
  - R;
  - Berkeley-Madonna.

On demand we can work with:

  - TreeAge;
  - Matlab.

Other software environments may also be considered, depending on project needs.