"The fastest and most efficient way to add beds to a hospital isn’t to build a bigger hospital… it’s to reduce variation in length of stay.”
If we focus on knee replacements, which is our most common procedure (has the highest dot), we see the variation that exists among the surgeons. Let’s drill in.
(Did you know the American Academy of Orthopedic Surgeons (AAOS) uses analytics to present benchmarks for joint procedures? See the AJRR twitter feed for the latest.)
Notice the length of stay variation that exists among the surgeons. It’s clear one clinician is a significant outlier. Let’s remove this clinician from our analysis so that we can see the variation and opportunities across the pack.
The analytics now reveals the average length of stay for knee replacement is 5.37 days across all clinicians (excluding our one major outlier, whom we bookmarked for later investigation).
To understand the potential saving for each clinician if the length of stay came down to the average figure, you’ll need an engine capable of calculating the savings over a large data set quickly. We’re not talking ask IT to craft a report for us and wait weeks. You need answers immediately.
But don’t just take my word for it. Learn how the Children’s Hospital of Pittsburg (of UPMC) tackles clinical variation within Cerner. They’re presenting in the healthcare track of the Qlik Virtual Forum on March 30th.