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Operations research techniques are widely used to analyse and optimise emergency department operations. The complex and stochastic nature of an emergency department makes simulation a suitable and frequently used technique. Simulation can provide valuable insights to hospital managers on how to improve the efficiency of an emergency department. However, the output of the simulation study is only as reliable as the input data used as basis for simulation modelling. As a result, high quality input data are essential for the construction of a realistic simulation model. This paper provides a data quality framework that categorises possible data quality problems in electronic healthcare records of emergency departments. Electronic healthcare records are a common source of input data for emergency department simulations, but often suffer from data quality issues. For the data quality problems identified in the framework, data quality assessment techniques are described. These techniques enable researchers and practitioners to identify and quantify the potential data quality issues present in input data. In order to facilitate data quality assessment, an implementation to automate this process is developed and applied to a real-life case study. This case study demonstrates the need for thorough and structured data quality assessment. Possible ways to deal with identified data quality problems are also described.

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