Readmission Risk Assessment Tool (RRAT) for Decreasing 30-Day Readmission Rates in Total Joint Arthroplasty (TJA) and Predicting Readmission.

ABSTRACT

Background Total joint arthroplasty (TJA) has moved to a value-based care model that emphasizes increased quality and decreased costs. Preoperative patient selection and optimization significantly improve postoperative outcomes, improve quality, and decrease systemic costs. We introduced a readmission risk assessment tool (RRAT) previously verified in the literature at a large, private practice, multispecialty hospital to determine if implementation could improve outcomes and decrease our readmission rates. Methods All patients were administered the RRAT scoring tool prior to surgery. All staff was trained prior by a team consisting of multiple orthopedic surgeons, internal medicine and cardiac specialists, and anesthesiologists. If the score received by the patient was greater or equal to 4, a letter was sent immediately to the operative physician to work on optimization and a list of options for optimization was provided. No patients were expressly denied surgery. Results All 4912 patients from September 2017 to March 2020 were screened using the RRAT tool. A total of 228 patients had an RRAT score greater than 4 and required notification of the index surgeon. The overall readmission rate was 2.61% for all patients. We noted a readmission rate of 2.35% for those with a score of <4, 4.27% for those between 4-6, and 13.64% for those with a readmission rate >6. The odds ratio of those readmitted with an RRAT score >6 was 6.5488 (1.9080-22.4775, 95% CI). The American Society of Anesthesiologists (ASA) score and RRAT score were significantly correlated (Spearman Rho =0.324, P<0.001). Thirty-day readmission rates across the system decreased from 3.7% to 2.61% (p<0.05) when compared to the readmission rate in the year prior to the application of RRAT (September 2016 - August 2017). Conclusion The preoperative RRAT score is significantly correlated with 30-day readmission rates. Notification of the surgeon preoperatively of risk factors with modification options significantly lowered readmission rates in our study. Preoperative optimization leads to a decreased readmission rate and surgeon involvement is paramount to adherence.