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Orthopaedic Proceedings
Vol. 94-B, Issue SUPP_XL | Pages 148 - 148
1 Sep 2012
Saucedo J Marecek G Huminiak L Stulberg SD Puri L
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Introduction

Readmission after Total Hip Arthroplasty (THA) or Total Knee Arthroplasty (TKA) places a great burden on the health care system. As reimbursement systems place increased emphasis on quality measures such as readmission rates, understanding the causes for readmission becomes increasingly important.

Methods

We queried an electronic database for all patients who underwent THA or TKA at our institution from 2006 through 2010. We identified those who had been readmitted within 90 days of discharge from the initial admission. We then collected clinical and demographic data as well as readmission diagnoses by ICD-9 code. We compared rates of readmission using chi-squared test.


Orthopaedic Proceedings
Vol. 94-B, Issue SUPP_XL | Pages 106 - 106
1 Sep 2012
Marecek G Saucedo J Stulberg SD Puri L
Full Access

Introduction

Readmission after Total Hip Arthroplasty (THA) or Total Knee Arthroplasty (TKA) places a great burden on the health care system. As reimbursement systems place increased emphasis on quality measures such as readmission rates, identifying and understanding the most common drivers for readmission becomes increasingly important.

Methods

We queried an electronic database for all patients who underwent THA or TKA at our institution from 2006 through 2010. We identified those who were readmitted within 90 days of discharge from the initial admission and set this as our outcome variable. We then reviewed demographic and clinical data such as age, index procedure, length of stay (LOS), readmission diagnosis, co-morbidities and payer group and set these as our variables of interest. We used chi-square tests to characterize and summarize the patient data and logistic regression analyses to predict the relative likelihood of patient readmission based on our control variables. Statistical significance was defined as p <0.05.