How to Calculate Length of Stay in Power BI

Tristan Keelan
Jan 7, 2021 12:37:15 AM


This tutorial demonstrates how you can use admission dates and discharge dates to calculate Length of Stay.  This is an important measure in all Health and Human Services programs, as it indicates how long clients are active in a program.

Good ways to use Length of Stay are to evaluate it against other categories for example, successful vs unsuccessful discharges.  Are there substantial differences in Length of Stay for what it takes to produce successful outcomes?  The answer to that question is a valuable one for understanding how long an episode of care will require to make the desired impact.  It is also valuable for Value Based Payment contracts to demonstrate that success can be achieved within a reasonable period of time, and therefore costs to insurance providers.

Target Length of Stay will vary substantially across program types; however, it is generally assumed that a shorter period is better, as long as you can also produce successful outcomes.  You may want to start by analyzing your average Length of Stay to help determine what a good target Length of Stay should be.

Another positive use for this calculation is to be able to filter out outliers.  When doing internal quality analysis, there may be times when extremely short or extremely long Length of Stays could be considered outliers.  For example, you might want to look at No Show Rate, but only for clients who have been in program for at least 90 days.

Formulas Used

Days Between Admit and Discharge = DATEDIFF('Chart Data - Sample'[Date - Admit].[Date],'Chart Data - Sample'[Date - Discharge].[Date],DAY)
*Reminder that formulas will have to use fields from your own data set. eg 'Your Table'[Your Field]

If you have any questions post them in the comments below.

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