Building Smarter Hospitals: The Widely Misunderstood Relationship Between Discharging Patients Too Early and the Likelihood of a 30 Day Readmission

When persons are admitted to a hospital, insurers’ payment rates are based on the diagnosis, not the number of days in the hospital (known as a “length of stay”).  As a result, once the admission is triggered, the hospital has important economic incentive to discharge the patient as quickly as possible. My physician colleagues used to refer to this as “treat, then street.”

Unfortunately, discharging patients too soon can result in readmissions.  That’s why I have agreed with others that diagnosis-based payment systems and a policy of “no pay” for readmissions were working at cross purposes. Unified bundled payment approaches like this seem to be a good start.

But that’s all theoretical.  What’s the science have to say?

Peter Kaboli and colleagues looked at the push-pull relationship between diagnosis-based payment incentives  and the likelihood of readmissions in a scientific paper just published in the Annals of Internal Medicine.

The authors used the U.S. Veterans Administration (VA) Hospital’s “Patient Treatment Files” to examine length of stay versus readmissions in 129 VA hospitals.  The sample consisted of over 4 million admissions and readmissions (defined as within 30 days and not involving another institution) from 1997 to 2010. The mean age started out at 63.8 years and increased to 65.5 years, while the proportion of persons aged 85 years or older increased from 2.5% to 8.8%. Over the years, admissions also grew more complicated with a higher rate of co-morbid conditions, such as diseases of the kidney (from 5% to 16%).

As length of stay went down, readmissions should have gone up, right?

The answer was yes and no.

Yes, if the data were trended over time: Over the 14 year period of observation, the number of days in the hospital (length of stay or LOS) decreased from 6.0 days to 4.3 days.  Yet, as LOS decreased, readmissions also decreased from 16.6% to 15.2%.

The decreases held up when the LOS was risk-adjusted for hospital and patient characteristics.  There was also no increase in mortality rates.

No, if hospitals were compared to each other:  Hospitals with risk-adjusted low lengths of stay had higher readmission rates compared to their average peers. In that group, each day of saved LOS was associated with a 6% increased rate of 30-day readmissions.

It gets even more complicated. As the LOS increased beyond the average, each additional day in the hospital was associated with a 3% increased rate of 30-day readmissions.

What should we learn from these data?  Keeping in mind that the VA is not necessarily generalizable to the typical community medical center.

1. Over 14 years of worth of VA data for 129 hospitals suggest it is possible to have your cake (a lower LOS) and eat it too (lower readmissions).  That’s the good news.

2. While overall performance improved over the years, between hospital comparisons showed there is a “U” shaped relationship between days in the hospital and the likelihood of readmission.  I agree with the authors: premature discharge before the patient is ready is associated with an 6% per day readmission rate, while patients who are very sick and have to stay a few extra days in the hospital are also at risk to the tune of 3% per day.  That’s the sobering news.

What are the implications?

Overzealous efforts to discharge patients can backfire with readmissions. It appears there’s an optimum length of stay that minimizes, but will never eliminate, readmissions.

Patients who do go home “too soon” or need extra days in the hospital appear to be at special risk.  Accountable care organizations and population health management service providers should use this information to target patients at special risk of “treat, street and … repeat.”

Jaan Sidorov, MD, is a primary care internist and former Medical Director at Geisinger Health Plan with over 20 years experience in primary care, disease management and population-based care coordination. He shares his knowledge and insights at Disease Management Care Blog, where this post first appeared.