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.”
On occasion, your correspondent fights the northeast’s dreary weekend winter evenings with a dram of spirituous liquor like Macallan 12. Unlocked with a small splash of water and a single ice cube, a generous ounce of that pungent cinnamon leathery elixir turns the cold into cozy.
