Length of stay differences in the uninsured is less than you think

There was a bit of excitement on Twitter recently with a number of tweets about a paper published in the Annals of Family Medicine which shows that uninsured patients are being released from  hospitals significantly sooner than insured patients. The numbers don’t lie.

From the abstract: “Across all hospital types, the mean length of stay … was significantly shorter for individuals without insurance (2.77 days) than for those with either private insurance (2.89 days, P=.04) or Medicaid (3.19, P<.01).”

These are statistically significant differences.

The authors conclude: “Future research should examine whether patients without insurance are being discharged prematurely.”

Let’s look a little closer at these numbers. The difference between the uninsured length of stay (2.77 days) and those with private insurance (2.89 days) is 0.12 days or to put it another way, 2.9 hours.

Do you really think that a difference in hospital length of stay of less than 3 hours is really clinically significant? I don’t.

Here’s another problem with the paper. Length of stay is what is called a “soft” endpoint. Having practiced surgery for 40 years, I can assure you that length of stay is very often not determined by the type of illness, treatment rendered, skill of the physician or any other parameter you can think of.

Here is what I mean. Just yesterday, a patient told me he could not go home on the day he had his laparoscopic cholecystectomy because his sister, whom he lives with, gets upset whenever he comes home from the hospital. He felt she needed another day to adjust. Patients have told me, “No one can come and pick me up today.” The care manager says, “The bed at the nursing home isn’t available today.”

Three weeks ago we couldn’t send some patients home because there was a massive power outage in our area. This list of excuses goes on and on.

I have written before about the problem of things being statistically significant but not clinically significant.

The paper is another example of statistical significance not corresponding to clinical significance.

“Skeptical Scalpel” is a surgeon blogs at his self-titled site, Skeptical Scalpel.

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  • Frank Lehman

    “The authors conclude: ‘Future research should examine whether patients without insurance are being discharged prematurely.’”   This seems to suggest that the authors made an assumption that patients without insurance are discharged prematurely.  Perhaps they should also examine whether patients with insurance are kept longer than medically necessary?  Might their assumption of the reason for the difference affect their future research?

    • Michal Haran

      I think this is a case in which you should be looking at relative differences and not absolute differences. Clearly 3 hours difference for an average stay for a given patient is of no practical importance, but a nearly 10% difference in length of stay for a large population translates into medical resources and hospital beds. 
      If you read the paper (and not only the abstract) you will see that this question (perhaps they should examine whether patients with insurance are kept longer? )was indeed addressed-”Our data indicate that in the United States, patients with less access to health care as defined by lack of insurance at admission have shorter lengths of stay, suggesting that either individuals without insurance are not receiving enough care or that individuals with insurance may be receiving more care than needed because it can be billed to the insurance company” .Further more, they did not only look at the average length of stay, but at many other parameters. “Uninsured patients have tended to have higher in-hospital mortality, which was supported in the current study for non-ACSC diagnoses. The increased mortality rate may be due to a higher initial severity of illness among uninsured individuals or differences in management, such as less use of procedural interventions or interdisciplinary care” They were also aware of the limitations of their study, and the need for further research addressing those issues. “There are several limitations to this study. First, we could not control for the quality of care delivered in the hospital. .. Second, it is unclear whether the shorter length of stay found among the uninsured patients represents poor quality of care. We do not have follow-up information on the patients to examine rehospitalizations or other outcomes after discharge. ” The major point of this study was summarized: “The problem of providing health insurance to the US population should continue to be a major policy concern. Clinicians should advocate for all patients to be treated equally no matter what type of health insurance or payment type is being provided for services. Uninsured patients have shorter lengths of stay, not only for hospitalizations that should be preventable but for other diagnoses as well. Further, uninsured individuals have an increased likelihood of in-hospital mortality. Addressing the problem of the uninsured with respect to hospital length of stay and in-hospital mortality needs to remain a priority”.

  • http://www.facebook.com/people/Terence-Ivfmd-Lee/1523282856 Terence Ivfmd Lee

    Let’s hope this doesn’t lead to some foolish decision to mandate that all hospitals need to have the average stays of insured and uninsured fall within a certain arbitrary percentage of each other. Although it would be intellectually amusing to observe the unintended human behaviors that follow from such a mandate, it would be sad as to the additional inefficiency it injects into the whole healthcare process, similar to the many already-existing examples where supposedly well-intentioned edicts, mandates and regulations led to inferior outcomes.

    For every law passed that seeks to improve short-term outcomes there are always indirect unintended sequelae, many of which make the situations ultimately worse in the long run.

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