title: Re-evaluation of re-hospitalization and rehabilitation in renal research.
abstract: The use of administrative data to capture 30-day readmission rates in end-stage renal disease is challenging since Medicare combines claims from acute care, inpatient rehabilitation (IRF), and long-term care hospital stays into a single "Inpatient" file. For data prior to 2012, the United States Renal Data System does not contain the variables necessary to easily identify different facility types, making it likely that prior studies have inaccurately estimated 30-day readmission rates.
  
  
  
  For this report, we developed two methods (a "simple method" and a "rehabilitation-adjusted method") to identify acute care, IRF, and long-term care hospital stays from United States Renal Data System claims data, and compared them to methods used in previously published reports.
  
  
  
  We found that prior methods overestimated 30-day readmission rates by up to 12.3% and overestimated average 30-day readmission costs by up to 11%. In contrast, the simple and rehabilitation-adjusted methods overestimated 30-day readmission rates by 0.1% and average 30-day readmission costs by 1.8%. The rehabilitation-adjusted method also accurately identified 96.8% of IRF stays.
  
  
  
  Prior research has likely provided inaccurate estimates of 30-day readmissions in patients undergoing dialysis. In the absence of data on specific facility types particularly when using data prior to 2012, future researchers could employ our method to more accurately characterize 30-day readmission rates and associated outcomes in patients with end-stage renal disease.
authors.affiliation: Division of Nephrology, Stanford University School of Medicine, Palo Alto, California, USA.
authors.forename: Eugene
authors.initials: E
authors.lastname: Lin
authors.affiliation: Division of Nephrology, Stanford University School of Medicine, Palo Alto, California, USA.|Geriatric Research and Education Clinical Center, Palo Alto VA Health Care System, Palo Alto, California, USA.
authors.forename: Manjula
authors.initials: M
authors.lastname: Kurella Tamura
authors.affiliation: Division of Nephrology, Stanford University School of Medicine, Palo Alto, California, USA.
authors.forename: Maria E
authors.initials: ME
authors.lastname: Montez-Rath
authors.affiliation: Division of Nephrology, Stanford University School of Medicine, Palo Alto, California, USA.
authors.forename: Glenn M
authors.initials: GM
authors.lastname: Chertow
mesh_terms: D015331:Cohort Studies; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007676:Kidney Failure, Chronic / Q000534:rehabilitation*; D010359:Patient Readmission / Q000706:statistics & numerical data*; D006435:Renal Dialysis / Q000379:methods*
keywords: Epidemiology; biostatistics; informatics; mathematical models; outcomes research