When Will You Need This?

When you need to estimate the length of stay remaining, for entities that are preloaded.

Remaining Length of Stay Estimator model image

Model Object

The following model object can be found in the model objects directory: Time \ Remaining Length of Stay Estimator.

Ease of Use: Moderate

Ease of Modification: Moderate

How to Use the Model Object

1. Open Your Model

Open your model or create a new blank model.

2. Insert the Model Object into Your Model

1. Locate the model object Remaining Length of Stay Estimator and select the insert button.

2. Move the cursor to the point of insertion and left mouse-click. The upper left corner of the model object will be inserted at the location of the mouse-click.

3. Update Objects

1. Copy the logic from the action logic of the Ward 1.

copy logic from Remaining Length of Stay Estimator

2. Use this logic to replace the term a_Next_Time in the action logic of the “ward” in your model.

paste logic from Remaining Length of Stay Estimator

2.1. For each “ward” a new variable needs to be added, v_LocTime2, v_LocTime3, etc.

new variable for Remaining Length of Stay Estimator

2.2. Replace the v_LocTime1, in the ward, with the newly created variable.

  At the start of the model: 1. How many entities will be in a “ward” are of the hospital? 2. How much remaining LOS with a patient have. Both of the items above are needed to accurately predict the behavior of the system.

update var num in Remaining Length of Stay Estimator

4. Review Model

1. Run the model for an extended period. Several years so that a sufficient sample is collected.

2. From the output report, export the variable data for v_LocTime# to Excel, and then open the Excel file from the location it was saved in.

export var data in Remaining Length of Stay Estimator

3. Remove the first 2 months of data (Use the appropriate time for your the ward).

4. Analyze the Excel export to determine the “census” and “remaining LOS”

5. Use Stat::Fit to create a distribution for be beginning census and remaining LOS.

5.1. Copy the “values” left in the Excel file.

copy excel data in Remaining Length of Stay Estimator

5.2. Goto ProcessModel, open Stat::Fit (Tools \ Stat::Fit) and paste the copied data.

paste data in stat fit in Remaining Length of Stay Estimator

5.3. Click Autofit and then click OK on the new window.

fit data in Remaining Length of Stay Estimator

5.4. Click Export and then click OK to export the distribution to Windows clipboard.

export distribution in Remaining Length of Stay Estimator

6. Create a one time arrival (Periodic) into each ward using the distribution defining the beginning census as the “Quantity per Arrival.”

create one time arrival in Remaining Length of Stay Estimator

7. Set the attribute a_Next_Time = the distribution “Remaining LOS” (In the action logic of the arrival).

add action logic to arrival in Remaining Length of Stay Estimator

8. Remove pasted Estimator Model Object from your model.

This model object will not be part of your final model. It is designed to be inserted into a model temporarily to help discover the remaining length of stay and then be removed. The data collected from this MO will help to identify the distribution used as a remaining LOS for entities pre loaded to start the simulation.

5. Completion

The model object is now integrated into your model, you should now be able to save and then simulate the model.

Attributes, Variables, Scenario Parameters and Scenarios Usage

Attributes:

1. a_Next_Time: Do not change. Is the attribute used to store time values for the for entities. Initial value must be provided when entities are preloaded.

2. a_HoursRW: Do not change. Is used to store the hours remaining in the week. Nothing needs to be changed for the attribute.

Variables:

1. v_LocTime1: Do not change. Is used to store the remaining time value for the entities each weekend. A new variable will need to be defined for each “Ward” for which remaining LOS will be collected.

2. v_HoursRW: Do not change. Is used to calculate the hours remaining in the week. Nothing needs to be changed for the variable.