Health Care Costs and Utilization Predictions by the Skilled Nursing Facility Readmission Risk Instrument

Health care providers at hospitals and skilled nursing facilities (SNFs) are increasingly expected to optimize care of post-acute patients to reduce hospital readmissions and contain costs. To achieve these goals, providers need to understand their patients' risk of hospital readmission and how this risk is associated with health care costs. A previously developed risk prediction model identifies patients' probability of 30-day hospital readmission at the time of discharge to an SNF. With a computerized algorithm, we translated this model as the Skilled Nursing Facility Readmission Risk (SNFRR) instrument. Our objective was to evaluate the relationship between 30-day health care costs and hospital readmissions according to the level of risk calculated by this model.

This retrospective cohort study used SNFRR scores to evaluate patient data.

The patients were discharged from Mayo Clinic Rochester hospitals to 11 area SNFs.

We compared the outcomes of all-cause 30-day standardized direct medical costs and hospital readmissions between risk quartiles based on the distribution of SNFRR scores for patients discharged to SNFs for post-acute care from April 1 through November 30, 2017.

Mean 30-day all-cause standardized costs were positively associated with SNFRR score quartiles and ranged from $9199 in the fourth quartile (probability of readmission, 0.27-0.66) to $2679 in the first quartile (probability of readmission, 0.07-0.13) (P ≤ .05). Patients in the fourth SNFRR score quartile had 5.68 times the odds of 30-day hospital readmission compared with those in the first quartile.

The SNFRR instrument accurately predicted standardized direct health care costs for patients on discharge to an SNF and their risk for 30-day hospital readmission. Therefore, it could be used to help categorize patients for preemptive interventions. Further studies are needed to confirm its validity in other institutions and geographic areas.