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Modeling readmissions

The current intent to judge hospital performance and modify hospital payments based on relative rates of readmissions is not wise.  Contrary to President Obama’s characterization that readmitting a patient to the hospital is equivalent to bringing a car back to the mechanic after a repair, rates of readmissions are based on a number of factors, of which a significant portion are services not provided by the hospitals and environmental conditions not controlled by the hospitals.

But let’s put my objections aside and determine how we would model an “appropriate” rate of readmissions.  Well, a new article in JAMA* explores existing models, noting that robust models are needed “to identify which patients would benefit most from care transition interventions, as well as to risk-adjust readmission rates for the purposes of hospital comparison.”  The article concludes that the capability for doing these things does not yet exist.

In “Risk Prediction Models for Hospital Readmission,” the authors state as their objective:  “To summarize validated readmission risk prediction models, describe their performance, and assess suitability for clinical or administrative use.”  Their conclusion, after reviewing two dozen such models, was that “Most current readmission risk prediction models that were designed for either comparative or clinical purposes perform poorly.”

For the technically inclined among you, here’s more of the abstract:

Fourteen models that relied on retrospective administrative data could be potentially used to risk-adjust readmission rates for hospital comparison; of these, 9 were tested in large US populations and had poor discriminative ability (c statistic range: 0.55-0.65).

Although most models incorporated variables for medical comorbidity and use of prior medical services, few examined variables associated with overall health and function, illness severity, or social determinants of health.

So, even if the readmission rate is the right metric to use for comparison purposes, we don’t have a model that would accurately compare one hospital to the others.  This suggests that the time is not ripe to use this measure for financial incentives or penalties.  It might give the impression of precision, but it is not, in fact, analytically rigorous enough for regulatory purposes.

Paul Levy is the former President and CEO of Beth Israel Deconess Medical Center in Boston. For the past five years he blogged about his experiences in an online journal, Running a Hospital. He now writes as an advocate for patient-centered care, eliminating preventable harm, transparency of clinical outcomes, and front-line driven process improvement at Not Running a Hospital.

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