## 2 Materials and Methods
### Metrics for the Evaluation of PROforma Models  
In this section, we describe the metrics we propose to assess quality aspects of CIGs modeled in PROforma related to their understandability and modifiability. Note that a high (respectively, low) metric value does not necessarily imply that the model is low (high) quality. Instead, given two equivalent models, the metric value could identify which model is the least understandable and therefore error-prone. Our starting point is the set of 15 metrics proposed by [PERSON] (2018) dealing with different aspects of the structure and the space state of a process model: size, coupling, cohesion, complexity, and modularity. The size aspect measures how big the process is or how many elements it has. Coupling deals with the number of interconnections among the different modules of the process model, the density of these interconnections, and how complex they are. Cohesion measures the relationship among the elements inside a module. Complexity deals with the simplicity of the process models, usually related to the number of control flows and the number of modules of the process. Finally, modularity measures to what extent a process can be separated into different parts or modules. These 15 metrics have been adapted to the BPMN language and validated by [PERSON] (2018). In order to reinterpret them in terms of PROforma, first we need to consider the main differences between both formalisms. Moreover, it is crucial to consider the specific types of knowledge typically contained in CPGs. Taking into account both aspects, we have reinterpreted the original metrics by [PERSON], and further we have defined new PROforma-specific ones, as we explain in this section. [PERSON] et al. (2018) considered the process model as a graph \(G=(N,A)\), where \(N\) is the set of nodes and \(A\) is the set of arcs connecting those nodes, \(A\subseteq N\times N\). We have also considered a PROforma model as a graph, where the tasks correspond to nodes and the scheduling constraints correspond to arcs. Clinical processes included in guidelines do not usually contain unstructured loops. Then, we have ruled out the possibility of arbitrary cycles in the process model graph. As a matter of fact, the PROforma editor warns about graph cycles. In BPMN there are different types of nodes: tasks, split connectors, and join connectors. In contrast, PROforma does not have connector nodes properly speaking. Instead, we have considered any task (node) with more than one incoming or more than one outgoing scheduling constraint (arc) as a connector node. Accordingly, if the number of outgoing arcs is greater than one, we talk about split connectors, and, if the number of incoming arcs is greater than one, they are join connectors. In BPMN, parallel, exclusive or inclusive split connectors are explicitly distinguished, regarding the behavior of the split node on the number of available paths taken (all, one or variable, respectively). However, in PROforma, we do not make any difference among split connectors regarding their behavior as it is not possible to determine it from the node. For example, if the connector node is a PROforma  
Figure 2: PROforma task “age between 5-15 decision”. decision task, its actual behavior (parallel, exclusive or inclusive) is determined not only by the result of the decision but also by the preconditions of the subsequent tasks. One of the distinctive features of PROforma is decision tasks. According to our experience, decisions tasks can be very complex, and therefore their use can have a negative impact in the understandability of the process model. For this reason, we have considered to define new metrics to study their impact in the quality of the model. PROforma is a hierarchical task network language, and therefore plans are also a key feature of the models. A plan is a task that acts as a container for other tasks, which are grouped together to achieve a particular goal. Although BPMN allows for subprocesses, the set of metrics by [PERSON] [11] does not consider this feature.