# Question-Driven Methodology for Analyzing Emergency Room Processes Using Process Mining
## 2 Frequently-Posed Questions
It helps the classification of patients according to five different colors (red, orange, yellow, green and blue), regarding the severity of the episode and the immediate need of attention; red being the most severe cases and blue being the least [21]. Generally, this task is executed by a nurse. It involves gaining an understanding of the needs of the patient and assigning them a color in line with the severity of their condition, for example red for patients in a critical state. Questions relating to this type are those for which the expert requires information regarding certain types of cases, for example: What process is executed for patients who are triaged green? What are the key activities executed for specific diagnoses in which the majority of patients are triaged orange? The stay duration-oriented questions are based on the time in which the activities are executed for each case. The stay duration of a patient is the total time in which they are attended in the ER. This value might be denoted in units of time, for example two or four hours, or by means of categories according to a short stay (e.g., episodes of less than six hours) or a long stay (e.g., episodes longer than six hours). The duration values for the questions are established by the expert according to their questions. Examples of the questions include: What are the characteristics of episodes that last less than three hours? What is the process executed for attending to long-stay patients?The ER patient discharge-driven questions are based on the destination of the patient after leaving ER, e.g., if they are formally admitted to the hospital or discharged home. The options can vary according to the characteristics and circumstances of the medical center, for example the ER may not be located in the patient's preferred hospital, resulting in a request to be moved. In our analysis, the term 'inpatient' will be used to refer to a patient admitted to the hospital following a discharge from ER, whereas 'outpatient' will be used to refer to an ER patient who was sent home. Examples of questions include: What are the clinical characteristics and activities executed during the episodes in which patients are hospitalized? What process is followed for attending to patients that are discharged and sent home? In addition, compound questions can be detected from several characteristics of the episodes, combining triage, stay duration and patient discharge. For example: What activities are undertaken for patients who are triaged green, have a long stay in ER and whose final destination is to be admitted to the hospital? What characterizes the process followed by short-stay patients, who are triaged yellow or green, and sent home? What process is followed by long-stay patients who are triaged orange? Are there cases in which a patient who is triaged red is sent home? Furthermore, there are additional medical and demographic data that can be used to identify new categories of questions according to the analysis required in ER. For example, other categories may include different types of diagnoses, the resources involved, the physical infrastructure and the age and gender of the patients. In addition to conducting an analysis led by each of the categories separately, they can be combined to obtain more specific and in-depth results, according to the requirements of the frequently-posed question. For example, those that attempt to describe the process (process discovery) that relate to red or orange category episodes (triage-driven questions) or those that require verification regarding whether they comply with existing regulations or protocols (conformance checking) in long-stay episodes (stay duration oriented questions). As the level of specificity of the question increases, the required level of combination between the categories also increases in order to produce the correct answer. Understanding the frequently-posed questions and their categories can help to produce both a data extraction guide and a methodology for the application of data and process analysis.