# A Goal-Driven Evaluation Method Based On Process Mining for Healthcare Processes
## 2 Background
### Process Mining  
PM is relatively young discipline used to exploit event data on information systems for (i) process discovery, (ii) conformance checking of process implementations according to the discovered/modeled process, and (iii) enhancement of process by detecting the differences in process implementations [8]. Event logs store detailed information on events concerning the source; i.e., the person or tool that started and performed the activity, the starting and finishing time of the activity, and the data element; e.g., type, size, and comments [8].  
Process discovery is the most important activity of PM since it provides a basis for further analyses involving the application of the remaining two types of PM; conformance checking and enhancement. In process discovery, event logs are used as an input, and a process model is set up without prior information [8]. When an actual process is created from event logs, many organizations can face challenges due to the differences in theory and implementation.  
In conformance checking, the process model and its flow discovered from the event logs are analyzed, and it is checked whether the process has been carried out as identified in the model [8]. Conformance checking measures the differences between the performed process and the process model specifications. The main aim of this activity is to identify the areas that need improvement using the information gained from the actual process [20].  
Process enhancement is the improvement of the process model based on event data. This can be undertaken by adding further data perspectives to the process model using event data, an activity also known as extension. Another type of enhancement is repair, in which the quality of the process model is improved using event data to define a new repaired model [19].  
Through process exploration techniques, a process model is discovered from event logs and is evaluated. This process may be repeated several times until a satisfying model is achieved. The activity model can also be refined manually or automatically to obtain better representations with process enhancement techniques after the automatic process exploration activity. It also allows checking the conformity between actual clinical processes and recommendations. In addition, variations of recommendations can be improved using interactive visualization techniques and user-defined levels of abstraction. Selecting suitable representation notation and providing a visualization environment are pre-requirements for defining recommendations.  
Various software products have PM capabilities [21]; e.g., ARIS Process Performance Manager (Software AG) [22], ProM (TU/e) [23], Disco (Fluxicon) [24], PALIA-ER [25], CELONIS [26], andpMineR [27]. Some of these products are still at the maturing stage since PM is a relatively young paradigm open to research and practice. For example, ProM [23] is a basic PM tool, which provides a standard environment incorporating a generic open-source framework for implementing PM techniques. Disco [24] is a popular, powerful, fast, and easy-to-use PM toolkit. The revolutionary commercial PM technology in Disco helps researchers to create visual maps from process data in minutes. In addition to these generic-purpose PM tools, pMineR introduced as an R library has been designed to perform PM specifically in the medical domain, and now supports two types of PM analysis; process discovery and conformance checking [27]. PALIA-ER is a web-based PM tool designed for question-driven PM analysis of the emergency room domain and includes only process discovery by using the algorithm PALIA [28].