Discretely Integrated Condition Event (DICE) Simulation

Our Solutions Clinical Development PPD Evidera Health Economics & Market Access PPD Evidera Health Economics DICE

Delivering a transparent and flexible approach to health economic models

Decision analytic modeling techniques are used to inform health technology assessments (HTAs), playing a significant role in pricing and reimbursement decisions globally. A wide range of modeling methods are used, such as decision trees, Markov models, and discrete event simulation. These methods were originally borrowed from other fields, in the absence of any health economic-specific tools, and consequently their application in health economics (HE) often leads to oversimplification of the problem and/or loss of transparency.

Discretely Integrated Condition Event (DICE) simulation is a unifying approach specifically designed to meet HE modeling needs for accurate representation of the HTA decision problem. Gain value throughout the lifecycle, from early modeling through formal HE submissions, with an approach that is widely accepted and implemented, including use by many companies for their HE models.

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Core components of DICE

The core components of DICE are events and conditions, which are integrated at discrete time points. This simple structure can be used to reflect any aspect of a disease and its management, including valuation (e.g., quality-adjusted life years [QALYs], costs) of outcomes of interest.

With the ability to represent whatever pathways are relevant, its application ranges from basic cost-consequences and budget impact analyses to full cost-effectiveness, cost-utility, and even Multi-Criteria Decision Analysis (MCDA).

Advantages of DICE

Simple concept The two concepts (conditions, events) that define a DICE are straightforward and realistically match disease processes and their management. DICE can even combine cohort Markov, individual, and time-to-event approaches in a hybrid model.
Standard framework Users and reviewers do not need to “relearn” each new model since DICE uses a standard framework, standard terminology and a generic macro. The disease-specific terms will change, but the structuring and implementation remain consistent across models.
Easily understood and communicated DICE is very easy to understand and navigate. Even a person completely unfamiliar with modeling should be able to quickly understand the concept and review a DICE model.
Extremely flexible and transparent A variety of programming languages, including standard MS Excel, R, C# and Python, can be used for DICE implementation, with no add-ons or other requirements. This provides users with the ability to easily share a model across groups, make adaptations and provide critical reviews.

DICE simulation is very flexible, accommodating anything from very simple models to vast complex structures, while remaining transparent and easy to debug. The technique can appropriately address all the components of the research question, eliminating the structural limitations of other methods.

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An efficient approach to DICE using AI and wizards

We have developed user-friendly and transparent artificial intelligence (AI) tools and wizards to design and implement a DICE model.

Reduce the burden of programming and verification while minimizing errors that impair trust in modeled outcomes.

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Download our DICE demos

Explore the functionality and options DICE offers through various DICE models, including Markov, Hybrid Simulation, Micro-Simulation, Time to Event, and Basic Oncology.

Complete this form to download selected demos to compare and identify the value DICE can bring to your health economic modeling needs.