Model Developed to Predict Readmission Risk
Researchers at Brigham and Women's Hospital (BWH) have developed a new model that could help clinicians identify which patients are at the greatest risk for avoidable readmissions. The model, which is based on three years of research, relies on seven variables that the researchers say are the strongest indicator of a patient who is at risk for readmission.
The factors, which the researchers say are available at the patient’s bedside prior to discharge, are as follows:
- Hemoglobin level at discharge
- Sodium level at discharge
- Whether or not the patient is being discharged from an oncology service
- Whether or not non-surgical patients had a procedure during their hospital stay
- Whether or not the hospital admission was elective
- The number of times the patient has been admitted to the hospital during the last year
- The length of the patient's hospital stay
"The strength of this model is its simplicity," Jacques Donzé, M.D., MSc, a research associate in the Department of Medicine at BWH and co-creator of the model, said in a statement. "We have identified seven important variables that a physician can easily run through at a patient's bedside prior to discharge. If a patient is determined to be at high-risk for readmission, a return trip to the hospital could be prevented by providing additional interventions such as a home visit by a nurse or pharmacist consultation.
According to Jeffrey Schnipper, M.D., the director of clinical research for the BWH hospitalist service and a co-creator of the model, says identifying patients who at least have the potential to benefit from more intensive transitional interventions is the first step in reducing readmissions. The Centers for Medicare & Medicaid Services (CMS) have begun penalizing hospitals for high 30-day readmission rates.
