## 3 Results
### Facilitation of Good Quality Model Design  
For the second pilot, a small team with no previous experience using a modelling tool was tasked with modelling additional concepts associated with the CCPDD. The more sophisticated design of the modelling tool compared to the Microsoft Excel spreadsheet prompted discussions about the structure of the models that had previously been defined in Excel and how they would fit as the data dictionary increased in size and complexity. This included discussions about reusability of data items and how to structure models so that they could potentially have a more general application. The team agreed that the modelling tool directly facilitated these conversations about modelling aspects that had been overlooked when using Excel and, to an extent, provided a learning environment for colleagues who had no prior experience with data modelling.  
As well as helping to define the structure of the data items, the modelling tool also prompted discussions about the cardinality and conformance of data items which was not addressed in the Excel version of the CCPDD.  
As described above, the modelling tool provided a platform for discussion and for reaching consensus around building more complex and reusable data models, but it was recognised that the models also needed to be exportable to EDC systems to work in a  
Figure 4: Image showing the ‘Element’ section in an ‘Entry’ page in Direcht.  
real-world setting. The more structured approach of the modelling tool also highlighted gaps in knowledge which resulted in the pilot team reaching out to colleagues within the c4c consortium for guidance on how to model 'Pubertal Status' concepts from the Excel version of the CCPDD as shown in Figure 5 below. The data items 'Male Genitalia Stage', 'Male Public Hair Stage', 'Female Breast Stage', 'Female Public Hair Stage', 'Date of Menarche', 'Age of Menarche', and 'Testicular Volume' all existed in the Excel version of the CCPDD. Most of these data items were included as part of the Tanner Scales. This step could have potentially been simplified if the original model had been created in a more structured way and demonstrated one of the advantages of using a modelling tool over Microsoft Excel.  
In the period between the finalisation of CCPDDv1 and modelling the pubertal status concepts described above, the CDISC published examples of how these concepts are represented in CDISC standards [24]. The pubertal status models were mapped to the new user guide within Direcht, as shown in Figure 6 below. As with the Microsoft Excel version of the CCPDD, mapping to standards within the modelling tool is done manually by searching for the online link and copying and pasting it into the space provided. While this does not initially seem to offer an obvious advantage over Excel, it does provide a clear list of the standards associated with the model.  
In summary, using a modelling tool facilitated the discipline of providing unambiguous definitions of data dictionary items which can be consumed and implemented downstream. The rigour of modelling helped not just the producers of the data dictionary, but the consumers of the data dictionary. The pilot has also facilitated the unexpected feedback loop into the standards body to help improve definitions, highlighting that standards bodies need to keep abreast of improvements in how these data dictionary items are now being modelled.  
Figure 5: Example of modelling pubertal status concepts.  
Figure 6: Image showing the CDISC mapping uniform resource locator (URL) and description. CDISC—Clinical Data Interchange Standards Consortium.