Literature DB >> 29799349

Variation in payments for spine surgery episodes of care: implications for episode-based bundled payment.

Elyne N Kahn1,2, Chandy Ellimoottil1,3, James M Dupree1,3, Paul Park1,2, Andrew M Ryan1,4.   

Abstract

OBJECTIVE Spine surgery is expensive and marked by high variation across regions and providers. Bundled payments have potential to reduce unwarranted spending associated with spine surgery. This study is a cross-sectional analysis of commercial and Medicare claims data from January 2012 through March 2015 in the state of Michigan. The objective was to quantify variation in payments for spine surgery in adult patients, document sources of variation, and determine influence of patient-level, surgeon-level, and hospital-level factors. METHODS Hierarchical regression models were used to analyze contributions of patient-level covariates and influence of individual surgeons and hospitals. The primary outcome was price-standardized 90-day episode payments. Intraclass correlation coefficients-measures of variability accounted for by each level of a hierarchical model-were used to quantify sources of spending variation. RESULTS The authors analyzed 17,436 spine surgery episodes performed by 195 surgeons at 50 hospitals. Mean price-standardized 90-day episode payments in the highest spending quintile exceeded mean payments for episodes in the lowest cost quintile by $42,953 (p < 0.001). Facility payments for index admission and post-discharge payments were the greatest contributors to overall variation: 39.4% and 32.5%, respectively. After accounting for patient-level covariates, the remaining hospital-level and surgeon-level effects accounted for 2.0% (95% CI 1.1%-3.8%) and 4.0% (95% CI 2.9%-5.6%) of total variation, respectively. CONCLUSIONS Significant variation exists in total episode payments for spine surgery, driven mostly by variation in post-discharge and facility payments. Hospital and surgeon effects account for relatively little of the observed variation.

Entities:  

Keywords:  CMS = Centers for Medicare and Medicaid Services; DRG = diagnosis-related group; IQR = interquartile range; MVC = Michigan Value Collaborative; Medicare; bundled payments; episode-based payment; payment models; spine surgery costs

Mesh:

Year:  2018        PMID: 29799349     DOI: 10.3171/2017.12.SPINE17674

Source DB:  PubMed          Journal:  J Neurosurg Spine        ISSN: 1547-5646


  7 in total

1.  Reaching the medicare allowable threshold in adult spinal deformity surgery: multicenter cost analysis comparing actual direct hospital costs versus what the government will pay.

Authors:  Jeffrey L Gum; Breton Line; Leah Y Carreon; Richard A Hostin; Samrat Yeramaneni; Steven D Glassman; Douglas L Burton; Justin S Smith; Christopher I Shaffrey; Peter G Passias; Virginie Lafage; Christopher P Ames; R Shay Bess
Journal:  Spine Deform       Date:  2021-09-01

2.  Utilization of the American Society of Anesthesiologists (ASA) classification system in evaluating outcomes and costs following deformity spine procedures.

Authors:  Alexander J Schupper; William H Shuman; Rebecca B Baron; Sean N Neifert; Emily K Chapman; Jeffrey Gilligan; Jonathan S Gal; John M Caridi
Journal:  Spine Deform       Date:  2020-08-11

3.  The influence of sagittal spinopelvic alignment on patient discharge disposition following minimally invasive lumbar interbody fusion.

Authors:  Mohamed Macki; Hassan A Fadel; Travis Hamilton; Seokchun Lim; Lara W Massie; Hesham Mostafa Zakaria; Jacob Pawloski; Victor Chang
Journal:  J Spine Surg       Date:  2021-03

4.  Bundled Payment Models in Spine Surgery.

Authors:  Kevin Hines; Nikolaos Mouchtouris; Charles Getz; Glenn Gonzalez; Thiago Montenegro; Adam Leibold; James Harrop
Journal:  Global Spine J       Date:  2021-04

5.  Spine coding transition from ICD-9 to ICD-10: Not taking advantage of the specificity of a more granular system.

Authors:  Matthew J Sabatino; Patrick J Burroughs; Harold G Moore; Jonathan N Grauer
Journal:  N Am Spine Soc J       Date:  2020-10-31

6.  Translating Data Analytics Into Improved Spine Surgery Outcomes: A Roadmap for Biomedical Informatics Research in 2021.

Authors:  Jacob K Greenberg; Ayodamola Otun; Zoher Ghogawala; Po-Yin Yen; Camilo A Molina; David D Limbrick; Randi E Foraker; Michael P Kelly; Wilson Z Ray
Journal:  Global Spine J       Date:  2021-05-11

7.  Using machine learning methods to predict nonhome discharge after elective total shoulder arthroplasty.

Authors:  Cesar D Lopez; Michael Constant; Matthew J J Anderson; Jamie E Confino; John T Heffernan; Charles M Jobin
Journal:  JSES Int       Date:  2021-04-20
  7 in total

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