Introduction: This empirical work examines the information requirements when undertaking a process modelling project in a Healthcare setting such as a CT (Computed Tomography) department. Using qualitative and quantitative methods we map the process, incorporating patient, staff and process related components so as to quantify resource utilisation and the service experienced by the patient. Method: In this study, semi structured interviews are used to identify patient complexity factors/characteristics. Process mapping and involvement of stakeholders are discussed as is the identification and analysis of data. A discrete event simulation (DES) model of the process is designed and performance metrics identified. Results: Yearly demand for Radiology services are increasing significantly. Factors determining patient complexity and variation include patient type, infectiousness, mobility, exam type and patient care needs. A strong correlation between age and infectiousness was observed. C onclusion: DES modelling, though data intensive, provides decision makers with insights into resource utilisation, process capacity, delays and disruptions and in doing so supports operations, management and the adoption of good practices in Healthcare.