Derivation and Validation of a Model to Predict 30-Day Readmission in Surgical Patients Discharged to Skilled Nursing Facility

Objectives: To identify factors associated with 30-day all-cause readmission rates in surgical patients discharged to skilled nursing facilities (SNFs), and derive and validate a risk score.

Design: Retrospective cohort.

Setting and participants: Patients admitted to 1 tertiary hospital's surgical services between January 1, 2011, and December 31, 2014 and subsequently discharged to 110 SNFs within a 25-mile radius of the hospital. The first 2 years were used for the derivation set and the last 2 for validation.

Methods: Data were collected on 30-day all cause readmissions, patient demographics, procedure and surgical service, comorbidities, laboratory tests, and prior health care utilization. Multivariate regression was used to identify risk factors for readmission.

Results: During the study period, 2405 surgical patients were discharged to 110 SNFs, and 519 (21.6%) of these patients experienced readmission within 30 days. In a multivariable regression model, hospital length of stay [odds ratio (OR) per day: 1.03, 95% confidence interval (CI) 1.02-1.04], number of hospitalizations in past year (OR 1.24 per hospitalization, 95% CI 1.18-1.31), nonelective surgery (OR 1.33, 95% CI 1.18-1.65), low-risk service (orthopedic/spine service) (OR 0.32, 95% CI 0.25-0.42), and intermediate-risk service (cardiothoracic surgery/urology/gynecology/ear, nose, throat) (OR 0.69, 95% CI 0.53-0.88) were associated with all-cause readmissions. The model had a C index of 0.71 in the validation set. Using the following risk score [0.8 × (hospital length of stay) + 7 × (number of hospitalizations in past year) +10 for nonelective surgery, +36 for high-risk surgery, and +20 for intermediate-risk surgery], a score of >40 identified patients at high risk of 30-day readmission (35.8% vs 12.6%, P < .001).

Conclusions/implications: Among surgical patients discharged to an SNF, a simple risk score with 4 parameters can accurately predict the risk of 30-day readmission.