Association of Hospital Discharge Against Medical Advice With Readmission and In-Hospital Mortality.

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.

Factors Associated With Family Experience in Pediatric Inpatient Care.

BACKGROUND: Hospitals are rapidly increasing efforts to improve the pediatric inpatient experience. However, hospitals often do not know what to target for improvement. To determine what matters most to families, we assessed which aspects of experience have the strongest relationships with parents' willingness to recommend a hospital. METHODS: Cross-sectional study of 17 727 surveys completed from November 2012 to January 2014 by parents of children hospitalized at 69 hospitals in 34 states using the Child Hospital Consumer Assessment of Healthcare Providers and Systems Survey. Hierarchical logistic regressions predicted the "top box" for willingness to recommend from measures of specific care dimensions (nurse-parent communication, doctor-parent communication, communication about medicines, keeping parents informed about the child's care, privacy with providers, preparing to leave the hospital, mistakes and concerns, child comfort, cleanliness, and quietness), adjusting for parent-child characteristics. Relative importance was assessed by using partially standardized adjusted odds ratios (aORs). RESULTS: Child comfort (aOR 1.50; 95% confidence interval 1.41-1.60) and nurse-parent communication (aOR 1.50; 95% confidence interval 1.42-1.58) showed the strongest relationships with willingness to recommend, followed by preparing to leave the hospital, doctor-parent communication, and keeping parents informed. Privacy and quietness were not significantly associated with willingness to recommend in multivariate analysis. CONCLUSIONS: Our study uncovered highly valued dimensions that are distinct to pediatric care. Hospitals that care for children should consider using dedicated pediatric instruments to measure and track their performance. Improvement efforts should focus on creating an age-appropriate environment, improving the effectiveness of provider interactions, and engaging parents to share their values and concerns.

Analysis of Readmissions Following Hospitalization for Cellulitis in the United States.

Importance: Cellulitis commonly results in hospitalization. Limited data on the proportion of cellulitis admissions associated with readmission are available. Objective: To characterize the US national readmission rate associated with hospitalization for treatment of cellulitis. Design, Setting, and Participants: This retrospective cohort analysis of cellulitis admissions from the nationally representative 2014 Nationwide Readmissions Database calculated readmission rates for all cellulitis admissions and subsets of admissions. The multicenter population-based cohort included adult patients admitted for conditions other than obstetrical or newborn care. Data were collected from January 1 through November 30, 2014, and analyzed from February 1 through September 18, 2018. Bivariate logistic regression models were used to assess differences in readmission rates by patient characteristics. Costs were calculated for all readmissions after discharge from hospitalization for cellulitis (hereinafter referred to as cellulitis discharge) and by readmission diagnosis. Exposures: Admission with a primary diagnosis of cellulitis. Main Outcomes and Measures: Proportion of cellulitis admissions associated with nonelective readmission within 30 days, characteristics of patients readmitted after cellulitis discharge, and costs associated with cellulitis readmission. Results: A total of 447 080 (95% CI, 429 927-464 233) index admissions with a primary diagnosis of cellulitis (53.8% male [95% CI, 53.5%-54.2%]; mean [SD] age, 56.1 [18.9] years) were included. Overall 30-day all-cause nonelective readmission rate after cellulitis discharge was 9.8% (95% CI, 9.6%-10.0%). Among patients with cellulitis, age (odds ratio for 45-64 years, 0.78; 95% CI, 0.75-0.81; P = .001) and insurance status (odds ratio for Medicare, 2.45; 95% CI, 2.33-2.58; P < .001) were associated with increased readmission rates. The most common diagnosis of readmissions included skin and subcutaneous tissue infections. The total cost associated with nonelective readmissions attributed to skin and subcutaneous infections within 30 days of a cellulitis discharge during the study period was $114.4 million (95% CI, $106.8-$122.0 million). Conclusions and Relevance: Readmission after hospitalization for cellulitis is common and costly and may be preventable with improved diagnostics, therapeutics, and discharge care coordination.

Adverse Events and Patient Outcomes Among Hospitalized Children Cared for by General Pediatricians vs Hospitalists.

Importance: Pediatric hospital medicine is a relatively new and growing specialty. However, research remains inconclusive on outcomes for inpatients cared for by pediatric hospitalists compared with those cared for by general pediatricians. Objective: To analyze outcomes, adverse events (AEs), and types of AEs associated with care provided for pediatric patients by hospitalists vs general pediatricians. Design, Setting, and Participants: This cross-sectional study used data from the medical records of a US urban academic children's hospital comprising 1423 hospitalizations between January 1, 2009, and August 31, 2015, for 57 diagnoses of patients cared for by either a hospitalist or general pediatrician. General pediatricians worked primarily in the hospital's outpatient clinic, serving a few inpatient weeks per year, and were not the patients' primary care physician. Data analysis was performed from July 1, 2017, to October 10, 2018. Main Outcomes and Measures: Outcomes were length of stay, total costs, 30-day readmission rates, and AEs. Adverse events were documented by International Classification of Diseases, Ninth Revision, Clinical Modification codes determined by review of medical records. Adverse event categories were drug events, infections, and device-related AEs. Generalized linear models were used to analyze patient outcomes, with standard errors clustered by physician. Models were adjusted for patient characteristics, including Chronic Condition Indicators. Models were estimated with and without adjustment for physician characteristics. Results: The data set contained 1423 hospitalizations among 726 female patients and 697 male patients (mean [SD] age, 6.1 [6.3] years). Hospitalists cared for 870 patients, and general pediatricians cared for 553 patients. Among the physicians, there were 57 women and 38 men; physicians were a mean (SD) 11.1 (8.1) years out of medical school. Patients cared for by general pediatricians were younger than those cared for by hospitalists (mean [SD] age, 5.4 [6.0] vs 6.5 [6.4] years; P = .001) but had similar mean (SD) Chronic Condition Indicator scores (1.5 [1.0] vs 1.5 [1.0]). A total of 33 of 56 general pediatricians (58.9%) and 24 of 39 hospitalists (61.5%) were women (P = .006), and general pediatricians were in practice twice as long as hospitalists on average (mean [SD], 16.0 [10.3] vs 7.9 [3.8] years out of medical school; P < .001). In multivariate models adjusting for patient-level features, there were no significant differences between general pediatricians and hospitalists for mean length of stay (4.7 vs 4.6 days), total costs ($14 490 vs $15 200), and estimated 30-day readmission rate (8.9% vs 6.4%), and results were similar with adjustments for physician characteristics. Device-related AEs were higher among hospitalists (3.0% vs 1.1%; odds ratio, 0.34; 95% CI, 0.12-1.00); this association became nonsignificant after adjusting for physician experience. Conclusions and Relevance: General pediatrician and hospitalist inpatient care had similar length of stay, total costs, and readmission rates. However, AEs differed between hospitalists and general pediatricians, with device-related AEs more common among hospitalists, which may be associated with hospitalists' fewer years in practice. Such findings can inform hospitals in planning their inpatient staffing and patient safety oversight.

Readmission After Pediatric Mental Health Admissions.

BACKGROUND AND OBJECTIVES: Reducing readmissions is a major health care system goal. There is a gap in our understanding of pediatric readmission patterns after mental health (MH) admissions. With this study, we aimed to characterize the prevalence of readmissions after MH admissions, to identify patient-level factors and costs associated with readmissions, and to assess variation in readmission rates across hospitals. METHODS: Using the 2014 Healthcare Cost and Utilization Project all-payer Nationwide Readmissions Database, we conducted a retrospective cohort analysis of 253 309 admissions for 5- to 17-year-olds at acute-care hospitals in 22 states. We calculated 30-day unplanned readmission rates, lengths of stay, and costs by primary admission diagnosis. We used hierarchical regression models to assess differences in readmission rates by patient characteristics, primary diagnoses, and comorbid chronic conditions, and to estimate the variation in case mix-adjusted rates across hospitals. RESULTS: MH stays accounted for 18.7% (n = 47 397) of index admissions. The 30-day readmission rate for MH admissions was higher than for non-MH admissions (8.0% vs 6.2%; P < .001). Children who were ≤14 years old, had non-MH chronic conditions, and/or had public insurance were more likely to be readmitted than their peers (P < .001 for each). Adjusted rates varied across hospitals (P < .001) and were 97.9% greater for hospitals 1 SD above versus below (11.2% vs 5.6%) the mean. Adjusted readmission rates, lengths of stay, and costs differed by diagnosis (P < .001). CONCLUSIONS: 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.

Same-Hospital Readmission Rates as a Measure of Pediatric Quality of Care.

IMPORTANCE: 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). 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 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. 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 ≤ 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 AND RELEVANCE: 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.

Changes in obesity between fifth and tenth grades: a longitudinal study in three metropolitan areas.

BACKGROUND: Despite epidemic childhood obesity levels, we know little about how BMI changes from preadolescence to adolescence and what factors influence changes. METHODS: We studied 3961 randomly selected public school students and 1 parent per student in 3 US metropolitan areas in fifth and again in tenth grades. In each grade, we measured child and parent height/weight and calculated BMI category. We examined whether baseline sociodemographic characteristics, child health-related factors, and parental obesity were significantly associated with exit from and entry into obesity from fifth to tenth grade. RESULTS: Fifth- and tenth-graders were 1%/2% underweight, 53%/60% normal weight, 19%/18% overweight, and 26%/20% obese, respectively. Among obese tenth-graders, 83% had been obese as fifth-graders and 13% had been overweight. Sixty-five percent of obese fifth-graders remained obese as tenth-graders, and 23% transitioned to overweight. Multivariately, obese fifth-graders who perceived themselves to be much heavier than ideal (P = .01) and those who had lower household education (P = .006) were less likely to exit obesity; by contrast, overweight fifth-graders were more likely to become obese if they had an obese parent (P < .001) or watched more television (P = .02). CONCLUSIONS: Obese fifth-graders face challenges in reducing obesity, especially when they lack advantages associated with higher socioeconomic status or when they have a negative body image. Clinicians and others should educate parents on the importance of preventing obesity very early in development. Children who are not yet obese by fifth grade but who have an obese parent or who watch considerable television might benefit from monitoring, as might children who have negative body images.

Pediatric readmission prevalence and variability across hospitals.

IMPORTANCE: 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, AND PATIENTS: We analyzed 568,845 admissions at 72 children's hospitals between July 1, 2009, and June 30, 2010, in the National Association of Children's Hospitals and Related Institutions Case Mix Comparative data set. 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 1 SD above and below the mean were defined as having "high" and "low" rates, respectively. MAIN OUTCOME MEASURES: 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 procedure codes from the International Classification of Diseases, Ninth Revision, Clinical Modification. 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 admission 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 AND RELEVANCE: Among patients admitted to acute care pediatric hospitals, the rate of unplanned readmissions at 30 days was 6.5%. There was significant variability in readmission rates across conditions and hospitals. These data may be useful for hospitals' quality improvement efforts.