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Objectives: To determine whether social determinants of health (SDH) risk adjustment changes hospital-level performance on the 30-day Pediatric All-Condition Readmission (PACR) measure and improves fit and accuracy of discharge-level models., Study Design: We performed a retrospective cohort study of all hospital discharges meeting criteria for the PACR from 47 hospitals in the Pediatric Health Information database from January to December 2014. We built four nested regression models by sequentially adding risk adjustment factors as follows: chronic condition indicators (CCIs); PACR patient factors (age and sex); electronic health record-derived SDH (race, ethnicity, payer), and zip code-linked SDH (families below poverty level, vacant housing units, adults without a high school diploma, single-parent households, median household income, unemployment rate). For each model, we measured the change in hospitals' readmission decile-rank and assessed model fit and accuracy., Results: For the 458 686 discharges meeting PACR inclusion criteria, in multivariable models, factors associated with higher discharge-level PACR measure included age <1 year, female sex, 1 of 17 CCIs, higher CCI count, Medicaid insurance, higher median household income, and higher percentage of single-parent households. Adjustment for SDH made small but significant improvements in fit and accuracy of discharge-level PACR models, with larger effect at the hospital level, changing decile-rank for 17 of 47 hospitals., Conclusions: We found that risk adjustment for SDH changed hospitals' readmissions rate rank order. Hospital-level changes in relative readmissions performance can have considerable financial implications; thus, for pay for performance measures calculated at the hospital level, and for research associated therewith, our findings support the inclusion of SDH variables in risk adjustment., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Study Objectives: Continuous positive airway pressure (CPAP) is effective in treating obstructive sleep apnea in children, but adherence to therapy is low. Our center created an intensive program that aimed to improve adherence. Our objective was to estimate the program's efficacy, cost, revenue and break-even point in a generalizable manner relative to a standard approach., Methods: The intensive program included device consignment, behavioral psychology counseling, and follow-up telephone calls. Economic modeling considered the costs, revenue and break-even point. Costs were derived from national salary reports and the Pediatric Health Information System. The 2015 Medicare reimbursement schedule provided revenue estimates., Results: Prior to the intensive CPAP program, only 67.6% of 244 patients initially prescribed CPAP appeared for follow-up visits and only 38.1% had titration polysomnograms. In contrast, 81.4% of 275 patients in the intensive program appeared for follow-up visits (p < .001) and 83.6% had titration polysomnograms (p < .001). Medicare reimbursement levels would be insufficient to cover the estimated costs of the intensive program; break-even points would need to be 1.29-2.08 times higher to cover the costs., Conclusions: An intensive CPAP program leads to substantially higher follow-up and CPAP titration rates, but costs are higher. While affordable at our institution due to the local payer mix and revenue, Medicare reimbursement levels would not cover estimated costs. This study highlights the need for enhanced funding for pediatric CPAP programs, due to the special needs of this population and the long-term health risks of suboptimally treated obstructive sleep apnea., (© Sleep Research Society 2016. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Background and Objective: Like their adult counterparts, pediatric hospitals are increasingly at risk for financial penalties based on readmissions. Limited information is available on how the composition of a hospital's patient population affects performance on this metric and hence affects reimbursement for hospitals providing pediatric care. We sought to determine whether applying different readmission metrics differentially affects hospital performance based on the characteristics of patients a hospital serves., Methods: We performed a cross-sectional analysis of 64 children's hospitals from the Children's Hospital Association Case Mix Comparative Database 2012 and 2013. We calculated 30-day observed-to-expected readmission ratios by using both all-cause (AC) and Potentially Preventable Readmissions (PPR) metrics. We examined the association between observed-to-expected rates and hospital characteristics by using multivariable linear regression., Results: We examined a total of 1 416 716 hospitalizations. The mean AC 30-day readmission rate was 11.3% (range 4.3%-19.6%); the mean PPR rate was 4.9% (range 2.9%-6.9%). The average 30-day AC observed-to-expected ratio was 0.96 (range 0.63-1.23), compared with 0.95 (range 0.65-1.23) for PPR; 59% of hospitals performed better than expected on both measures. Hospitals with higher volumes, lower percentages of infants, and higher percentage of patients with low income performed worse than expected on PPR., Conclusions: High-volume hospitals, those that serve fewer infants, and those with a high percentage of patients from low-income neighborhoods have higher than expected PPR rates and are at higher risk of reimbursement penalties., (Copyright © 2017 by the American Academy of Pediatrics.)

Importance: Medicaid payments tend to be less than the cost of care. Federal Disproportionate Share Hospital (DSH) payments help hospitals recover such uncompensated costs of Medicaid-insured and uninsured patients. The Patient Protection and Affordable Care Act reduces DSH payments in anticipation of fewer uninsured patients and therefore decreased uncompensated care. However, unlike adults, few hospitalized children are uninsured, while many have Medicaid coverage. Therefore, DSH payment reductions may expose extensive Medicaid financial losses for hospitals serving large absolute numbers of children., Objectives: To identify types of hospitals with the highest Medicaid losses from pediatric inpatient care and to estimate the proportion of losses recovered through DSH payments., Design, Setting, and Participants: This retrospective cross-sectional analysis evaluated Medicaid-insured hospital discharges of patients 20 years and younger from 23 states in the 2009 Kids' Inpatient Database. The dates of the analysis were March to September 2015. Hospitals were categorized as freestanding children's hospitals (FSCHs), children's hospitals within general hospitals, non-children's hospital teaching hospitals, and non-children's hospital nonteaching hospitals. Financial records of FSCHs in the data set were used to estimate the proportion of Medicaid losses recovered through DSH payments., Main Outcomes and Measures: Hospital financial losses from inpatient care of Medicaid-insured children (defined as the reimbursement minus the cost of care) were compared across hospital types. For our subsample of FSCHs, Medicaid-insured inpatient financial losses were calculated with and without each hospital's DSH payment., Results: The 2009 Kids' Inpatient Database study population included 1485 hospitals and 843 725 Medicaid-insured discharges. Freestanding children's hospitals had a higher median number of Medicaid-insured discharges (4082; interquartile range [IQR], 3524-5213) vs non-children's hospital teaching hospitals (674; IQR, 258-1414) and non-children's hospital nonteaching hospitals (161; IQR, 41-420). Freestanding children's hospitals had the largest median Medicaid losses from pediatric inpatient care (-$9 722 367; IQR, -$16 248 369 to -$2 137 902). Smaller losses were experienced by non-children's hospital teaching hospitals (-$204 100; IQR, -$1 014 100 to $14 700]) and non-children's hospital nonteaching hospitals (-$28 310; IQR, -$152 370 to $9040]). Disproportionate Share Hospital payments to FSCHs reduced their Medicaid losses by almost half., Conclusions and Relevance: Estimated financial losses from pediatric inpatients covered by Medicaid were much larger for FSCHs than for other hospital types. For children's hospitals, small anticipated increases in insured children are unlikely to offset the reductions in DSH payments.

Background: To develop the capacity for rapid-cycle improvement at the unit level, a large freestanding children's hospital designated 2 inpatient units with normal patient loads and workforce as pilot "Innovation Units" where frontline staff was trained to lead rigorous improvement portfolios., Methods: Frontline staff received improvement training, and interdisciplinary teams brainstormed ideas for tests of change. Ideas were prioritized using an impact-effort evaluation and an assessment of how they aligned with high-level goals. A template for each test summarized the following: the opportunity for improvement, the test being conducted, dates for the tests, driver diagrams, metrics to measure effects, baseline data, results, findings, and next steps. Successful interventions were implemented and disseminated to other units., Results: Multidisciplinary staff generated 150 improvement ideas and Innovation Units collectively ran >40 plan-do-study-act cycles. Of the 10 distinct improvement projects, elements of all 10 were deemed "successful" and fully implemented on the unit, and elements from 8 were spread to other units. More than 3 years later, elements of all of the successful improvements are still in practice in some form on the units, and each unit has tested >20 additional improvement ideas, using multiple plan-do-study-act cycles to refine them., Conclusions: The Innovation Unit model successfully engaged frontline staff in improvement work and established a sustainable system and framework for managing rigorous improvement portfolios at the unit level. Other hospitals and health care delivery settings may find our quality improvement approach helpful, especially because it is rooted in the microsystem of care delivery., (Copyright © 2016 by the American Academy of Pediatrics.)

Background: Previous studies attempting to distinguish preventable from nonpreventable readmissions reported challenges in completing reviews efficiently and consistently., Objectives: (1) Examine the efficiency and reliability of a Web-based fault tree tool designed to guide physicians through chart reviews to a determination about preventability. (2) Investigate root causes of general pediatrics readmissions and identify the percent that are preventable., Design/setting/patients: General pediatricians from The Children's Hospital of Philadelphia used a Web-based fault tree tool to classify root causes of all general pediatrics 15-day readmissions in 2014., Intervention/measurements: The tool guided reviewers through a logical progression of questions, which resulted in 1 of 18 root causes of readmission, 8 of which were considered potentially preventable. Twenty percent of cases were cross-checked to measure inter-rater reliability., Results: Of the 7252 discharges, 248 were readmitted, for an all-cause general pediatrics 15-day readmission rate of 3.4%. Of those readmissions, 15 (6.0%) were deemed potentially preventable, corresponding to 0.2% of total discharges. The most common cause of potentially preventable readmissions was premature discharge. For the 50 cross-checked cases, both reviews resulted in the same root cause for 44 (86%) of files (κ = 0.79; 95% confidence interval: 0.60-0.98). Completing 1 review using the tool took approximately 20 minutes., Conclusion: The Web-based fault tree tool helped physicians to identify root causes of hospital readmissions and classify them as either preventable or not preventable in an efficient and consistent way. It also confirmed that only a small percentage of general pediatrics 15-day readmissions are potentially preventable. Journal of Hospital Medicine 2016;11:329-335. © 2016 Society of Hospital Medicine., (© 2016 Society of Hospital Medicine.)

Importance: Performance-measure risk adjustment is of great interest to hospital stakeholders who face substantial financial penalties from readmissions pay-for-performance (P4P) measures. Despite evidence of the association between social determinants of health (SDH) and individual patient readmission risk, the effect of risk adjusting for SDH on readmissions P4P penalties to hospitals is not well understood., Objective: To determine whether risk adjustment for commonly available SDH measures affects the readmissions-based P4P penalty status of a national cohort of children's hospitals., Design, Setting, and Participants: Retrospective cohort study of 43 free-standing children's hospitals within the Pediatric Health Information System database in the calendar year 2013. We evaluated hospital discharges from 2013 that met criteria for 3M Health Information Systems' potentially preventable readmissions measure for calendar year 2013. The analysis was conducted from July 2015 to August 2015., Exposures: Two risk-adjustment models: a baseline model adjusted for severity of illness and an SDH-enhanced model that adjusted for severity of illness and the following 4 SDH variables: race, ethnicity, payer, and median household income for the patient's home zip code., Main Outcomes and Measures: Change in a hospital's potentially preventable readmissions penalty status (ie, change in whether a hospital exceeded the penalty threshold) using an observed-to-expected potentially preventable readmissions ratio of 1.0 as a penalty threshold., Results: For the 179,400 hospital discharges from the 43 hospitals meeting inclusion criteria, median (interquartile range [IQR]) hospital-level percentages for the SDH variables were 39.2% nonwhite (n = 71,300; IQR, 28.6%-54.6%), 17.9% Hispanic (n = 32,060; IQR, 6.7%-37.0%), and 58.7% publicly insured (n = 106,116; IQR, 50.4%-67.8%). The hospital median household income for the patient's home zip code was $ 40,674 (IQR, $ 35,912-$ 46,190). When compared with the baseline model, adjustment for SDH resulted in a change in penalty status for 3 hospitals within the 15-day window (2 were no longer above the penalty threshold and 1 was newly penalized) and 5 hospitals within the 30-day window (3 were no longer above the penalty threshold and 2 were newly penalized)., Conclusions and Relevance: Risk adjustment for SDH changed hospitals' penalty status on a readmissions-based P4P measure. Without adjusting P4P measures for SDH, hospitals may receive penalties partially related to patient SDH factors beyond the quality of hospital care.

Objective: There is growing consensus that to ensure that health care dollars are spent efficiently, physicians need more training in how to provide high-value, cost-conscious care. Thus, in fiscal year 2014, The Children's Hospital of Philadelphia piloted a 9-part curriculum on health care costs and value for faculty in the Division of General Pediatrics. This study uses baseline and postintervention surveys to gauge knowledge, perceptions, and views on these issues and to assess the efficacy of the pilot curriculum., Methods: Faculty completed surveys about their knowledge and perceptions about health care costs and value and their views on the role physicians should play in containing costs and promoting value. Baseline and postintervention responses were compared and analyzed on the basis of how many of the sessions respondents attended., Results: Sixty-two faculty members completed the baseline survey (71% response rate), and 45 faculty members completed the postintervention survey (63% response rate). Reported knowledge of health care costs and value increased significantly in the postintervention survey (P=.04 and P<.001). Odds of being knowledgeable about costs and value were 2.42 (confidence interval: 1.05-5.58) and 6.22 times greater (confidence interval: 2.29-16.90), respectively, postintervention. Reported knowledge of health care costs and value increased with number of sessions attended (P=.01 and P<.001)., Conclusions: The pilot curriculum appeared to successfully introduce physicians to concepts around health care costs and value and initiated important discussions about the role physicians can play in containing costs and promoting value. Additional education, increased cost transparency, and more decision support tools are needed to help physicians translate knowledge into practice., (Copyright © 2016 by the American Academy of Pediatrics.)

Objective: To determine if household income is associated with hospitalization costs for severe traumatic brain injury (TBI) and spinal cord injury (SCI)., Study Design: Retrospective cohort study of inpatient, nonrehabilitation hospitalizations at 43 freestanding children's hospitals for patients <19 years old with unintentional severe TBI and SCI from 2009-2012. Standardized cost of care for hospitalizations was modeled using mixed-effects methods, adjusting for age, sex, race/ethnicity, primary payer, presence of chronic medical condition, mechanism of injury, injury severity, distance from residence to hospital, and trauma center level. Main exposure was zip code level median annual household income., Results: There were 1061 patients that met inclusion criteria, 833 with TBI only, 227 with SCI only, and 1 with TBI and SCI. Compared with those with the lowest-income zip codes, patients from the highest-income zip codes were more likely to be older, white (76.7% vs 50.4%), have private insurance (68.9% vs 27.9%), and live closer to the hospital (median distance 26.7 miles vs 81.2 miles). In adjusted models, there was no significant association between zip code level household income and hospitalization costs., Conclusions: Children hospitalized with unintentional, severe TBI and SCI showed no difference in standardized hospital costs relative to a patient's home zip code level median annual household income. The association between household income and hospitalization costs may vary by primary diagnosis., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Objective: Observation unit (OU) use has been promoted recently to decrease resource utilization and costs for select patients, but little is known about the operations of pediatric OUs. This study aimed to characterize the infrastructure and function of OUs within freestanding children's hospitals and to compare characteristics between hospitals with and without OUs., Methods: All 43 freestanding children's hospitals that submit data to the Pediatric Health Information System were contacted in 2013 to identify OUs that admitted unscheduled patients from their emergency department (ED) in 2011. Semistructured interviews were conducted with representatives at hospitals with these OUs. Characteristics of hospitals with and without OUs were compared., Results: Fourteen (33%) of 43 hospitals had an OU during 2011. Hospitals with OUs had more beds and more annual ED visits compared to those without OUs. Most OUs (65%) were located in the ED and had <12 beds (65%). Staffing models and patient populations differed between OUs. Nearly 60% were hybrid OUs, providing scheduled services. OUs lacked uniform outcome measures. Themes included: admissions were intuition based, certain patients were not well suited for OUs, OUs had rapid-turnover cultures, and the designation of observation status was arbitrary. Challenges included patient discontent with copayments and payer-driven utilization reviews., Conclusions: OUs were located in higher volume hospitals and varied by location, size, and staffing. Most functioned as hybrid OUs. OUs based admissions on intuition, had staffing cultures centered on rapid turnover of patient care, lacked consistent outcome measures, and faced challenges regarding utilization review and patient copayments., (Copyright © 2015 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)

Background: Many studies have demonstrated a rise in computed tomography (CT) utilization in abstract children's hospitals. However, CT utilization may be declining, perhaps due to awareness of potential hazards of pediatric ionizing radiation, such as increased risk of malignancy. Th e objective is to assess the trend in CT utilization in hospitalized children at freestanding children's hospitals from 2004 to 2012 and we hypothesize decreases are associated with shifts to alternate imaging modalities., Methods: Multicenter cross-sectional study of children admitted to 33 pediatric tertiary-care hospitals participating in the Pediatric Health Information System between January 1, 2004, and December 31, 2012. The rates of CT, ultrasound, and MRI for the top 10 All-Patient Refined Diagnosis Related Groups (APR-DRGs) for which CT was performed in 2004 were determined by billing data. Rates of each imaging modality for those top 10 APR-DRGs were followed through the study period. Odds ratios of imaging were adjusted for demographics and illness severity., Results: For all included APR-DRGs except ventricular shunt procedures and nonbacterial gastroenteritis, the number of children imaged with any modality increased. CT utilization decreased for all APR-DRGs (P values , .001). For each of the APR-DRGs except seizure and infections of upper respiratory tract, the decrease in CT was associated with a significant rise in an alternative imaging modality (P values # .005)., Conclusions: For the 10 most common APR-DRGs for which children received CT in 2004,a decrease in CT utilization was found in 2012. Alternative imaging modalities for 8 of the diagnoses were used.

Objective: In preparation for the development of a curriculum on health care costs and value for pediatricians, the goal of this study was to assess pediatricians' baseline perceptions about the concepts of "cost" and "value" in health care, and topics that should be included in a curriculum that teaches about costs and value in pediatrics., Methods: Physicians in the Department of Pediatrics at The Children's Hospital of Philadelphia received an online freelisting survey asking them to generate lists of words that come to mind when thinking about "costs" in health care, "value" in health care, and topics to include in a curriculum on costs and value in pediatrics. AnthroPac software generated salience scores, indicating the relative importance of each term., Results: A total of 207 surveys were completed for a 40% response rate. For the "cost" prompt, the most salient responses were "excessive," "waste," and "insurance." For the "value" prompt, the most salient responses were "outcomes" and "quality." For elements to include in a curriculum, the most salient responses were "insurance" and "costs." Analyzing responses based on years in practice, percentage clinical time, and division resulted in slightly different lists and salience scores., Conclusions: In this freelisting exercise, there was general agreement that health care costs are "excessive," that "outcomes" and "quality" are integral to value, and that there is a need for education in these areas, especially around "insurance." Differences based on years in practice, percentage clinical time, or division can inform the development of targeted curricula that consider the needs, knowledge, and interests of these groups., (Copyright © 2015 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)

Background: Pediatric observation units (OUs) have demonstrated reductions in lengths of stay (LOS) and costs of care. Hospital-level outcomes across all observation-status stays have not been evaluated in relation to the presence of a dedicated OU in the hospital., Objective: To compare observation-status stay outcomes in hospitals with and without a dedicated OU., Design: Cross-sectional analysis of hospital administrative data., Methods: Observation-status stay outcomes were compared in hospitals with and without a dedicated OU across 4 categories: (1) LOS, (2) standardized costs, (3) conversion to inpatient status, and (4) return care., Setting/patients: Observation-status stays in 31 free-standing children's hospitals contributing observation patient data to the Pediatric Health Information System database, 2011., Results: Fifty-one percent of the 136,239 observation-status stays in 2011 occurred in 14 hospitals with a dedicated OU; the remainder were in 17 hospitals without. The percentage of observation-status same-day discharges was higher in hospitals with a dedicated OU compared with hospitals without (23.8 vs 22.1, P < 0.001), but risk-adjusted LOS in hours and total standardized costs were similar. Conversion to inpatient status was higher in hospitals with a dedicated OU (11.06%) compared with hospitals without (9.63%, P < 0.01). Adjusted odds of return visits and readmissions were comparable., Conclusions: The presence of a dedicated OU appears to have an influence on same-day and morning discharges across all observation-status stays without impacting other hospital-level outcomes. Inclusion of location of care (eg, dedicated OU, inpatient unit, emergency department) in hospital administrative datasets would allow for more meaningful comparisons of models of hospital care., (© 2015 Society of Hospital Medicine.)

Objective: To assess readmission rates identified by 3M-Potentially Preventable Readmissions software (3M-PPRs) in a national cohort of children's hospitals., Study Design: A total of 1 719 617 hospitalizations for 1 531 828 unique patients in 58 children's hospitals from 2009 to 2011 from the Children's Hospital Association Case-Mix Comparative database were examined. Main outcome measures included rates, diagnoses, and costs of potentially preventable readmissions (PPRs) and all-cause readmissions., Results: The 7-, 15-, and 30-day rates by 3M-PPRs were 2.5%, 4.1%, and 6.2%, respectively. Corresponding all-cause readmission rates were 5.0%, 8.7%, and 13.3%. At 30 days, 60.6% of all-cause readmissions were considered nonpreventable by 3M-PPRs, more than one-half of which were related to malignancies. The percentage of readmissions rated as potentially preventable was similar at all 3 time intervals. Readmissions after chemotherapy, acute leukemia, and cystic fibrosis were all considered nonpreventable, and at least 80% of readmissions after index admissions for sickle cell crisis, bronchiolitis, ventricular shunt procedures, asthma, and appendectomy were designated potentially preventable. Total costs for all readmissions were $1.7 billion; PPRs accounted for 27.3% of these costs. The most costly readmissions were associated with ventricular shunt procedures ($26.5 million/year), seizures ($15.5 million/year), and sickle cell crisis ($15.0 million/year)., Conclusions: Rates of PPRs were significantly lower than all-cause readmission rates more than one-half of which were caused by exclusion of malignancies. Annual costs of PPRs, although significant in the aggregate, appear to represent a much smaller cost-savings opportunity for children than for adults. Our study may help guide children's hospitals to focus readmission reduction strategies on areas where the financial vulnerability is greatest based on 3M-PPRs., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Objectives: To describe readmissions among children hospitalized with H1N1 (influenza subtype, hemagglutinin1, neuraminidase 1) pandemic influenza and secondarily to determine the association of oseltamivir during index hospitalization with readmission., Methods: We reviewed data from 42 freestanding children's hospitals contributing to the Pediatric Health Information System from May through December 2009 when H1N1 was the predominant influenza strain. Children were divided into 2 groups by whether they experienced complications of influenza during index hospitalization. Primary outcome was readmission at 3, 7, and 30 days among both patient groups. Secondary outcome was the association of oseltamivir treatment with readmission., Results: The study included 8899 children; 6162 patients had uncomplicated index hospitalization, of whom 3808 (61.8%) received oseltamivir during hospitalization, and 2737 children had complicated influenza, of whom 1055 (38.5%) received oseltamivir. Median 3-, 7-, and 30-day readmission rates were 1.6%, 2.5%, and 4.7% for patients with uncomplicated index hospitalizations and 4.3%, 5.8%, and 10.3% among patients with complicated influenza. The 30-day readmission rates did not differ by treatment group among patients with uncomplicated influenza; however, patients with complicated index hospitalizations who received oseltamivir had lower all-cause 30-day readmissions than untreated patients. The most common causes of readmission were pneumonia and asthma exacerbations., Conclusions: Oseltamivir use for hospitalized children did not decrease 30-day readmission rates in children after uncomplicated index hospitalization but was associated with a lower 30-day readmission rate among children with complicated infections during the 2009 H1N1 pandemic. Readmission rates for children who had complicated influenza infection during index hospitalizations are high., (Copyright © 2014 by the American Academy of Pediatrics.)

Objective: To describe the design features, utilization, and outcomes of a protocol treating children with status asthmaticus with continuous albuterol in the inpatient setting., Methods: We performed a retrospective cohort analysis of children ages 2 to 18 treated in the non-intensive care, inpatient setting on a standardized treatment protocol for status asthmaticus from July 2011 to June 2013. We assessed characteristics associated with continuous albuterol therapy and, for those treated, duration of therapy and the proportion who clinically deteriorated (ICU transfer or progression to enhanced respiratory support) or who were identified as having hypokalemia or an arrhythmia. Using multivariable logistic regression, we determined which factors were associated with clinical deterioration or prolonged (>24 hours) continuous albuterol., Results: Of 3003 children meeting study criteria, 1298 (43%) received continuous albuterol. Older age, black race, lower initial oxygen saturation, and higher initial age-standardized heart rate and respiratory rate were associated with initiation of continuous albuterol therapy (P < .001 for all). Median duration of therapy was 14.4 hours (interquartile range, 7.7, 24.6); 340 children (26%) experienced prolonged therapy. Seventy children (5%) experienced clinical deterioration, and 33 children (3%) had identified hypokalemia or arrhythmia. Comorbid pneumonia and emergency department administration of intravenous magnesium or subcutaneous terbutaline were associated with prolonged therapy and clinical deterioration., Conclusions: With appropriate support structures and care processes, continuous albuterol can be delivered effectively in the non-ICU, inpatient setting with low rates of adverse outcomes. Certain initial clinical characteristics may help identify patients needing more intensive therapy., (Copyright © 2014 by the American Academy of Pediatrics.)

Background: Matching workforce to workload is particularly important in healthcare delivery, where an excess of workload for the available workforce may negatively impact processes and outcomes of patient care and resident learning. Hospitals currently lack a means to measure and match dynamic workload and workforce factors., Objectives: This article describes our work to develop and obtain consensus for use of an objective tool to dynamically match the front-line ordering clinician (FLOC) workforce to clinical workload in a variety of inpatient settings., Methods: We undertook development of a tool to represent hospital workload and workforce based on literature reviews, discussions with clinical leadership, and repeated validation sessions. We met with physicians and nurses from every clinical care area of our large, urban children's hospital at least twice., Results: We successfully created a tool in a matrix format that is objective and flexible and can be applied to a variety of settings. We presented the tool in 14 hospital divisions and received widespread acceptance among physician, nursing, and administrative leadership. The hospital uses the tool to identify gaps in FLOC coverage and guide staffing decisions., Discussion: Hospitals can better match workload to workforce if they can define and measure these elements. The Care Model Matrix is a flexible, objective tool that quantifies the multidimensional aspects of workload and workforce. The tool, which uses multiple variables that are easily modifiable, can be adapted to a variety of settings., (© 2014 Society of Hospital Medicine.)

Background: Although patient flow is a focus for improvement in hospitals, commonly used single or unaggregated measures fail to capture its complexity. Composite measures can account for multiple dimensions of performance but have not been reported for the assessment of patient flow., Objectives: To present and discuss the implementation of a composite measure system as a way to measure and monitor patient flow and improvement activities at an urban children's hospital., Methods: A 5-domain patient flow scorecard with composite measurement was designed by an interdisciplinary workgroup using measures involved in multiple aspects of patient flow., Results: The composite score measurement system provided improvement teams and administrators with a comprehensive overview of patient flow. It captured overall performance trends and identified operational domains and specific components of patient flow that required improvement., Discussion: A patient flow scorecard with composite measurement holds advantages over a single or unaggregated measurement system, because it provides a holistic assessment of performance while also identifying specific areas in need of improvement., (© 2014 Society of Hospital Medicine.)

Background: Deaths during induction chemotherapy for pediatric acute lymphoblastic leukemia (ALL) account for one-tenth of ALL-associated mortality and half of ALL treatment-related mortality. We sought to ascertain patient- and hospital-level factors associated with induction mortality., Procedure: We performed a retrospective cohort analysis of 8,516 children ages 0 to <19 years with newly diagnosed ALL admitted to freestanding US children's hospitals from 1999 to 2009 using the Pediatric Health Information System database. Induction mortality risk was modeled accounting for demographics, intensive care unit-level interventions, and socioeconomic status (SES) using Cox regression. The association of ALL induction mortality with hospital-level factors including volume, hospital-wide mortality and payer mix was analyzed with multiple linear regression., Results: ALL induction mortality was 1.12%. Race and patient-level SES factors were not associated with induction mortality. Patients receiving both mechanical ventilation and vasoactive infusions experienced nearly 50% mortality (hazard ratio 122.30, 95% CI 66.56-224.80). Institutions in the highest induction mortality quartile contributed 27% of all patients but nearly half of all deaths (47 of 95). Hospital payer mix was associated with ALL induction mortality after adjustment for other hospital-level factors (P = 0.046)., Conclusions: The overall risk of induction death is low but substantially increased in patients with cardio-respiratory and other organ failures. Induction mortality varies up to three-fold across hospitals and is correlated with hospital payer mix. Further work is needed to improve induction outcomes in hospitals with higher mortality. These data suggest an induction mortality rate of less than 1% may be an attainable national benchmark., (© 2013 Wiley Periodicals, Inc.)

Background and Objective: Child health is influenced by biomedical and socioeconomic factors. Few studies have explored the relationship between community-level income and inpatient resource utilization for children. Our objective was to analyze inpatient costs for children hospitalized with common conditions in relation to zip code-based median annual household income (HHI)., Methods: Retrospective national cohort from 32 freestanding children's hospitals for asthma, diabetes, bronchiolitis and respiratory syncytial virus, pneumonia, and kidney and urinary tract infections. Standardized cost of care for individual hospitalizations and across hospitalizations for the same patient and condition were modeled by using mixed-effects methods, adjusting for severity of illness, age, gender, and race. Main exposure was median annual HHI. Posthoc tests compared adjusted standardized costs for patients from the lowest and highest income groups., Results: From 116,636 hospitalizations, 4 of 5 conditions had differences at the hospitalization and at the patient level, with lowest-income groups having higher costs. The individual hospitalization level cost differences ranged from $187 (4.1%) to $404 (6.4%). Patient-level cost differences ranged from $310 to $1087 or 6.5% to 15% higher for the lowest-income patients. Higher costs were typically not for laboratory, imaging, or pharmacy costs. In total, patients from lowest income zip codes had $8.4 million more in hospitalization-level costs and $13.6 million more in patient-level costs., Conclusions: Lower community-level HHI is associated with higher inpatient costs of care for 4 of 5 common pediatric conditions. These findings highlight the need to consider socioeconomic status in health care system design, delivery, and reimbursement calculations.

Objective: To test the hypothesis that children's hospitals with shorter length of stay (LOS) for hospitalized patients have higher all-cause readmission rates., Study Design: Longitudinal, retrospective cohort study of the Pediatric Health Information System of 183616 admissions within 43 US children's hospitals for appendectomy, asthma, gastroenteritis, and seizure between July 2009 and June 2011. Admissions were stratified by medical complexity, based on whether patients had a complex chronic health condition, were neurologically impaired, or were assisted with medical technology. Outcome measures include LOS; all-cause readmission rates within 3, 7, 15, and 30 days; and the association between hospital-specific mean LOS and all-cause readmission rates as determined by linear regression., Results: Mean LOS was <3 days for all patients across all conditions, except for appendectomy in complex patients (mean LOS 3.7 days, 95% CI 3.47-4.01). Condition-specific 3-, 7-, 15-, and 30-day all-cause readmission rates for noncomplex patients were all <5%. Condition-specific readmission rates for complex patients ranged from <1% at 3 days for seizures to 16% at 30 days for gastroenteritis. There was no linear association between hospital-specific, condition-specific mean LOS, stratified by medical complexity, and all-cause readmission rates at any time interval within 30 days (all P values ≥.10)., Conclusion: In children's hospitals, LOS is short and readmission rates are low for asthma, appendectomy, gastroenteritis, and seizure admissions. In the conditions studied, there is no association between shorter hospital-specific LOS and higher readmission rates within the LOS observed., (Copyright © 2013 Mosby, Inc. All rights reserved.)

Background and Objective: Education of residents in academic medical centers occurs as part of clinical care, but little is known about the relationship between clinical workload and educational experiences among pediatric residents. The goal of this study was to assess residents' perceptions of learning on inpatient services at a children's hospital in relation to perceived workload and actual patient census., Methods: This was a prospective cohort study of pediatric residents at 1 urban academic children's hospital. Surveys on educational experience were administered weekly to residents on 12 inpatient units from October 2010 to June 2011. Daily peak medical inpatient census data were collected, and Pearson correlations were performed., Results: Mean weekly response rate was 25%. Perceived workload was correlated with weekly peak of patient census for interns (r = 0.66; P= .00) and senior residents (r = 0.73; P = .00). Many aspects of perceived learning were negatively correlated with perceived workload among interns and residents in "acute care" units. Activities beyond direct patient care (eg, attending conferences, independent reading) revealed more negative correlation than educational experience during rounds. Among seniors, scores of aspects of perceived learning did not correlate with workload., Conclusions: The study found mostly negative associations between high perceived workload and perceived learning, especially for interns. Results suggest varied impact of workload on perceived learning by training year. Although patient care is essential for resident education, higher workload may adversely affect learning opportunities for pediatric trainees. More research is needed to identify if generalizable thresholds of patient census and/or clinical workload cause declines in perceived or real education.

Background and Objective: Observation status, in contrast to inpatient status, is a billing designation for hospital payment. Observation-status stays are presumed to be shorter and less resource-intensive, but utilization for pediatric observation-status stays has not been studied. The goal of this study was to describe resource utilization characteristics for patients in observation and inpatient status in a national cohort of hospitalized children in the Pediatric Health Information System., Methods: This study was a retrospective cohort from 2010 of observation- and inpatient-status stays of ≤2 days; all children were admitted from the emergency department. Costs were analyzed and described. Comparison between costs adjusting for age, severity, and length of stay were conducted by using random-effect mixed models to account for clustering of patients within hospitals., Results: Observation status was assigned to 67 230 (33.3%) discharges, but its use varied across hospitals (2%-45%). Observation-status stays had total median costs of $2559, including room costs and $678 excluding room costs. Twenty-five diagnoses accounted for 74% of stays in observation status, 4 of which were used for detailed analyses: asthma (n = 6352), viral gastroenteritis (n = 4043), bronchiolitis (n = 3537), and seizure (n = 3289). On average, after risk adjustment, observation-status stays cost $260 less than inpatient-status stays for these select 4 diagnoses. Large overlaps in costs were demonstrated for both types of stay., Conclusions: Variability in use of observation status with large overlap in costs and potential lower reimbursement compared with inpatient status calls into question the utility of segmenting patients according to billing status and highlights a financial risk for institutions with a high volume of pediatric patients in observation status.

Objectives: The objective of this study was to test the impact of an education and training intervention about management of common childhood illnesses on caregiver knowledge and health service use by an index child., Methods: This was a quasi-experimental, preintervention-postintervention pilot study of a primary care-based intervention among 32 caregivers of urban children aged 7 months to 5 years. Intervention consisted of a 90-minute educational activity developed after input from focus groups and taught by pediatric nurses; it addressed management of fever, colds, and minor trauma in children at home. Caregiver knowledge before, immediately after, and 6 months after intervention was tested using a written instrument. Health services utilization for an index child in the family was collected 6 months before and after intervention., Results: Caregiver knowledge, as assessed by mean score on the test instrument, increased immediately after the intervention. It was lower at 6-month follow-up but remained higher than pretest. Total health services utilization, adjusted for patient and caregiver factors, did not change significantly 6 months after the intervention. After-hours calls to the primary care physician increased from a mean of 0.33 to 1.46 per patient (P = 0.047), making it the only behavior with significant change. Preintervention health services utilization was the strongest positive predictor of postintervention health services use., Conclusions: The primary care-based intervention led to increased caregiver knowledge regarding management of common minor childhood illnesses and to increased after-hours telephone use. There was no significant decrease in ED use. To reduce reliance on the ED for nonurgent conditions, additional strategies may be needed.

Objective: Describe variability in admission, discharge, and occupancy patterns for surgical patients at a large children's hospital and assess the relationship between scheduled admissions and occupancy., Background: High hospital occupancy degrades quality of care and access, whereas low levels of occupancy use hospital resources inefficiently. Variability in scheduling patients for surgical procedures may affect occupancy and be amenable to alteration., Methods: This is a retrospective administrative data analysis that took place at 1 urban, tertiary-care children's hospital. A total of 8552 surgical patients hospitalized from July 1, 2009, to June 30, 2010, were included in the analysis, and admission-discharge-transfer data for 1 fiscal year were abstracted for analysis of admission and occupancy patterns., Results: Among 6257 surgical admissions for non-intensive care unit (ICU) patients, 49% were emergent and 51% were scheduled. Variation in admission volume by day of week was more than 3 times higher for scheduled admissions than for emergent admissions. For non-ICU surgical patients with length of stay 7 days or less (97%), Mondays and Tuesdays generated 42% of scheduled patient occupancy time. Thursdays and Fridays often had high occupancy of surgical patients (>90% of designated beds filled), whereas Saturdays, Sundays, and Mondays were often at low occupancy for those beds (<80% filled). Only 20% of all days in the year had designated non-ICU surgery beds with occupancy between 80% and 95%., Conclusions: Scheduled admissions contribute significantly to variability in occupancy. Predictable patterns of admissions lead to high occupancy on some days and unused capacity on others, with few days being at an optimal level of occupancy. These predictable patterns suggest opportunities to improve hospital operations with changes in scheduled admission patterns, which present a different problem than random demand.

Objective: Socioeconomic status (SES) is inversely related to pediatric mortality in the community. However, it is unknown if this association exists for in-hospital pediatric mortality. Our objective was to determine the association of SES with in-hospital pediatric mortality among children's hospitals and to compare observed mortality with expected mortality generated from national all-hospital inpatient data., Methods: This is a retrospective cohort study from 2009 to 2010 of all 1,053,101 hospitalizations at 42 tertiary care, freestanding children's hospitals. The main exposure was SES, determined by the median annual household income for the patient's ZIP code. The main outcome measure was death during the admission. Primary outcomes of interest were stratified by income and diagnosis-based service lines. Observed-to-expected mortality ratios were created, and trends across quartiles of SES were examined., Results: Death occurred in 8950 (0.84%) of the hospitalizations. Overall, mortality rates were associated with SES (P < .0001) and followed an inverse linear association (P < .0001). Similarly, observed-to-expected mortality was associated with SES in an inverse association (P = .014). However, mortality overall was less than expected for all income quartiles (P < .05). The association of SES and mortality varied by service line; only 3 service lines (cardiac, gastrointestinal, and neonatal) demonstrated an inverse association between SES and observed-to-expected mortality., Conclusions: Within children's hospitals, SES is inversely associated with in-hospital mortality, but is lower than expected for even the lowest SES quartile. The association between SES and mortality varies by service line. Multifaceted interventions initiated in the inpatient setting could potentially ameliorate SES disparities in in-hospital pediatric mortality.

Objective: To describe 1 pediatric integrated delivery system's experience with the influenza A (H1N1) pandemic in 2009 to illustrate the benefits of coordination, scale, scope, and flexibility in handling large volumes of patients in many locations., Methods: Through multidisciplinary planning across a large, multisite pediatric delivery system, an effective 3-tier plan was developed to handle anticipated increased volumes associated with the fall 2009 influenza pandemic in the Philadelphia region., Results: Patient demand for services increased to record-setting levels, particularly for emergency department visits and phone calls. The 3-tier plan of response allowed for graded and appropriate response to volumes that more than doubled in many locations. Measured by wait times and leftwithout- being-seen rates, the system appeared to match capacity to demand effectively. Lessons learned in terms of successes and challenges are useful for future planning., Conclusions: The experience of 1 pediatric delivery system in handling increased volume due to pandemic influenza may hold lessons for other organizations and for policy makers seeking to improve the preparedness, quality, and value of healthcare. These experiences do not imply the need for vertical integration with ownership, but do support tight coordination, communication, integration, and alignment in any management structure.

Objective: To examine the relationship between local macroeconomic indicators and physical abuse admission rates to pediatric hospitals over time., Methods: Retrospective study of children admitted to 38 hospitals in the Pediatric Hospital Information System database. Hospital data were linked to unemployment, mortgage delinquency, and foreclosure data for the associated metropolitan statistical areas. Primary outcomes were admission rates for (1) physical abuse in children <6 years old, (2) non-birth, non-motor vehicle crash-related traumatic brain injury (TBI) in infants <1 year old (which carry high risk for abuse), and (3) all-cause injuries. Poisson fixed-effects regression estimated trends in admission rates and associations between those rates and trends in unemployment, mortgage delinquency, and foreclosure., Results: Between 2000 and 2009, rates of physical abuse and high-risk TBI admissions increased by 0.79% and 3.1% per year, respectively (P ≤ .02), whereas all-cause injury rates declined by 0.80% per year (P < .001). Abuse and high-risk TBI admission rates were associated with the current mortgage delinquency rate and with the change in delinquency and foreclosure rates from the previous year (P ≤ .03). Neither abuse nor high-risk TBI rates were associated with the current unemployment rate. The all-cause injury rate was negatively associated with unemployment, delinquency, and foreclosure rates (P ≤ .007)., Conclusions: Multicenter hospital data show an increase in pediatric admissions for physical abuse and high-risk TBI during a time of declining all-cause injury rate. Abuse and high-risk TBI admission rates increased in relationship to local mortgage delinquency and foreclosure trends.

Background: The pediatric intensive care unit (PICU), with limited number of beds and resource-intensive services, is a key component of patient flow. Because the PICU is a crossroads for many patients, transfer or discharge delays can negatively impact a patient's clinical status and efficiency., Objective: The objective of this study was to describe, using direct observation, PICU bed utilization., Methods: We conducted a real-time, prospective observational study in a convenience sample of days in the PICU of an urban, tertiary-care children's hospital., Results: Among 824 observed hours, 19,887 bed-hours were recorded, with 82% being for critical care services and 18% for non-critical care services. Fourteen activities accounted for 95% of bed-hours. Among 200 hours when the PICU was at full capacity, 75% of the time included at least 1 bed that was used for non-critical care services; 37% of the time at least 2 beds. The mean waiting time for a floor bed assignment was 9 hours (median, 5.5 hours) and accounted for 4.62% of all bed-hours observed., Conclusions: The PICU delivered critical care services most of the time, but periods of non-critical care services represented a significant amount of time. In particular, periods with no bed available for new patients were associated with at least 1 or more PICU beds being used for non-critical care activities. The method should be reproducible in other settings to learn more about the structure and processes of care and patient flow and to make improvements., (Copyright © 2011 Society of Hospital Medicine.)

Context: The Children's Asthma Care (CAC) measure set evaluates whether children admitted to hospitals with asthma receive relievers (CAC-1) and systemic corticosteroids (CAC-2) and whether they are discharged with a home management plan of care (CAC-3). It is the only Joint Commission core measure applicable to evaluate the quality of care for hospitalized children., Objectives: To evaluate longitudinal trends in CAC measure compliance and to determine if an association exists between compliance and outcomes., Design, Setting, and Patients: Cross-sectional study using administrative data and CAC compliance data for 30 US children's hospitals. A total of 37,267 children admitted with asthma between January 1, 2008, and September 30, 2010, with follow-up through December 31, 2010, accounted for 45,499 hospital admissions. Hospital-level CAC measure compliance data were obtained from the National Association of Children's Hospitals and Related Institutions. Readmission and postdischarge emergency department (ED) utilization data were obtained from the Pediatric Health Information System., Main Outcome Measures: Children's Asthma Care measure compliance trends; postdischarge ED utilization and asthma-related readmission rates at 7, 30, and 90 days., Results: The minimum quarterly CAC-1 and CAC-2 measure compliance rates reported by any hospital were 97.1% and 89.5%, respectively. Individual hospital CAC-2 compliance exceeded 95% for 97.9% of the quarters. Lack of variability in CAC-1 and CAC-2 compliance precluded examination of their association with the specified outcomes. Mean CAC-3 compliance was 40.6% (95% CI, 34.1%-47.1%) and 72.9% (95% CI, 68.8%-76.9%) for the initial and final 3 quarters of the study, respectively. The mean 7-, 30-, and 90-day postdischarge ED utilization rates were 1.5% (95% CI, 1.3%-1.6%), 4.3% (95% CI, 4.0%-4.5%), and 11.1% (95% CI, 10.5%-11.7%) and the mean quarterly 7-, 30-, and 90-day readmission rates were 1.4% (95% CI, 1.2%-1.6%), 3.1% (95% CI, 2.8%-3.3%), and 7.6% (95% CI, 7.2%-8.1%). There was no significant association between overall CAC-3 compliance (odds ratio [OR] for 5% improvement in compliance) and postdischarge ED utilization rates at 7 days (OR, 1.00; 95% CI, 0.98-1.02), 30 days (OR, 0.97; 95% CI, 0.90-1.04), and 90 days (OR, 0.96; 95% CI, 0.77-1.18). In addition, there was no significant association between overall CAC-3 compliance (OR for 5% improvement in compliance) and readmission rates at 7 days (OR, 1.00; 95% CI, 0.99-1.02), 30 days (OR, 0.99; 95% CI, 0.96-1.02), and 90 days (OR, 1.01; 95% CI, 0.90-1.12)., Conclusion: Among children admitted to pediatric hospitals for asthma, there was high hospital-level compliance with CAC-1 and CAC-2 quality measures and moderate compliance with the CAC-3 measure but no association between CAC-3 compliance and subsequent ED visits and asthma-related readmissions.

Objective: To quantify the difference in weekday versus weekend occupancy, and the opportunity to smooth inpatient occupancy to reduce crowding at children's hospitals., Methods: Daily inpatient census data for 39 freestanding, tertiary-care children's hospitals were used to calculate occupancy and to model the impact of reducing variation in occupancy and the change in the number of patients, patient-days, and hospitals exposed to high occupancy pre- and post-smoothing. We also calculated the proportion of weekly admissions that would require different scheduling to achieve within-week smoothing., Results: Overall, hospitals' mean occupancy ranged from 70.9% to 108.1% on weekdays, and 65.7% to 94.9% on weekends. Weekday occupancy exceeded weekend occupancy with a median difference of 8.2% points. The mean post-smoothing reduction in weekly maximum occupancy across all hospitals was 6.6% points. Through smoothing, 39,607 patients from the 39 hospitals were removed from exposure to occupancy levels >95%. To achieve within-week smoothing, a median 2.6% of admissions would have to be scheduled on a different day of the week; this equates to a median of 7.4 patients per week (range: 2.3-14.4)., Conclusion: Hospitals do have substantial unused capacity, and smoothing occupancy over the course of a week could be a useful strategy that hospitals can use to reduce crowding and protect patients from crowded conditions., (Copyright © 2011 Society of Hospital Medicine.)

Quantifying how close hospitals came to exhausting capacity during the outbreak of pandemic influenza A (H1N1) 2009 can help the health care system plan for more virulent pandemics. This ecologic analysis used emergency department (ED) and inpatient data from 34 US children's hospitals. For the 11-week pandemic (H1N1) 2009 period during fall 2009, inpatient occupancy reached 95%, which was lower than the 101% occupancy during the 2008-09 seasonal influenza period. Fewer than 1 additional admission per 10 inpatient beds would have caused hospitals to reach 100% occupancy. Using parameters based on historical precedent, we built 5 models projecting inpatient occupancy, varying the ED visit numbers and admission rate for influenza-related ED visits. The 5 scenarios projected median occupancy as high as 132% of capacity. The pandemic did not exhaust inpatient bed capacity, but a more virulent pandemic has the potential to push children's hospitals past their maximum inpatient capacity.

Unlabelled: In the spring of 2009, the first patients infected with 2009 H1N1 virus were arriving for care in hospitals in the United States. Anticipating a second wave of infection, our hospital leaders initiated multidisciplinary planning activities to prepare to increase capacity by expansion of emergency department (ED) and inpatient functional space and redeployment of medical personnel., Experience: During the fall pandemic surge, this urban, tertiary-care children's hospital experienced a 48% increase in ED visits and a 12% increase in daily peak inpatient census. However, several strategies were effective in mitigating the pandemic's impact including using a portion of the hospital's lobby for ED waiting, using a subspecialty clinic and a 24-hour short stay unit to care for ED patients, and using physicians not board certified in pediatric emergency medicine and inpatient-unit medical nurses to care for ED patients. The average time patients waited to be seen by an ED physician and the proportion of children leaving the ED without being seen by a physician was less than for the period when seasonal influenza peaked in the winter of 2008-2009. Furthermore, the ED did not go on divert status, no elective medical or surgical admissions required cancellation, and there were no increases in serious patient safety events., Summary: Our health center successfully met the challenges posed by the 2009 H1N1 outbreak. The intent in sharing the details of our planning and experience is to allow others to determine which elements of this planning might be adapted for managing a surge of patients in their setting.

Background: High hospital occupancy is a challenge for quality of care and access, while low levels of occupancy may be inefficient in terms of resource utilization. Variability from scheduling decisions may affect occupancy and be amenable to alteration., Objective: Describe variability in admission, discharge, and occupancy patterns at a large children's hospital and assess the relationship between scheduled admissions and occupancy., Design: Retrospective administrative data analysis., Setting: One urban, tertiary-care children's hospital., Patients: A total of 22,310 consecutive patients admitted from July 1, 2007 to June 30, 2008., Measurements: Admission-discharge-transfer (ADT) data for 1 fiscal year were abstracted for analysis of admission and occupancy patterns., Results: Among 22,310 admissions, 78% were coded as emergent and 22% as scheduled. Variation in admission volume by day of week was high for scheduled admissions (coefficient of variation [CV] 65.3%), while it was more consistent for emergent admissions (CV 12.0%). For patients with length of stay (LOS) ≤ 7 days (84%), Mondays and Tuesdays generated 45.2% of scheduled patient hours. Wednesdays and Thursdays had the highest frequency of high occupancy., Conclusions: Scheduled admissions contribute significantly to variability in occupancy and risk of mid-week crowding. Predictable patterns of admissions lead to high occupancy on some days and unused capacity on others, which can be addressed with proactive management of admissions (eg, greater use of unused capacity on weekends and in summer). Hospitals interested in optimizing patient flow should assess their admission and occupancy patterns. Further studies should link variation in occupancy to outcomes including quality of care, educational activities, and staff satisfaction., (Copyright © 2010 Society of Hospital Medicine.)

Objectives: The objective was to describe the emergency department (ED) resource burden of the spring 2009 H1N1 influenza pandemic at U.S. children's hospitals by quantifying observed-to-expected utilization., Methods: The authors performed an ecologic analysis for April through July 2009 using data from 23 EDs in the Pediatric Health Information System (PHIS), an administrative database of widely distributed U.S. children's hospitals. All ED visits during the study period were included, and data from the 5 prior years were used for establishing expected values. Primary outcome measures included observed-to-expected ratios for ED visits for all reasons and for influenza-related illness (IRI)., Results: Overall, 390,983 visits, and 88,885 visits for IRI, were included for Calendar Weeks 16 through 29, when 2009 H1N1 influenza was circulating. The subset of 106,330 visits and 31,703 IRI visits made to the 14 hospitals experiencing the authors' definition of ED surge during Weeks 16 to 29 was also studied. During surge weeks, the 14 EDs experienced 29% more total visits and 51% more IRI visits than expected (p < 0.01 for both comparisons). Of ED IRI visits during surge weeks, only 4.8% were admitted to non-intensive care beds (70% of expected, p < 0.01), 0.19% were admitted to intensive care units (44% of expected, p < 0.01), and 0.01% received mechanical ventilation (5.0% of expected, p < 0.01). Factors associated with more-than-expected visits included ages 2-17 years, payer type, and asthma. No factors were associated with more-than-expected hospitalizations from the ED., Conclusions: During the spring 2009 H1N1 influenza pandemic, pediatric EDs nationwide experienced a marked increase in visits, with far fewer than expected requiring nonintensive or intensive care hospitalization. The data in this study can be used for future pandemic planning., (© 2011 by the Society for Academic Emergency Medicine.)

Objective: High hospital occupancy may lead to overcrowding in emergency departments and inpatient units, having an adverse impact on patient care. It is not known how children's hospitals acutely respond to high occupancy. The objective of this study was to describe the frequency, direction, and magnitude of children's hospitals' acute responses to high occupancy., Methods: Patients who were discharged from 39 children's hospitals that participated in the Pediatric Health Information System database during 2006 were eligible. Midnight census data were used to construct occupancy levels. Acute response to high occupancy was measured by 8 variables, including changes in hospital admissions (4 measures), transfers (2 measures), and length of stay (2 measures)., Results: Hospitals were frequently at high occupancy, with 28% of midnights at 85% to 94% occupancy and 42% of midnights at > or =95% occupancy. Whereas half of children's hospitals used occupancy-mitigating responses, there was variability in responses and magnitudes were small. When occupancy was >95%, no more than 8% of hospitals took steps to reduce admissions, 13% increased transfers out, and up to 58% reduced standardized length of stay. Two-day lag response was more common but remained of too small a magnitude to make a difference in hospital crowding. Additional modeling techniques also revealed little response., Conclusions: We found a low rate of acute response to high occupancy. When there was a response, the magnitude was small.