Is there a Correlation between Length of Stay and Skilled Nursing Facility Discharge Rates for Joint Replacements?



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By: Jeffrey Maser  Oct. 13, 2017

One of the most common topics when discussing length of stay (LOS) metrics is the myriad of ways one can reduce LOS while other metrics such as Skilled Nursing Facility (SNF) discharge rates & readmittance rates are adversely impacted. Specifically, regarding SNF Discharge rates, there is a perception that there is a correlation between lower LOS metrics & higher SNF discharge rates.


Dexur studied if this perception could be reflected in the data.  Dexur analysts identified all discharges between July 2015 & June 2016 in the Medicare claims database and filtered only those discharges for DRG 470 - Joint Replacement for the purpose of this study. For background, DRG 470 is one of the main procedure groups for Comprehensive Care for Joint Replacement (CJR) that is part of the Bundled Payments initiative OF CMS. SNF discharge rates are closely tracked within the CJR & BPCI framework to ensure that quality outcomes are not being adversely impacted while economic metrics improve. Dexur analysts then filtered under the criteria of a minimum of 100 Medicare discharges in the 12 month period between July 2015 to June 2016 and were left with data on 1,506 hospitals.


While the work performed to gather the data for analysis was complex, the end result can be shown through a simple scatter plot (shown below) for the 1,506 Hospitals.


The above scatter plot shows a correlation of .52, which indicates that a higher LOS is very loosely associated with a SNF higher discharge rate.  These results should not assume an association between a higher LOS & more SNF discharges, but it certainly disproves the notion that lower LOS is associated with higher SNF discharge rates.

ABOUT THE AUTHOR

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Jeffrey Maser

Jeffrey Maser is an analyst. He truly loves working with numbers and enjoys the challenge of turning healthcare data into a resource that real patients can use to help make important decisions. Jeff's passion for data will serve him well in his quest to become the top mind in Fantasy Hockey. He previously worked at Truven Health Analytics, now a part of IBM Watson Health, and is a graduate of Brandeis University.