Introduction: Total joint replacement surgery has revolutionized the management of debilitating joint conditions, offering patients renewed mobility and relief from pain.

Objective: The main objective of the study is to find the preoperative prediction for risk factors of readmission after total joint replacement surgery.

Methodology of the study: This observational study was conducted at Medicare Cardiac and General Hospital from January 2021 to January 2023. A cohort of 80 patients who underwent total joint replacement surgery were included in the study. Patients were selected based on the availability of complete preoperative and postoperative data, ensuring a comprehensive dataset for analysis. Preoperative data, including demographic information, clinical characteristics, and surgical details, were meticulously collected from electronic medical records.

Results: Data were collected from 80 patients of joint replacement surgery. Mean age of the patients was 56.3±2.35 years and mean BMI was 29.1±1.89 kg/m². 38% shows diabetes and 46% shows hypertension alongside replacement therapy. 60% of the patients undergoes knee replacement therapy and 40% hip replacement therapy. Sensitivity and specificity were balanced, with values of 0.70 and 0.80, respectively, indicating the model's ability to correctly identify both positive and negative cases of readmission risk. Additionally, the model exhibited a Positive Predictive Value (PPV) of 0.65 and a Negative Predictive Value (NPV) of 0.85, reflecting its utility in predicting readmission outcomes.

Conclusion: It is concluded that developed preoperative prediction model offers a valuable tool for identifying patients at higher risk of readmission after total joint replacement surgery.