J Madison Hyer1, Diamantis I Tsilimigras1, Anghela Z Paredes1, Kota Sahara1, Susan White2, Timothy M Pawlik3. 1. Department of Surgery, The Ohio State University Wexner Medical Center, James Cancer Hospital and Solove Research Institute, 395 W. 12th Ave., Suite 670, Columbus, OH, USA. 2. Department of Financial Services, The Ohio State University Wexner Medical Center, James Cancer Hospital and Solove Research Institute, Columbus, OH, USA. 3. Department of Surgery, The Ohio State University Wexner Medical Center, James Cancer Hospital and Solove Research Institute, 395 W. 12th Ave., Suite 670, Columbus, OH, USA. tim.pawlik@osumc.edu.
Abstract
INTRODUCTION: Data on the association of high preoperative healthcare utilization and adverse clinical outcomes are scarce. We sought to evaluate the role of annual preoperative expenditure (APE) as a surrogate for latent variables of risk for adverse short-term postoperative outcomes. METHODS: Low and super-utilizers who underwent abdominal aortic aneurysm repair, coronary artery bypass graft, colectomy, total hip arthroplasty, total knee arthroplasty, or lung resection between 2013 and 2015 were identified from 100% Medicare Inpatient Standard Analytic Files. To assess the association between APE and postoperative outcomes, multivariable logistic regression was utilized. RESULTS: Among 1,049,160 patients, 788,488 (75.1%) and 21,700 (2.1%) patients were preoperative low- and super-utilizers, respectively. Median APE was more than 60 times higher among super-utilizers than low-utilizers ($57,160 vs. $932), as was the cost of the surgical episode ($21,141 vs. $13,179). The predictive ability of APE ranged from 0.683 (95% CI 0.678-0.687) for 90-day readmission to 0.882 (95% CI 0.879-0.886) for a complication at the index hospitalization. Among super-utilizers, the odds of a complication during the surgical episode was nearly double versus low-utilizers (OR = 1.96, 95% CI 1.89-2.04). Super-utilizers also had an increased odds of 30-day readmission (OR = 1.64, 95% CI 1.58-1.69) and mortality (OR = 2.22; 95% CI 2.04-2.42). CONCLUSION: APE was able to predict adverse postsurgical outcomes including complications during the surgical episode, readmission, and 90-day mortality. APE should be considered in the assessment of patient populations when defining risk of adverse postoperative events.
INTRODUCTION: Data on the association of high preoperative healthcare utilization and adverse clinical outcomes are scarce. We sought to evaluate the role of annual preoperative expenditure (APE) as a surrogate for latent variables of risk for adverse short-term postoperative outcomes. METHODS: Low and super-utilizers who underwent abdominal aortic aneurysm repair, coronary artery bypass graft, colectomy, total hip arthroplasty, total knee arthroplasty, or lung resection between 2013 and 2015 were identified from 100% Medicare Inpatient Standard Analytic Files. To assess the association between APE and postoperative outcomes, multivariable logistic regression was utilized. RESULTS: Among 1,049,160 patients, 788,488 (75.1%) and 21,700 (2.1%) patients were preoperative low- and super-utilizers, respectively. Median APE was more than 60 times higher among super-utilizers than low-utilizers ($57,160 vs. $932), as was the cost of the surgical episode ($21,141 vs. $13,179). The predictive ability of APE ranged from 0.683 (95% CI 0.678-0.687) for 90-day readmission to 0.882 (95% CI 0.879-0.886) for a complication at the index hospitalization. Among super-utilizers, the odds of a complication during the surgical episode was nearly double versus low-utilizers (OR = 1.96, 95% CI 1.89-2.04). Super-utilizers also had an increased odds of 30-day readmission (OR = 1.64, 95% CI 1.58-1.69) and mortality (OR = 2.22; 95% CI 2.04-2.42). CONCLUSION: APE was able to predict adverse postsurgical outcomes including complications during the surgical episode, readmission, and 90-day mortality. APE should be considered in the assessment of patient populations when defining risk of adverse postoperative events.
Authors: David C Miller; Cathryn Gust; Justin B Dimick; Nancy Birkmeyer; Jonathan Skinner; John D Birkmeyer Journal: Health Aff (Millwood) Date: 2011-11 Impact factor: 6.301
Authors: Gregory C Pope; John Kautter; Randall P Ellis; Arlene S Ash; John Z Ayanian; Lisa I Lezzoni; Melvin J Ingber; Jesse M Levy; John Robst Journal: Health Care Financ Rev Date: 2004