Association of Weekend Admission and Weekend Discharge with Length of Stay and 30-Day Readmission in Children's Hospitals.

2018

2018 10 31

1553-5606

<p><strong>BACKGROUND: </strong>Worse outcomes among adults presenting for/receiving care on weekends (ie, "the weekend effect") have been observed for many diseases. However, little is known about the overall impact of the weekend effect in hospitalized children.</p>

<p><strong>OBJECTIVE: T</strong>o determine the association between weekend admission and length of stay (LOS) and between weekend discharge and 30-day all-cause readmission.</p>

<p><strong>METHODS: </strong>We conducted a retrospective, cross-sectional study of children hospitalized between October 1, 2014 and September 30, 2015 using the Pediatric Health Information System. Birth hospitalizations and planned procedures were excluded. We used generalized linear mixed modeling to assess the independent association between weekend admission and LOS and weekend discharge and readmission risk.</p>

<p><strong>RESULTS: </strong>Among 390,745 hospitalizations across 43 hospitals, the median LOS was 41 hours (interquartile range [IQR] 24-71) and the 30-day readmission rate was 8.2% (IQR 7.2-9.4). We observed no association between weekend admission and LOS (adjusted LOS [95% CI: weekend 63.70 [61.01-66.52] hours vs weekday 63.40 [60.73-66.19] hours, P = .112). Weekend discharge was associated with slightly increased odds of readmission compared with weekday discharge (adjusted probability of readmission [95% CI]: weekend 0.13 [0.12-0.13] versus weekday 0.11 [0.11-0.12], P &lt; .001) but was variable among individual hospitals. Patient characteristics (ie, number of chronic conditions) were more strongly associated with LOS and readmission risk than weekend admission or discharge.</p>

<p><strong>CONCLUSIONS: </strong>Patient-level factors (ie, clinical and demographic characteristics) are more indicative of longer LOS and readmission risk than weekend admissions or discharges. The overall impact of the weekend effect across children's hospitals was minimal.</p>

10.12788/jhm.3085

J Hosp Med

30379138

Adding Social Determinant Data Changes Children's Hospitals' Readmissions Performance.

2017

2017 May 02

1097-6833

<p><strong>OBJECTIVES: </strong>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.</p>

<p><strong>STUDY DESIGN: </strong>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.</p>

<p><strong>RESULTS: </strong>For the 458 686 discharges meeting PACR inclusion criteria, in multivariable models, factors associated with higher discharge-level PACR measure included age &lt;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.</p>

<p><strong>CONCLUSIONS: </strong>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.</p>

10.1016/j.jpeds.2017.03.056

J. Pediatr.

28476461

Children's Hospital Characteristics and Readmission Metrics.

2017

2017 Jan 25

1098-4275

<p><strong>BACKGROUND AND OBJECTIVE: </strong>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.</p>

<p><strong>METHODS: </strong>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.</p>

<p><strong>RESULTS: </strong>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.</p>

<p><strong>CONCLUSIONS: </strong>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.</p>

10.1542/peds.2016-1720

Pediatrics

28123044

Association of Social Determinants With Children's Hospitals' Preventable Readmissions Performance.

2016

350-8

2016 Apr 1

2168-6211

<p><strong>IMPORTANCE: </strong>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.</p>

<p><strong>OBJECTIVE: </strong>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.</p>

<p><strong>DESIGN, SETTING, AND PARTICIPANTS: </strong>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.</p>

<p><strong>EXPOSURES: </strong>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.</p>

<p><strong>MAIN OUTCOMES AND MEASURES: </strong>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.</p>

<p><strong>RESULTS: </strong>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).</p>

<p><strong>CONCLUSIONS AND RELEVANCE: </strong>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.</p>

10.1001/jamapediatrics.2015.4440

JAMA Pediatr

26881387

Admission chest radiographs predict illness severity for children hospitalized with pneumonia.

2014

559-64

2014 Sep

1553-5606

<p><strong>OBJECTIVE: </strong>To assess whether radiographic findings predict outcomes among children hospitalized with pneumonia.</p>

<p><strong>METHODS: </strong>This retrospective study included children &lt;18 years of age from 4 children's hospitals admitted in 2010 with clinical and radiographic evidence of pneumonia. Admission radiographs were categorized as single lobar, unilateral or bilateral multilobar, or interstitial. Pleural effusions were classified as absent, small, or moderate/large. Propensity scoring was used to adjust for potential confounders, including need for supplemental oxygen, intensive care, and mechanical ventilation, as well as hospital length of stay and duration of supplemental oxygen.</p>

<p><strong>RESULTS: </strong>There were 406 children (median age, 3 years). Infiltrate patterns included: single lobar, 61%; multilobar unilateral, 13%; multilobar bilateral, 16%; and interstitial, 10%. Pleural effusion was present in 21%. Overall, 63% required supplemental oxygen (median duration, 31.5 hours), 8% required intensive care, and 3% required mechanical ventilation. Median length of stay was 51.5 hours. Compared with single lobar infiltrate, all other infiltrate patterns were associated with need for intensive care; only bilateral multilobar infiltrate was associated with need for mechanical ventilation (adjusted odds ratio [aOR]: 3.0, 95% confidence interval [CI]: 1.2-7.9). Presence of effusion was associated with increased length of stay and duration of supplemental oxygen; only moderate/large effusion was associated with need for intensive care (aOR: 3.2, 95% CI: 1.1-8.9) and mechanical ventilation (aOR: 14.8, 95% CI: 9.8-22.4).</p>

<p><strong>CONCLUSIONS: </strong>Admission radiographic findings are associated with important hospital outcomes and care processes and may help predict disease severity.</p>

10.1002/jhm.2227

J Hosp Med

24942619

Improving asthma care in the hospital: an overview of treatments and quality improvement interventions for children hospitalized for status asthmaticus

2015

100-112

03/2015

Pediatric hospital discharge interventions to reduce subsequent utilization: a systematic review.

2014

251-60

2014 Apr

1553-5606

<p><strong>BACKGROUND: </strong>Reducing avoidable readmission and posthospitalization emergency department (ED) utilization has become a focus of quality-of-care measures and initiatives. For pediatric patients, no systematic efforts have assessed the evidence for interventions to reduce these events.</p>

<p><strong>PURPOSE: </strong>We sought to synthesize existing evidence on pediatric discharge practices and interventions to reduce hospital readmission and posthospitalization ED utilization.</p>

<p><strong>DATA SOURCES: </strong>PubMed and the Cumulative Index to Nursing and Allied Health Literature.</p>

<p><strong>STUDY SELECTION: </strong>Studies available in English involving pediatric inpatient discharge interventions with at least 1 outcome of interest were included.</p>

<p><strong>DATA EXTRACTION: </strong>We utilized a modified Cochrane Good Practice data extraction tool and assessed study quality with the Downs and Black tool.</p>

<p><strong>DATA SYNTHESIS: </strong>Our search identified a total of 1296 studies, 14 of which met full inclusion criteria. All included studies examined multifaceted discharge interventions initiated in the inpatient setting. Overall, 2 studies demonstrated statistically significant reductions in both readmissions and subsequent ED visits, 4 studies demonstrated statistically significant reductions in either readmissions or ED visits, and 2 studies found statistically significant increases in subsequent utilization. Several studies were not sufficiently powered to detect changes in either subsequent utilization outcome measure.</p>

<p><strong>CONCLUSIONS: </strong>Interventions that demonstrated reductions in subsequent utilization targeted children with specific chronic conditions, providing enhanced inpatient feedback and education reinforced with postdischarge support. Interventions seeking to reduce subsequent utilization should identify an individual or team to assume responsibility for the inpatient-to-outpatient transition and offer ongoing support to the family via telephone or home visitation following discharge.</p>

10.1002/jhm.2134

J Hosp Med

24357528

Rates and impact of potentially preventable readmissions at children's hospitals.

2015

613-9.e5

03/2015

1097-6833

<p><strong>OBJECTIVE: </strong>To assess readmission rates identified by 3M-Potentially Preventable Readmissions software (3M-PPRs) in a national cohort of children's hospitals.</p>

<p><strong>STUDY DESIGN: </strong>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.</p>

<p><strong>RESULTS: </strong>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).</p>

<p><strong>CONCLUSIONS: </strong>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.</p>

10.1016/j.jpeds.2014.10.052

J. Pediatr.

25477164