BACKGROUND AND OBJECTIVES: Respiratory illnesses are the leading cause of pediatric hospitalizations in the United States, and a major focus of efforts to improve quality of care. Understanding factors associated with poor outcomes will allow better targeting of interventions for improving care. The objective of this study was to identify patient and hospital factors associated with prolonged length of stay (LOS) or complications during pediatric hospitalizations for asthma or lower respiratory infection (LRI).
METHODS: Cross-sectional study of hospitalizations of patients <18 years with asthma or LRI (bronchiolitis, influenza, or pneumonia) by using the nationally representative 2012 Kids Inpatient Database. We used multivariable logistic regression models to identify factors associated with prolonged LOS (>90th percentile) or complications (noninvasive ventilation, mechanical ventilation, or death).
RESULTS: For asthma hospitalizations(n = 85 320), risks for both prolonged LOS and complications were increased with each year of age (adjusted odds ratio [AOR] 1.06, 95% confidence interval [CI] 1.05–1.07; AOR 1.05, 95% CI 1.03–1.07, respectively for each outcome) and in children with chronic conditions (AOR 4.87, 95% CI 4.15–5.70; AOR 21.20, 95% CI 15.20–29.57, respectively). For LRI hospitalizations (n = 204 950), risks for prolonged LOS and complications were decreased with each year of age (AOR 0.98, 95% CI 0.97–0.98; AOR 0.95, 95% CI 0.94–0.96, respectively) and increased in children with chronic conditions (AOR 9.86, 95% CI 9.03–10.76; AOR 56.22, 95% CI 46.60–67.82, respectively). Risks for prolonged LOS for asthma were increased in large hospitals (AOR 1.67, 95% CI 1.32–2.11) and urban-teaching hospitals (AOR 1.62, 95% CI 1.33–1.97).
CONCLUSIONS: Older children with asthma, younger children with LRI, children with chronic conditions, and those hospitalized in large urban-teaching hospitals are more vulnerable to prolonged LOS and complications. Future research and policy efforts should evaluate and support interventions to improve outcomes for these high-risk groups (eg, hospital-based care coordination for children with chronic conditions).
Respiratory illnesses are the leading cause of pediatric hospitalizations in the United States, causing nearly 25% of hospitalizations.1 In 2006, there were ∼200 000 hospitalizations of children for pneumonia and asthma costing ∼$2 billion.2 Due to the tremendous burden of respiratory illnesses in children, they have been the main focus of national efforts to measure and improve quality of health care. In 2007, the Joint Commission implemented metrics to enable tracking of quality of care for children hospitalized with asthma,3 and more recently, the National Quality Forum developed a quality metric focused on readmissions of children after hospitalization for lower respiratory infections (LRIs), including bronchiolitis, pneumonia, and influenza.4 At the hospital level, many institutions have implemented interventions such as clinical pathways or practice guidelines to improve care for children hospitalized for respiratory illnesses.5–9 However, such interventions require substantial commitment of resources toward development, implementation, and maintenance.10 Ideally, interventions to improve care should be targeted toward high-risk patients or hospitals.
Our goal was to identify patient- and hospital-level factors associated with prolonged length of stay (LOS) or complications during pediatric hospitalizations for respiratory illnesses, by using a nationally representative sample. Previous analyses with similar aims have been limited to single hospitals.11,12 We hypothesized that patient-level characteristics (eg, race, insurance status) and hospital-level characteristics (eg, bed size, region) may affect LOS or complications in patients with asthma or LRIs. The information we gain from this national analysis can be used by physicians, hospital administrators, and policy makers to better target limited resources to improve outcomes for children hospitalized with these common conditions.
Data Source and Study Design
We performed a cross-sectional analysis of the most recent year of the Kids Inpatient Database (KID), 2012. KID is developed by the Agency for Healthcare Research and Quality; it is the only all-payer hospital administrative dataset designed to assess use of hospital services by children.13 KID includes a systematic random sample of pediatric discharges (age <21 years) from all hospitals in the 44 participating states (n = 4179). Discharge records contain de-identified, patient-level, clinical, and resource use data included in a typical discharge abstract.13 The database provides discharge weights to extrapolate from sampled discharges and produce national estimates of discharges from all US, community, nonrehabilitation hospitals. A detailed report on estimate and variance generation is found in the statistical report provided by the Healthcare Cost and Utilization Project.14
The analysis included all hospitalizations with a diagnosis of asthma or LRI as the primary diagnosis. Asthma was defined by using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes 493.0 to 493.92,15 and LRI was defined by using ICD-9-CM codes specified by the National Quality Forum metric (Appendix).4 Records without documented age were excluded.4 Hospitalizations with transfer as the admission source or discharge disposition were excluded because of inability to accurately determine LOS.15 Elective hospitalizations were excluded because of the possibility that these were for routine workup rather than acute treatment.2 The analysis of children with asthma excluded hospitalizations of children <2 years because of the potential for overlap between bronchiolitis and a true diagnosis of asthma in this age group.15
Comparisons of LOS and Rates of Complications
LOS and rates of complications were compared for each group, those with asthma and those with LRI. Complications included mechanical ventilation, noninvasive ventilation, or death; this outcome was created by using the Clinical Classifications Software code 216 for mechanical ventilation and ICD-9-CM procedure code 93.90 for noninvasive ventilation16 (ventilation without use of an artificial airway, such as positive-pressure ventilation with nasal/face mask).17 LOS and rates of complications were compared with respect to the patient-level characteristics age, gender, race, median household income quartile, patient’s residence (urban versus rural), payment source, and number of chronic medical conditions, as well as the hospital-level characteristics size, location and teaching status, hospital ownership, and geographic region. These variables were chosen based on previous studies showing potential associations.11,12,16,18–21 Discharge quarter was included to account for seasonal variation in respiratory hospitalizations.
Nearly 10% of values were missing for race, so these were labeled “Unknown” and collapsed with “Other,” so the records would not be excluded from our analysis.16 Continuous variables were categorized to allow univariate tests of comparison. Univariate tests for LOS were done by using simple linear regression. Univariate tests for rates of complications were done by using χ2 tests.
Predictors of Prolonged LOS and Complications
Prolonged LOS was defined as the 90th percentile of the LOS distribution for each condition (asthma = 3.3 days, LRI = 5 days).22 Multivariable logistic regression modeling was used to determine patient- and hospital-level characteristics associated with prolonged LOS or complications during hospitalization. Number of chronic conditions was included in the models to address confounding bias that may be caused by higher case-severity mix at certain types of hospitals. Chronic conditions were identified by using the Chronic Condition Indicator, developed by the Agency for Healthcare Research and Quality.23 This indicator categorizes all ICD-9-CM diagnosis codes as chronic or not chronic and categorizes the condition within a body system (eg, circulatory system). A chronic condition is defined as a condition that lasts >12 months and (1) places limitations on self-care, independent living, and social interactions; or (2) results in the need for ongoing intervention with medical products, services, and special equipment. Examples include malignancies, diabetes, asthma, and congenital anomalies. Chronic conditions were modeled in 4 categories and as a continuous variable (in a sensitivity analysis). All variables with P < .20 in univariate analysis were included in the model.24 Odds ratios with 95% confidence intervals (CIs) were determined for each predictor variable.
This study qualified for exempt status from the University of California, San Francisco, Committee on Human Research. All analyses were performed by using SAS 9.3 (SAS Institute, Inc, Cary, NC). Survey-weighted procedures were used for all descriptive statistics and regression models to account for the complex survey design.
Characteristics of pediatric hospitalizations for asthma and LRI are described in Table 1. There were 60 429 asthma hospitalizations and 144 569 LRI hospitalizations before survey-weighting. After survey-weights were applied, there were 85 320 asthma hospitalizations and 204 950 LRI hospitalizations. All remaining results represent survey-weighted analyses.
For asthma hospitalizations, mean age was 6.52 (SE 0.03) years, with 62% of hospitalizations for boys. Most hospitalizations were of children with 1 chronic condition (78%) in the respiratory disorder category, so most likely represents asthma. Most hospitalizations were of children from lower median household income quartiles (40% in Quartile 1, 23% in Quartile 2), living in urban settings (83%), with public insurance as the payment source (60%). Most hospitalizations occurred in large (63%), urban-teaching (72%), private nonprofit hospitals (74%).
LRI hospitalizations included those for bronchiolitis (50%), pneumonia (46%), and influenza (4%). For LRI hospitalizations, mean age was younger at 2.33 (SE 0.02) years, with 56% of hospitalizations for boys. Most hospitalizations were of children with no chronic conditions (58%), from lower median household income quartiles (37% in Quartile 1, 25% in Quartile 2), living in urban settings (73%), with public insurance as the payment source (61%). Most occurred in large (64%), urban-teaching (61%), private nonprofit hospitals (73%).
LOS for pediatric asthma and LRI are described in Table 2. For asthma hospitalizations, LOS was longer in the older age group compared with the youngest and in those with public insurance compared with private insurance. Hospitalizations of children with >4 chronic conditions were over double the length of those for children with 1 chronic condition. For LRI hospitalizations, LOS was longer in the older age group compared with the youngest group, in Hispanic children compared with white children, and in those with public insurance compared with private insurance. Hospitalizations of children with >4 chronic conditions were more than 3 times longer than those with no chronic conditions.
Comparisons of rates of complications for pediatric asthma and LRI are described in Table 3. For pediatric asthma hospitalizations, a total of 1595 (1.9%) of hospitalizations indicated a complication: all 1595 (1.9%) indicated use of mechanical ventilation, 1109 (1.3%) indicated use of both noninvasive and mechanical ventilation, and 17 (0.02%) indicated use of mechanical ventilation and the complication death. Complication rates were higher in hospitalizations of older children (P < .001); black, Hispanic, and Asian children compared with white children (P < .001); and >20 times higher in hospitalizations of children with >4 chronic conditions (22%) compared with those with 1 condition (1%, P < .001). For pediatric LRI hospitalizations, a total of 7327 (3.6%) of hospitalizations indicated a complication: all 7327 (3.6%) indicated use of mechanical ventilation, 2664 (1.3%) indicated use of both noninvasive and mechanical ventilation, and 164 (0.08%) indicated use of mechanical ventilation and the complication death. Complication rates were higher in the oldest group (P < .001) and in Asian and Hispanic children compared with white children (P < .001). The complication rate in children with >4 chronic conditions was 40%, >30 times higher than in children with no chronic conditions (1.2%, P < .001). Complication rates for both asthma and LRI were higher during hospitalizations in large (P < .001), urban-teaching hospitals (P < .001).
Final results from our multivariable model are described in Table 4. The model controlled for the patient factors of age, gender, race, place of residence, payment source, discharge quarter, income quartile, and number of chronic conditions, and the hospital factors of size, location and teaching status, geographic region, and control/ownership (government, private nonprofit, or private investor-owned hospital). Among hospitalizations of children for asthma (n = 82 619), odds of prolonged LOS (n = 9969) were increased with each year of age (adjusted odds ratio [AOR] 1.06, 95% CI 1.05–1.07). Hospitalizations of children with chronic medical conditions had significantly increased odds of prolonged LOS (AOR 4.87, 95% CI 4.15–5.70 for >4 conditions compared with 1 condition). Odds of prolonged LOS were higher in hospitalizations with public insurance compared with private insurance (AOR 1.13, 95% CI 1.06–1.21), in large hospitals (AOR 1.67, 95% CI 1.32–2.11]), and in urban-teaching hospitals compared with rural hospitals (AOR 1.62, 95% CI 1.33–1.97).
During hospitalizations for asthma, odds of complications (n = 1071) were also increased with each year of age (AOR 1.05, 95% CI 1.03–1.07). Odds of complications were increased during hospitalizations of black (AOR 1.35, 95% CI 1.11–1.66) or Asian (AOR 2.29, 95% CI 1.38–3.79) children compared with white children, and children with chronic medical conditions (AOR 21.20, 95% CI 15.20–29.57 for >4 conditions compared with 1 condition). Odds of complications were higher in hospitalizations with public insurance compared with private insurance (AOR 1.24, 95% CI 1.05–1.46), in large hospitals (AOR 1.67, 95% CI 1.03–2.73), and in urban-teaching hospitals compared with rural hospitals (AOR 4.07, 95% CI 2.25–7.36).
Among hospitalizations of children for LRI (n = 199 782), after our multivariable model controlled for chronic medical conditions, the relationship between LOS and age was reversed, and we found odds of prolonged LOS (n = 21 825) were decreased with each year of age (AOR 0.98, 95% CI 0.97–0.98). Odds were also decreased in hospitalizations of black children compared with white children (AOR 0.82, 95% CI 0.76–0.88). Hospitalizations of girls (AOR 1.13, 95% CI 1.10–1.17) and children with chronic medical conditions had significantly increased odds of prolonged LOS (AOR 9.86, 95% CI 9.03–10.76 for >4 conditions compared with no conditions). Odds of prolonged LOS were also higher in hospitalizations with public insurance compared with private insurance (AOR 1.14, 95% CI 1.09–1.19), in large hospitals (AOR 1.30, 95% CI 1.16–1.46), and in urban-teaching hospitals compared with rural hospitals (AOR 2.41, 95% CI 2.12–2.74).
After controlling for chronic conditions, the relationship between complications and age was also reversed, with odds of complications (n = 5071) decreased with each year of age (AOR 0.95, 95% CI 0.94–0.96). Odds of complications were increased in hospitalizations of girls (AOR 1.08, 95% CI 1.02–1.15), Asian children compared with white children (AOR 1.28, 95% CI 1.03–1.59), and in children with chronic medical conditions (AOR 56.22, 95% CI 46.60–68.82 for >4 conditions compared with no conditions). Odds of complications were higher in hospitalizations to large hospitals (AOR 1.42, 95% CI 1.11–1.83) and urban-teaching hospitals compared with rural hospitals (AOR 5.43, 95% CI 4.17–7.08).
Asthma and LRI represent the most significant burdens on child health in the inpatient setting.1 Our study sought to identify patient- and hospital-level factors associated with prolonged LOS and complications during these hospitalizations by using a nationally representative sample. During pediatric hospitalizations for asthma, we found risks were increased for older children and those with chronic conditions. During pediatric hospitalizations for LRI, we found risks were increased for younger children and those with chronic conditions. For both asthma and LRI, risks were higher in large, urban-teaching hospitals.
We found the risks of both prolonged LOS and complications were increased during asthma hospitalizations of older children. Odds of prolonged LOS increased 5% and complications increased 6% for every year of age, making the odds of these events up to 78% higher in adolescents. Previous studies examining risk factors for longer LOS11 and complications12 during pediatric asthma hospitalizations have not found older age to increase risks of these outcomes; however, these were small, single-center studies.
Adolescents with asthma are a vulnerable group at significant risk of experiencing complications because of underrecognition and denial of disease severity, poor medication adherence, and other risk-taking behaviors.25 These factors may lead to later, more severe presentations and consequent longer stays with higher risks of complications. During hospitalizations, providing quality disease management education may play a crucial role in improving disease control, thereby reducing risk of subsequent severe asthma exacerbations and complications.26 Efforts to improve outpatient medication adherence24 and transition to adult care providers27,28 are also important for improving outcomes in this challenging age group. The US Maternal and Child Health Bureau formed the Center for Health Care Transition to support research and policy efforts to improve transitions from pediatric to adult health care. Continued support of such efforts to improve transitions is crucial to improving health outcomes for adolescents with asthma.
We found the risks of both prolonged LOS and complications during LRI hospitalizations were increased in younger children. Odds of prolonged LOS decreased 2% and complications decreased 5% for every year of age, making the odds of these events up to 85% higher in infants. Pati et al18 also found risks of prolonged LOS were highest in the youngest children admitted for pneumonia. Possible reasons include more severe disease courses in younger children or greater variation in care of young children, such as in the use of pulse oximetry. Oxygen saturation has been implicated as the primary determinant of LOS during hospitalizations for bronchiolitis,29,30 and a study by Schroeder et al29 found that 1 in 4 patients incur unnecessarily prolonged hospitalization as a result of a perceived need for oxygen outside of other symptoms. Current guidelines on the management of bronchiolitis from the American Academy of Pediatrics suggest clinicians decrease utilization of continuous pulse oximetry as a means of decreasing unnecessarily prolonged hospitalization.31
We found a strong relationship between the presence of chronic medical conditions and increased risks of prolonged LOS or complications for both asthma and LRI hospitalizations. During asthma hospitalizations, children with >4 chronic conditions had nearly fivefold increased odds of prolonged LOS and >20-fold odds of complications. During LRI hospitalizations, children with >4 chronic conditions had nearly 10-fold increased odds of prolonged LOS and >50-fold odds of complications. Our findings support those of Simon et al,19 who found, from 1997 to 2006, children with complex chronic conditions were using an increasing proportion of inpatient care (26% of inpatient days in 2006) and had intensive inpatient resource use, with median LOS >3 times longer and risk of mortality 15 times higher than those with no chronic conditions. The Institute of Medicine has prioritized medical homes for improving health care for this vulnerable population.32 Better coordination of inpatient and outpatient care also has shown potential for improving outcomes in children with chronic conditions,32,33 and the Affordable Care Act’s support of developing Accountable Care Organizations may provide opportunities for better integration of inpatient and outpatient care. In the inpatient setting, hospital-based care coordination has been shown to decrease inpatient days and hospital costs.34 Given the rising proportion of children with chronic conditions cared for in hospital and these children’s substantially increased risk of poor outcomes, it is imperative that we better determine the effectiveness of interventions such as hospital-based care coordination and consider developing policies that incentivize hospitals to implement such programs.
We also found hospitalizations of children with public insurance had higher risks of prolonged LOS in both asthma and LRI and higher risks of complications in asthma. These findings are in line with several previous studies,12,18,35,36 and are likely due to multiple factors that may include worse disease severity on presentation.37 Additional research is necessary to understand whether there are differences in processes of care, quality of care, or other outcomes related to inpatient management for children with different insurance coverage.18
For both asthma and LRI, we found hospitalizations to large, urban-teaching hospitals had higher risk of prolonged LOS and complications. Similar associations have been found in analyses of children admitted for pneumonia,18 common pediatric conditions,21 and all-cause pediatric hospitalizations.36 Teaching hospitals have been shown to have longer LOS and higher costs even after adjustment for case severity and socioeconomic status (SES),21 as we have done in our analysis. One potential reason for this finding may be decreases in efficiency in teaching hospitals as a result of trainee supervision.18 Another reason may be limits in our ability to completely control for the higher proportion of children with complex conditions and low-SES in teaching hospitals.21 However, given that these types of hospitals are serving a disproportionately large share of medically complex and low-SES children, these hospitals should prioritize implementation of interventions shown to improve quality of care for children admitted with respiratory illness. Single-center studies have shown clinical pathways improve antimicrobial use38 and reduce radiation exposure, video-assisted thoracoscopic surgery procedures, and readmission rates in children admitted for pneumonia9; reduce resource utilization,39–41 LOS,41 and readmissions8 in children admitted for bronchiolitis; and increase home asthma management teaching7 and decrease in LOS5,42 in children admitted for asthma. Larger, multicenter studies are needed to determine if clinical pathways are an effective means of improving quality of care for respiratory illnesses, and if pathways are found to be effective, policies should incentivize large, urban-teaching hospitals to implement pathways.
There are several limitations to our analysis. First, KID contains discharge-level records rather than patient-level records, so a single child may be represented multiple times if readmitted to hospital over the study interval. Second, KID does not include detailed clinical variables, such as each child’s level of asthma severity and control; so, as with any observational study, our findings may be confounded by these factors. We adjusted for severity of case-mix by using number of chronic conditions, as specified in the National Quality Forum metric,4 but there may be residual confounding that effects our analysis of hospital-level risk factors for prolonged LOS and complications. In addition, LOS data do not account for time spent in the emergency department, so systematic variations in emergency department management that affect hospital LOS could bias our results; however, we do not suspect such systematic differences in emergency department care.
By using this nationally representative sample, we found older children with asthma, younger children with LRI, children with chronic medical conditions, and those admitted to large urban-teaching hospitals are more vulnerable to prolonged LOS and complications during hospitalizations. Further research efforts are needed to determine effective interventions to improve care for these high-risk groups and policy efforts are needed to help support implementation of effective interventions.
|ICD-9-CM Diagnosis Code||ICD-9-CM Diagnosis Code Description|
|46611||ACUTE BRONCHIOLITIS DUE TO RESPIRATORY SYNCYTIAL VIRUS (RSV)|
|46619||ACUTE BRONCIOLITIS DUE TO OTHER INFECTIOUS ORGANISMS|
|4801||VIRAL PNEUMONIA DUE TO RESPIRATORY SYNCYTIAL VIRUS|
|4870||INFLUENZA WITH PNEUMONIA|
|4871||INFLUENZA WITH OTHER RESPIRATORY MANIFESTATIONS|
|4878||INFLUENZA WITH OTHER MANIFESTATIONS|
|4881||INFLUENZA DUE TO IDENTIFIED NOVEL H1N1 INFLUENZA VIRUS|
|0310||PULMONARY INFECTION BY MYCOBACTERIUM AVIUM, INTRACELLULARE, KANSASII|
|0330||BORDETELLA PERTUSSIS [B. PERTUSSIS]|
|0331||BORDETELLA PARAPERTUSSIS [B. PARAPERTUSSIS]|
|0338||WHOOPING COUGH DUE TO OTHER SPECIFIED ORGANISM|
|0339||WHOOPING COUGH, UNSPECIFIED ORGANISM|
|0521||VARICELLA (HEMORRHAGIC) PNEUMONIA|
|0730||ORNITHOSIS WITH PNEUMONIA|
|0951||SYPHILIS OF LUNG|
|1140||PRIMARY COCCIDIOMYCOSIS (PULMONARY)|
|11505||HISTOPLASM CAPS PNEUMON (INFECTION BY HISTOPLASM CAPSULATUM, PNEUMONIA)|
|11515||HISTOPLASM DUB PNEUMONIA (INFECTION BY HISTOPLASM DUBOISII, PNEUMONIA)|
|11595||HISTOPLASMOSIS WITH PNEUMONIA|
|1304||PNEUMONITIS DUE TO TOXOPLASMOSIS|
|4800||VIRAL PNEUMONIA DUE TO ADENOVIRUS|
|4802||VIRAL PNEUMONIA DUE TO PARAINFLUENZA VIRUS|
|4803||VIRAL PNEUMONIA DUE TO SARS-ASSOCIATED CORONAVIRUS|
|4808||VIRAL PNEUMONIA DUE TO OTHER VIRUS NOT ELSEWHERE CLASSIFIED|
|4809||VIRAL PNEUMONIA, UNSPECIFIED|
|481||PNEUMOCOCCAL PNEUMONIA [NO 4TH OR 5TH DIGIT EXISTS IN THE ICD-9 SYSTEM FOR THIS CODE]|
|4820||PNEUMONIA DUE TO KLEBSIELLA PNEUMONIAE|
|4821||PNEUMONIA DUE TO PSEUDOMONAS|
|4822||PNEUMONIA DUE TO HAEMOPHILUS INFLUENZAE|
|4823×||PNEUMONIA DUE TO STREPTOCOCCUS|
|4824×||PNEUMONIA DUE TO STAPHYLOCOCCUS|
|4828×||PNEUMONIA DUE TO OTHER SPECIFIED BACTERIA|
|4829||BACTERIAL PNEUMONIA UNSPECIFIED|
|483×||PNEUMONIA DUE TO OTHER SPECIFIED ORGANISM|
|484×||PNEUMONIA IN INFECTIOUS DISEASES CLASSIFIED ELSEWHERE|
|485||BRONCHOPNEUMONIA [NO 4TH OR 5TH DIGIT EXISTS IN THE ICD-9 SYSTEM FOR THIS CODE]|
|486||PNEUMONIA, ORGANISM UNSPECIFIED [NO 4TH OR 5TH DIGIT EXISTS IN THE ICD-9 SYSTEM FOR THIS CODE]|
FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.
FUNDING: No external funding.
POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.
- adjusted odds ratio
- confidence interval
- International Classification of Diseases, Ninth Revision, Clinical Modification
- Kids Inpatient Database
- length of stay
- lower respiratory infection
- socioeconomic status
- ↵Agency for Healthcare Research and Quality. Hospital Stays for Children, 2009. 2011. Available at: www.hcup-us.ahrq.gov/reports/statbriefs/sb118.pdf. Accessed October 12, 2014
- ↵The Joint Commission. Children's Asthma Care. 2014. Available at: www.jointcommission.org/assets/1/6/CAC-Measures.pdf. Accessed October 20, 2014
- ↵National Quality Forum. #2414 Pediatric Lower Respiratory Infection Readmission Measure. 2014. Available at: www.qualityforum.org/QPS/2414. Accessed October 20, 2014
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- Copyright © 2015 by the American Academy of Pediatrics