Background: Data from the health care domain is often reused to create and parameterize simulation models for example to support life science business in the evaluation of new products. Data quality assessments play an important part to help model users in interpreting simulation results by showing deficiencies in the raw data used in the model building and offers model builders a comparison of data quality amongst the used data assets.

Objectives: Assess data quality in raw data prior to creating simulation models and prepare results for model users.

Methods: Using a literature review and documentation of previous models created, we searched data quality criteria. For eligible criteria we formulated questions and viable answers to be used in a questionnaire to assess data quality of a data asset.

Results: We developed a web tool to evaluate data assets using a generic data model. Percentage results are visualized using a radar chart.

Conclusion: Data quality assessment with questionnaires offers model builders a framework to critically analyse raw data and to detect deficiencies early in the modelling process. The summarized results can help model users to better interpret simulation results.