Is Comparing Hospitals by Readmission Rates Unfair? | Gabriel Perna | Healthcare Blogs Skip to content Skip to navigation

Is Comparing Hospitals by Readmission Rates Unfair?

October 12, 2012
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One of my daily routines as Healthcare Informatics’ go-to-news-guy (a nickname I’ve just given myself – even though I don’t like when people do that), is checking out the latest and greatest healthcare-related studies. We see a lot of them. Some are legitimate, some are not. Some bring up pretty basic points, while others bring up more controversial points.

One such study in the latter category, which surprisingly hasn’t gotten a lot of press, comes from our neighbors to the north. The study found in the CMAJ (Canadian Medical Association Journal), which can be read about here, declared that comparing hospital performance based on readmission rates and early death rates should require caution because those two indicators have significant variation in their values, depending on how they are calculated.

"Hospital-specific readmission rates have been reported as a quality of care indicator but no consensus exists on how these should be calculated. Our results highlight that caution is required when comparing hospital performance based on 30-day or urgent readmissions given their notable variation when methods used in their calculation change," stated Carl van Walraven, M.D., lead author of the study, senior scientist at Ottawa Hospital Research Institute (OHRI) and associate professor at the University of Ottawa (uOttawa).

Okay, I admit this conclusion isn’t that controversial.  It’s not like Dr. van Walraven and his colleagues suggested that we discount readmissions rates altogether. The authors simply said we should be leery when comparing hospitals over readmission rates, since the use of different methods and variables can result in different outcomes. The authors, by the way, looked at hospital-specific 30-day death or readmission rates for adults at all 162 Ontario hospitals between 2005 and 2010, with various methods for confounder adjustment (age-sex v. complete) and different units of analysis (all hospitalizations v. 1 per patient).

Considering that in United States there are serious penalties deriving from the mandatory Centers for Medicare & Medicaid Services (CMS) Readmissions Reduction program, not to mention the reputation blow that comes with a high rate, I don’t think the findings of this study are anything to balk at. Thanks to a fascinating Health Affairs blog I read this week, I know the American Hospitals Association (AHA) back in June expressed concern to CMS over not accounting for planned readmissions and patient disparities beyond a hospital’s control, when calculating a hospital’s readmission rate.

Furthermore, the OHRI study wasn’t the only research to suggest that calculated readmission rates may not be a fair indicator of a hospital’s performance. The same week the Canada-based study came out, researchers at the Loyola University Medical Center, revealed that they studied spine surgery patients to determine calculated readmission rates are a misleading indicator of hospital quality.

"We have identified potential pitfalls in the current calculation of readmission rates," Loyola University Medical Center neurosurgeon Beejal Amin, M.D., said in a statement. "We are working on modifying the algorithm to make it more clinically relevant."

Dr. Amin and his colleagues found that of the 5,780 spine surgery patients treated at the University of California San Francisco Medical Center between October, 2007 and June, 2011, 281 were readmitted within 30 days. However, the study’s authors say 69 of these readmissions (25 percent) should not have been counted against the hospital because many were planned, some were unrelated to spine surgery, and 14 were cancelled or rescheduled due to unpreventable reasons.

In general, I doubt many people would argue against working to lower readmission rates. And I commend the work by many of those in the healthcare industry, especially on the technical side, in creating information systems and analytics programs that will help in this work.  Still, the issues raised by these studies and the AHA deserve to be addressed and it should be interesting to see what might come out of this.

Would love to hear comments below from our readers on this topic!

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