Literature DB >> 30466961

Predicting Inpatient Status After Total Hip Arthroplasty in Medicare-Aged Patients.

Christian J Gronbeck1, Mark P Cote2, Mohamad J Halawi2.   

Abstract

BACKGROUND: The Centers for Medicare and Medicaid Services has solicited comments regarding the removal of total hip arthroplasty (THA) from its inpatient-only list. The goal of this study is to develop and internally validate a risk stratification nomogram to aid in the identification of optimal inpatient candidates in this patient population.
METHODS: The American College of Surgeons National Surgical Quality Improvement Program database was utilized to identify all patients >65 years of age who underwent primary THA between 2006 and 2015. Inpatient stay was the primary outcome measure, as defined by stay >2 days in length. The impact of numerous demographic, comorbid, and perioperative variables was assessed through a multivariable logistic regression analysis to construct a predictive nomogram.
RESULTS: In total, 30,587 inpatient THAs and 17,024 outpatient THAs were analyzed. Heart failure (odds ratio [OR] 2.11, P = .001), simultaneous bilateral THA (OR 2.47, P < .0001), age >80 years (OR 2.91, P < .0001), female gender (OR 1.90, P < .0001), and dependent functional status (OR 1.89, P < .0001) were the most influential determinants of inpatient status. The final prediction algorithm showed good accuracy, excellent calibration, and internal validation (bias-corrected concordance index of 0.69).
CONCLUSION: Our model enabled accurate and simple identification of the best candidates for inpatient admission after THA in Medicare-aged patients. Given the increasing feasibility of outpatient THA coupled with the likelihood of THA being removed from the Centers for Medicare and Medicaid Services inpatient-only list, this model provides a framework to guide discussion and decision-making for stakeholders.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Medicare; admission status; inpatient; outpatient; predictive nomogram; total hip arthroplasty

Mesh:

Year:  2018        PMID: 30466961     DOI: 10.1016/j.arth.2018.10.031

Source DB:  PubMed          Journal:  J Arthroplasty        ISSN: 0883-5403            Impact factor:   4.757


  5 in total

1.  Association between same day discharge total knee and total hip arthroplasty and risks of cardiac/pulmonary complications and readmission: a population-based observational study.

Authors:  Jiabin Liu; Nabil Elkassabany; Jashvant Poeran; Alejandro Gonzalez Della Valle; David H Kim; Daniel Maalouf; Stavros Memtsoudis
Journal:  BMJ Open       Date:  2019-12-08       Impact factor: 2.692

2.  Perioperative patient-specific factors-based nomograms predict short-term periprosthetic bone loss after total hip arthroplasty.

Authors:  Guangtao Fu; Mengyuan Li; Yunlian Xue; Qingtian Li; Zhantao Deng; Yuanchen Ma; Qiujian Zheng
Journal:  J Orthop Surg Res       Date:  2020-11-02       Impact factor: 2.359

3.  Impact of Intrathecal Fentanyl on Hospital Outcomes for Patients Undergoing Primary Total Hip Arthroplasty With Neuraxial Anesthesia.

Authors:  McKayla Kelly; Justin Turcotte; Jacob Aja; James MacDonald; Paul King
Journal:  Arthroplast Today       Date:  2021-04-14

4.  Predicting short stay total hip arthroplasty by use of the timed up and go-test.

Authors:  Ellen Oosting; Paul J C Kapitein; Suzan V de Vries; Ellen Breedveld
Journal:  BMC Musculoskelet Disord       Date:  2021-04-16       Impact factor: 2.362

5.  A Novel Machine Learning Predictive Tool Assessing Outpatient or Inpatient Designation for Medicare Patients Undergoing Total Hip Arthroplasty.

Authors:  David N Kugelman; Greg Teo; Shengnan Huang; Michael G Doran; Vivek Singh; William J Long
Journal:  Arthroplast Today       Date:  2021-04-13
  5 in total

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