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The Bone & Joint Journal
Vol. 102-B, Issue 7 Supple B | Pages 62 - 70
1 Jul 2020
Tompkins G Neighorn C Li H Fleming K Lorish T Duwelius P Sypher K

Aims

High body mass index (BMI) is associated with increased rates of complications in primary total hip arthroplasty (THA), but less is known about its impact on cost. The effects of low BMI on outcomes and cost are less understood. This study evaluated the relationship between BMI, inpatient costs, complications, readmissions, and utilization of post-acute services.

Methods

A retrospective database analysis of 40,913 primary THAs performed between January 2013 and December 2017 in 29 hospitals was conducted. Operating time, length of stay (LOS), complication rate, 30-day readmission rate, inpatient cost, and utilization of post-acute services were measured and compared in relation to patient BMI.


Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_13 | Pages 22 - 22
1 Oct 2018
Springer B Huddleston J Odum S Froemke C Sariolghalam S Fleming K Sypher K Duwelius PJ
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Introduction

Bundle payment models have clinical and economic impacts on providers. Despite efforts made to improve care, experience has shown that a few episodes with costs well above a target (bundle busters) can reduce or negate positive performances. The purpose of this study was to identify both the primary episode drivers of cost and patient factors that led to episodes above target.

Methods

A retrospective study of 10,000 joint replacement episodes from a large healthcare system in CJR and a private orthopedic practice in BPCI was conducted. Episodes with costs greater than target price (TP) were designated as bundle busters and sub-divided into 4 groups:

< 1 standard deviation (SD) above TP (n=1700)

> 1 to 2 SD above TP (n=240)

> 2 to 3 SD above TP (n=70)

> 3 SD above TP (n=70)

Bundle busters were compared to the control that were at/below the TP (n= 7500). For the CJR/BPCI cohorts, one SD was defined as $10,700/$13,000, respectively.

Two linear regressions assessed the likelihood of factors predicting a bundle buster and the total episode cost. These variables included demographics, acuity classifications, comorbidities, length of stay, readmissions, discharge disposition, post-acute utilization, and episode costs.