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.

4 replies »

  1. DRG’s started when it was realized that hospitals kept patients in house for many days after procedures/for care because they were paid based on the number of days of admission. These were the days when patients stayed for 7dys post-tonsillectomy.

    A group of actuaries came in and figured out what the median/appropriate number of days were for each diagnosis code. The idea being that this would prevent keeping people for longer LOS just to be paid more.

    So then we went to discharging people in, for example, 2.4dys because the hospital would only be paid for 2.4days of care so any greater length of stay was suddenly money out of the hospitals pocket. The problem? There were times when the patient could have benefited from staying longer but the hospital would have been financially penalized. So…they were discharged and eventually were readmitted.

    This was all fine (financially speaking) until now when we also get dinged for readmissions. So finally we are left with this – care has to be provided in an optimized fashion to be able to get someone out the door in the requisite 2.4 days, with enough followup delivered after discharge to prevent them from being readmitted within the 30dy window.

    The problem? The plank we now have to walk is incredibly narrow and the room for margin of error limited. Pre-existing conditions have to be captured perfectly to allow for correct risk adjustment and near perfect protocols and followup systems need to be in place to given optimal care. Unfortunately, there are so many pieces of this that no individual is accountable for, that the likelihood of getting it right is slim.

    In the meantime, the complaint from physicians (who are often the ones on whom this data is publicly attributed) is that the only way for them to manage this issue is to take care of less sick people. And this doesn’t accomplish the goal at all.

  2. I believe that a strong support structure for post discharge is part of the solution. I don’t think hospitals discharge patients too soon but rather there isn’t much emphasis placed on concurrent assessments on patients daily that provide data/indicators as to weather the patient is receiving the most appropriate level of care and if they are not meeting the criteria to be in the bed then why are they there? I would suggest that a patient flow solution that is clinical based and evidenced based could be part of the solution for effective flow and care of patients. This is also supplemented in finding out why there are delays in the care plan and rectifying the bottlenecks to make sure that the patient is not staying over the ELOS or being discharged inappropriately. Any thoughts? Are there any systems like this in the US?

  3. I have a feeling the best way to decrease re-admissions is to have better aftercare. The people who “bounce back” as we used to say in internship, can often be predicted by the nature of their diseases and lack of support structures outside the hospital. I have never met a doctor who intentionally discharges someone too early for financial reasons.

  4. Folks with longer LOS’s as a rule have greater CMI’s, often require more home care and services post discharge, and assuming they accept visits, may (through detection bias) return to ERs in higher numbers.

    The science still needs ripening and we are learning, but I suspect long LOS may be a recidivism marker. Next step is identifying right interventions for right patients. Not enough resources to provide blanket protection for all candidates.