Context Readmission rates are used as an indicator of the quality of care that patients receive during a hospital admission and after discharge. Objective To determine the prevalence of pediatric readmissions and the magnitude of variation in pediatric readmission rates across hospitals. Design, Setting, Patients We analyzed 568,845 admissions at 72 children's hospitals between 7/1/2009 and 6/30/2010 in the National Association of Children's Hospitals and Related Institutions Case Mix dataset. We estimated hierarchical regression models for 30-day readmission rates by hospital, accounting for age and chronic condition indicators. Hospitals with adjusted readmission rates that were one standard deviation above and below the mean were defined as having “high” and “low” rates, respectively. Main Outcome Measure Thirty-day unplanned readmissions following admission for any diagnosis and for the 10 admission diagnoses with the highest readmission prevalence. Planned readmissions were identified with ICD-9-CM procedure codes. Results The 30-day unadjusted readmission rate for all hospitalized children was 6.5% (n=36,734). Adjusted rates were 28.6% greater in hospitals with high vs. low readmission rates [7.2% (95% CI 7.1–7.2%) vs. 5.6% (95% CI 5.6-5.6%)]. For the 10 admissions diagnoses with the highest readmission prevalence, the adjusted rates were 17.0% to 66.0% greater in hospitals with high vs. low readmission rates. For example, sickle cell rates were 20.1% (95% CI 20.0–20.3%) vs. 12.7% (95% CI 12.6–12.8%) in high vs. low hospitals, respectively. Conclusions Among patients admitted to acute care pediatric hospitals, the rate of unplanned readmissions at 30 days was 6.5%. There was wide variability in readmission rates across conditions and hospitals.

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). OBJECTIVES 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. DESIGN, SETTING, AND PARTICIPANTS 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 anticipateusing 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. MAIN OUTCOMES AND MEASURES 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 Յ1 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 AND RELEVANCE Different-hospital readmissions differentially affect hospitals' pediatric readmission rates and anticipated performance, ...

IMPORTANCE Hospital readmissions contribute to higher expenditures and may sometimes reflect suboptimal patient care. Individuals discharged against medical advice (AMA) are a vulnerable patient population and may have higher risk for readmission. OBJECTIVES To determine odds of readmission and mortality for patients discharged AMA vs all others, to characterize patient and hospital-level factors associated with readmissions, and to quantify their overall cost burden. DESIGN, SETTING, AND PARTICIPANTS Nationally representative, all-payer cohort study using the 2014 National Readmissions Database. Eligible index admissions were nonobstetrical/newborn hospitalizations for patients 18 years and older discharged between January 2014 and November 2014. Admissions were excluded if there was a missing primary diagnosis, discharge disposition, length of stay, or if the patient died during that hospitalization. Data were analyzed between January 2018 and June 2018. EXPOSURES Discharge AMA and non-AMA discharge. MAIN OUTCOMES AND MEASURES Thirty-day all-cause readmission and in-hospital mortality rate. RESULTS There were 19.9 million weighted index admissions, of which 1.5% resulted in an AMA discharge. Within the AMA cohort, 85% were younger than 65 years, 63% were male, 55% had Medicaid or other (including uninsured) coverage, and 39% were in the lowest income quartile. Thirty-day all-cause readmission was 21.0% vs 11.9% for AMA vs non-AMA discharge (P < .001), and 30-day in-hospital mortality was 2.5% vs 5.6% (P < .001), respectively. Individuals discharged AMA were more likely to be readmitted to a different hospital compared with non-AMA patients (43.0% vs 23.9%; P < .001). Of all 30-day readmissions, 19.0% occurred within the first day after AMA discharge vs 6.1% for non-AMA patients (P < .001). On multivariable regression, AMA discharge was associated with a 2.01 (95% CI, 1.97-2.05) increased adjusted odds of readmission and a 0.80 (95% CI, 0.74-0.87) decreased adjusted odds of in-hospital mortality compared with non-AMA discharge. Nationwide readmissions after AMA discharge accounted for more than 400 000 inpatient hospitalization days at a total cost of $822 million in 2014. CONCLUSIONS AND RELEVANCE Individuals discharged AMA have higher odds of 30-day readmission at significant cost to the health care system and lower in-hospital mortality rates compared with non-AMA patients. Patients discharged AMA are also more likely to be readmitted to different hospitals and to have earlier bounce-back readmissions, which may reflect dissatisfaction with their initial episode of care.

The 30-day readmission rate was significantly higher after MH than non-MH admissions. Adjusted MH readmission rates varied substantially among hospitals, suggesting potential room for improvement.