We’ve gone about as far as we can go in theoretical terms with the process model. The next step is to create a training data set on which to do further experiments and get further insights about combining process and statistics.
Let’s define the variables and the dataset we will be using for this project.
1. Each encounter with the entire process (all sub-processes from start to finish) requires a unique identifier (UID). A single patient could go through the process more than once, so a UID is necessary. This can be as simple as taking their MRN and adding a four digit trailing number identifying how many times through the process.
2. For each sub-process, time is measured in minutes. Using start and stop times/dates has some added benefits but is more complex to carry out, as anyone who has ever done so will recognize (non-synced internal clocks providing erroneous time/date data, especially after power outages/surges).
3. The main times are the pathway times – Sunprocess 1-2, 2-3,3-4,4-5,5-6.
1-2 Reflects the time it takes the physician to order the study and patient transport to come for the patient.
2-3 Reflects transport time from the ED to CT holding.
3-4 Reflects time of nursing evaluation of the patient’s appropriateness for CT imaging.
4-5 Reflects the time bringing the patient into the imaging room and scanning, and sending the study to the PACS system.
5-6 Reflects the time for the radiologist to react to the study being available, interpret the study, and dictate a preliminary result in a format the ED physician can use.
4. When an interaction occurs along the inner lines we need to account for these in a realistic way. The boolean variable built into the process will take care of whether the interaction is present or not. The effect of the off-pathway interaction is to lengthen the time of the main pathway sub-processes. For example: Patient arrives in CT holding and nurse identifies a creatinine of 1.9 which needs further information for contrast imaging. She phones the ED doctor (4 min) and then phones the Radiologist to approve the study based upon that information (2 min). These phone calls are part of the overall time in subprocess 3-4 for this UID. To evaluate the time process 3-4 takes without these phone calls, simply subtract the two inner processes.
Or in other words, Process3-4(theoretical)=Process3-4(actual)-(Process1-3 + Process 3-5)
5. This table will represent potential times for each part of the process, chosen at random but with some basis in fact.
Process | Mean Time | Variability |
1-2 | 10 minutes | – 5 / +30 minutes |
2-3 | 15 minutes | – 5 / +10 minutes |
3-4 | 15 minutes | – 10 / + 15 minutes |
4-5 | 15 minutes | -5 / +30 minutes |
5-6 | 20 minutes | -10 /+40 minutes |
1-3 | 5 minutes | – 3 / +10 minutes |
1-4 | 5 minutes | – 3 / +10 minutes |
1-5 | 5 minutes | – 3 / + 10 minutes |
3-5 | 5 minutes | – 3/ + 10 minutes |
3-6 | 5 minutes | – 3/ + 10 minutes |
Next post, we’ll begin coding this in an R language data frame.
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