title: Same-Hospital Readmission Rates as a Measure of Pediatric Quality of Care.
abstract: OBJECTIVE
  Health care systems, payers, and hospitals use hospital readmission rates as a measure of quality. Although hospitals can track readmissions back to themselves (hospital A to hospital A), they lack information when their patients are readmitted to different hospitals (hospital A to hospital B). Because hospitals lack different-hospital readmission (DHR) data, they may underestimate all-hospital readmission (AHR) rates (hospital A to hospital A or B).
  
  
  OBJECTIVE
  To determine the prevalence of 30-day pediatric DHRs; to assess the effect of DHR on readmission performance; and to identify patient and hospital characteristics associated with DHR.
  
  
  METHODS
  We analyzed all-payer inpatient claims for 701,263 pediatric discharges (patients aged 0-17 years) from 177 acute care hospitals in New York State from January 1, 2005, through November 30, 2009, to identify 30-day same-hospital readmissions (SHRs), DHRs, and AHRs. Data analysis was performed from March 12, 2013, through April 6, 2015. We compared excess readmission ratios (calculated per the Medicare formula) using SHRs and AHRs to determine what might happen if the federal formula were applied to a specific state and to evaluate how often hospitals might accurately anticipate-using data available to them--whether they would incur penalties (excess readmission ratio >1) for readmissions. Using multivariate logistic regression, we identified patient- and hospital-level predictors of DHR vs SHR.
  
  
  METHODS
  The proportion of DHRs vs SHRs, AHR and SHR rates, and excess readmissions.
  
  
  RESULTS
  Different-hospital readmissions constituted 13.9% of 31,325 AHRs. At the individual hospital level, the median (interquartile range) percentage of DHRs was 21.6% (12.8%-39.1%). The median (interquartile range) adjusted AHR rate was 3.4% (3.0%-4.1%), 38.9% higher than the median adjusted SHR rate of 2.5% (2.0%-3.4%) (P < .001). Excess readmission ratios using SHRs inaccurately anticipated penalties (changed from >1 to ≤ 1 or vice versa) for 20 of the 177 hospitals (11.3%); all were nonchildren's hospitals and 18 of 20 (90.0%) were nonteaching hospitals. Characteristics associated with higher odds ratios (ORs) (reported with 95% CIs) of DHR in multivariate analyses included being younger (compared with age <1 year, ORs [95% CIs] for the other age categories ranged from 0.76 [0.66-0.88] to 0.85 [0.73-0.99]); being white (ORs [95% CIs] for nonwhite race/ethnicity ranged from 0.74 [0.65-0.84] to 0.88 [0.79-0.99]); having private insurance (1.14 [1.04-1.24]); having a chronic condition indicator for a mental disorder (1.33 [1.13-1.56]) or a disease of the nervous system (1.37 [1.20-1.57]) or circulatory system (1.20 [1.00-1.43]); and admission to a nonchildren's (1.62 [1.01-2.60]), urban (ORs for nonurban hospitals ranged from 0.35 [0.24-0.52] to 0.36 [0.21-0.64]), or lower-volume (0.73 [0.64-0.84]) hospital (P < .05 for each).
  
  
  CONCLUSIONS
  Different-hospital readmissions differentially affect hospitals' pediatric readmission rates and anticipated performance, making SHRs an incomplete surrogate for AHRs-particularly for certain hospital types. Failing to incorporate DHRs into readmission measurement may impede quality assessment, anticipation of penalties, and quality improvement.
authors.affiliation: Division of General Pediatrics, Boston Children's Hospital, Boston, Massachusetts2Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.
authors.forename: Alisa
authors.initials: A
authors.lastname: Khan
authors.affiliation: Division of General Pediatrics, Boston Children's Hospital, Boston, Massachusetts2Department of Pediatrics, Harvard Medical School, Boston, Massachusetts3Division of Infectious Diseases, Boston Children's Hospital, Boston, Massachusetts.
authors.forename: Mari M
authors.initials: MM
authors.lastname: Nakamura
authors.affiliation: Department of Healthcare Policy, Harvard Medical School, Boston, Massachusetts.
authors.forename: Alan M
authors.initials: AM
authors.lastname: Zaslavsky
authors.affiliation: Clinical Research Center, Boston Children's Hospital, Boston, Massachusetts.
authors.forename: Jisun
authors.initials: J
authors.lastname: Jang
authors.affiliation: Division of General Pediatrics, Boston Children's Hospital, Boston, Massachusetts2Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.
authors.forename: Jay G
authors.initials: JG
authors.lastname: Berry
authors.affiliation: currently a medical student at Harvard Medical School, Boston, Massachusetts.
authors.forename: Jeremy Y
authors.initials: JY
authors.lastname: Feng
authors.affiliation: Division of General Pediatrics, Boston Children's Hospital, Boston, Massachusetts2Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.
authors.forename: Mark A
authors.initials: MA
authors.lastname: Schuster
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D005260:Female; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D009518:New York / Q000453:epidemiology; D010359:Patient Readmission / Q000706:statistics & numerical data*; D010372:Pediatrics / Q000706:statistics & numerical data*; D015995:Prevalence; D019984:Quality Indicators, Health Care; D012307:Risk Factors