Potentially Preventable 30-Day Hospital Readmissions at a Children's Hospital

Hospital discharge intervention developed in a dialogical way with families to prepare them to care for children with chronic diseases at home: Mixed methods study

A convergent parallel mixed methods design with qualitative data collection embedded in a quasi-experimental study was developed to examine the potential of three modalities of preparation for hospital discharge of the families of children with chronic diseases in terms of uncertainty levels and management of the disease at home. Caregivers of these children were divided into three groups: two experimental groups and one control group. Two scales were applied: one measured family management, and the other evaluated uncertainties in relation to the disease. In addition, an in-depth interview was conducted. Wilcoxon's test and the integrated response index were used in data analysis to compare performance between the groups. Inductive thematic analysis was employed for the qualitative data. The data were integrated, comparing the groups before and after preparation for hospital discharge. Twenty-five family caregivers completed this study. Data integration showed that the intervention group, in which the families developed planning to prepare for discharge in a dialogical way with professionals, presented better perceptions regarding care management when compared to structured guide and usual care groups. Participation of families in planning for hospital discharge showed a reduction in uncertainties regarding the disease and better care management of children at home.

Predictive Value of LACE Scores for Pediatric Readmissions

INTRODUCTION

Hospital readmissions are recognized as a prevalent, yet potentially preventable, personal and economic burden. Length of stay, Acuity of admission, Comorbidities, and number of Emergency Department visits in the preceding 6 months can be quantified into one score, the LACE score. LACE scores have previously been identified to correlate with hospital readmissions within 30 days of discharge, but research specific to the pediatric population is scant. The objective of the present study was to investigate if LACE scores, in addition to other factors, can be utilized to create a predictive pediatric hospital readmission model that may ultimately be used to decrease readmission rates.

METHODS

This study included 25,616 hospitalizations of patients under the age of 18 years. Data were extracted from a hospital network electronic medical record. Demographics included LACE scores, age, gender, race/ethnicity, median household income, and medical centers. The primary exposure variable was LACE score. The main outcome measures were readmissions within 7, 14, and 30 days. The area under the curve (AUC) was used to assess the predictive capability of the regression model on patient 30-day admission.

RESULTS

LACE scores, age, gender, race/ethnicity, median household income, and medical centers were examined in a multivariable model to assess patient risk of a 30-day readmission. Only age and LACE score were observed to be statistically significant. The AUC for the combined model was 0.69.

DISCUSSION

As only age and LACE score were observed to be statistically significant and the AUC for the combined model was 0.69, this model is considered to have poor predictive capability.

CONCLUSIONS

In this study, LACE scores, as well the other factors, had a poor predictive capability for pediatric readmissions.

Comprehensive care programmes for children with medical complexity

BACKGROUND

Children with medical complexity (CMC) represent a small, but growing, proportion of all children. Regardless of their underlying diagnosis, by definition, all CMC have similar functional limitations and high healthcare needs. It has been suggested that improving aspects of healthcare delivery for CMC improves health- and quality of life-related outcomes for children and their families and reduces healthcare-related expenditure. As a result, dedicated comprehensive care programmes have been established at many hospitals to meet the needs of CMC; however, it is unclear if such programmes are effective.

OBJECTIVES

Our main objective was to assess the effectiveness of comprehensive care programmes that aim to improve care coordination and other aspects of health care for CMC and to assess whether the effectiveness of such programmes differs according to the programme setting and structure. We aimed to assess their effectiveness in relation to child and parent health, functioning, and quality of life, quality of care, number of healthcare encounters, unmet healthcare needs, and total healthcare-related costs.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, and CINAHL in May 2023. We also searched reference lists, trial registries, and the grey literature.

SELECTION CRITERIA

Randomised and non-randomised trials, controlled before-after studies, and interrupted time series studies were included. Studies that compared enrolment in a comprehensive care programme with non-enrolment in such a programme/treatment as usual were included. Participants were children that met the criteria for the definition of CMC, which is: having (i) a chronic condition, (ii) functional limitations, (iii) increased health and other service needs, and (iv) increased healthcare costs. Studies that included the following types of outcomes were included: health; quality of care; utilisation, coverage and access; resource use and costs; equity; and adverse outcomes.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data, assessed the risk of bias in each included study, and evaluated the certainty of evidence according to GRADE criteria. Where possible, data were represented in forest plots and pooled. We were unable to undertake a meta-analysis for comparisons and outcomes, so we used a structured synthesis approach.

MAIN RESULTS

We included four studies with a total of 912 CMC as participants. All included studies were randomised controlled trials conducted in hospitals in the USA or Canada. Participants varied across the included studies; however, all four studies included children with complex and chronic illness and high healthcare needs. While the primary aim of the intervention was similar across all four studies, the components of the interventions differed: in the four studies, the intervention involved some element of care coordination; in two of the studies, it involved the child receiving care from a multidisciplinary team, while in one study, the intervention was primarily centred on access to an advanced practice nurse care coordinator and another study involved nurse a practitioner-paediatrician dyad partnering with families. The risk of bias in the four studies varied across domains, with issues primarily relating to the lack of blinding of participants, personnel, and outcome assessors, inadequate allocation concealment, and incomplete outcome data. Comprehensive care for CMC compared to usual care may make little to no difference to child health, functioning, and quality of life at 12 or 24 months (three studies with 404 participants) and we assessed the evidence for the outcomes in this category (child health-related quality of life and functional status) as being of low certainty. For CMC, comprehensive care probably makes little or no difference to parent health, functioning, and quality of life compared to usual care at 12 months (one study with 117 participants) and we assessed the evidence for this outcome as being of moderate certainty. Comprehensive care for CMC compared to usual care may slightly improve child and family satisfaction with, and perceptions of, care and service delivery at 12 months (three studies with 453 participants); however, we assessed the evidence for these outcomes as being of low certainty. For CMC, comprehensive care probably makes little or no difference to the number of healthcare encounters (emergency department visits) and the number of hospitalised days (hospital admissions) compared to usual care at 12 months (three studies with 668 participants), and we assessed the evidence for these outcomes as being of moderate certainty. Three of the included studies (668 participants) reported cost outcomes and had conflicting results, with one study reporting significantly lower healthcare costs at 12 months in the intervention group compared to the control group, one reporting no differences between groups, and the other study reporting a greater increase in total healthcare costs in the intervention group compared to the control group. Overall, comprehensive care may make little or no difference to overall healthcare costs in CMC; however, the methods used to measure total healthcare costs varied across studies and the certainty of the evidence relating to this outcome is low. No studies assessed the costs to the family.

AUTHORS' CONCLUSIONS

The findings of this review should be treated with caution due to the limited amount and quality of the published research that was available to be included. Overall, the certainty of the evidence for the effectiveness of comprehensive care for CMC ranged from low to moderate across outcomes and there is currently insufficient evidence on which to draw strong conclusions. There is a need for more high-quality randomised trials with consistency of the target population and intervention components, methods of reporting outcomes, and follow-up periods, as well as full cost analyses, taking into account both costs to the family and costs to the healthcare system.

Birth Weight and Gestational Age as Modifiers of Rehospitalization after Neonatal Intensive Care Unit Admission

OBJECTIVE

This study aimed to assess interaction effects between gestational age and birth weight on 30-day unplanned hospital readmission following discharge from the neonatal intensive care unit (NICU).

STUDY DESIGN

This is a retrospective study that uses the study site's Children's Hospitals Neonatal Database and electronic health records. Population included patients discharged from a NICU between January 2017 and March 2020. Variables encompassing demographics, gestational age, birth weight, medications, maternal data, and surgical procedures were controlled for. A statistical interaction between gestational age and birth weight was tested for statistical significance.

RESULTS

A total of 2,307 neonates were included, with 7.2% readmitted within 30 days of discharge. Statistical interaction between birth weight and gestational age was statistically significant, indicating that the odds of readmission among low birthweight premature patients increase with increasing gestational age, whereas decrease with increasing gestational age among their normal or high birth weight peers.

CONCLUSION

The effect of gestational age on odds of hospital readmission is dependent on birth weight.

KEY POINTS

· Population included patients discharged from a NICU between January 2017 and March 2020.. · A total of 2,307 neonates were included, with 7.2% readmitted within 30 days of discharge.. · The effect of gestational age on odds of hospital readmission is dependent on birth weight..

Discharge Time of Day and 30-day Hospital Reutilization at an Academic Children's Hospital

BACKGROUND

Pediatric hospital discharge is a complex process. Although morning discharges are operationally preferred, little is known about the association between discharge time of day and discharge outcomes. We assessed whether children discharged from the hospital in the evening have a higher 30-day hospital reutilization rate than those discharged in the morning or afternoon.

METHODS

We conducted a retrospective cohort study on discharges from a children's hospital between July 2016 and December 2019. The cohort was divided into morning, afternoon, and evening discharges. Multivariable modified least-squares regression was used to compare 30-day all-cause hospital reutilization rates between morning, afternoon, and evening discharges while adjusting for demographic and clinical characteristics.

RESULTS

Among 24 994 hospital discharges, 6103 (24.4%) were in the morning, 13 786 (55.2%) were in the afternoon, and 5105 (20.4%) were in the evening. The unadjusted 30-day hospital reutilization rates were 14.1% in children discharged in the morning, 18.2% in children discharged in the afternoon, and 19.3% in children discharged in the evening. The adjusted 30-day hospital reutilization rate was lowest in the morning (6.1%, 95% confidence interval [CI] 4.1%-8.2%), followed by afternoon (9.0%, 95% CI 7.0%-11.0%) and evening discharges (10.1%, 95% CI 8.0%-12.3%). Morning discharge had a significantly lower adjusted 30-day all-cause hospital reutilization rate compared with evening discharge (P < .001), whereas afternoon and evening discharges were not significantly different (P = .06).

CONCLUSIONS

The adjusted 30-day all-cause hospital reutilization rate was higher for evening discharges compared with morning discharges, whereas the rate was not significantly different between afternoon and evening discharges.

Thirty-day readmissions in children with complex chronic conditions

INTRODUCTION

The rate of hospital readmission within 30 days of discharge is a quality indicator in health care. Paediatric patients with complex chronic conditions have high readmission rates. Failure in the transition between hospital and home care could explain this phenomenon.

OBJECTIVES

To estimate the incidence rate of 30-day hospital readmission in paediatric patients with complex chronic conditions, estimate how many are potentially preventable and explore factors associated with readmission.

MATERIALS AND METHOD

Cohort study including hospitalised patients with complex chronic conditions aged 1 month to 18 years. Patients with cancer or with congenital heart disease requiring surgical correction were excluded. The outcomes assessed were 30-day readmission rate and potentially preventable readmissions. We analysed sociodemographic, geographic, clinical and transition to home care characteristics as factors potentially associated with readmission.

RESULTS

The study included 171 hospitalizations, and 28 patients were readmitted within 30 days (16.4%; 95% CI, 11.6%-22.7%). Of the 28 readmissions, 23 were potentially preventable (82.1%; 95% CI, 64.4%-92.1%). Respiratory disease was associated with a higher probability of readmission. There was no association between 30-day readmission and the characteristics of the transition to home care.

CONCLUSIONS

The 30-day readmission rate in patients with complex chronic disease was 16.4%, and 82.1% of readmissions were potentially preventable. Respiratory disease was the only identified risk factor for 30-day readmission.

Machine learning for hospital readmission prediction in pediatric population

BACKGROUND AND OBJECTIVE

Pediatric readmissions are a burden on patients, families, and the healthcare system. In order to identify patients at higher readmission risk, more accurate techniques, as machine learning (ML), could be a good strategy to expand the knowledge in this area. The aim of this study was to develop predictive models capable of identifying children and adolescents at high risk of potentially avoidable 30-day readmission using ML.

METHODS

Retrospective cohort study was carried out with 9,080 patients under 18 years old admitted to a tertiary university hospital. Demographic, clinical, and biochemical data were collected from electronic databases. We randomly divided the dataset into training (75 %) and testing (25 %), applied downsampling, repeated cross-validation with five folds and ten repetitions, and the hyperparameter was optimized of each technique using a grid search via racing with ANOVA models. We applied six ML classification algorithms to build the predictive models, including classification and regression tree (CART), random forest (RF), gradient boosting machine (GBM), extreme gradient boosting (XGBoost), decision tree and logistic regression (LR). The area under the receiver operating curve (AUC), sensitivity, specificity, Youden's J-index and accuracy were used to evaluate the performance of each model.

RESULTS

The avoidable 30-day hospital readmissions rate was 9.5 %. Some algorithms presented similar AUC, both in the dataset training and in the dataset testing, such as XGBoost, RF, GBM and CART. Considering the Youden's J-index, the algorithm that presented the best index was XGBoost with bagging imputation, with AUC of 0.814 (J-index of 0.484). Cancer diagnosis, age, red blood cells, leukocytes, red cell distribution width and sodium levels, elective admission, and multimorbidity were the most important characteristics to classify between readmission and non-readmission groups.

CONCLUSION

Machine learning approaches, especially XGBoost, can predict potentially avoidable 30-day pediatric hospital readmission into tertiary assistance. If implemented in the computer hospital system, our model can help in the early and more accurate identification of patients at readmission risk, targeting health strategic interventions.

An examination of characteristics, social supports, caregiver resilience and hospital readmissions of children with medical complexity

BACKGROUND

Children with medical complexity (CMC) account for 1% of children in the United States. These children experience frequent hospital readmissions, high healthcare costs and poor health outcomes. A link between CMC caregiver social support, resilience and hospital readmissions has never been fully investigated. This study examines the feasibility of a prospective, descriptive, repeated measures research design to characterize CMC and their caregivers, social supports, caregiver resilience and hospital readmissions to inform a larger prospective investigation.

METHODS

Caregivers of CMC with unplanned hospitalizations completed surveys at the index hospitalization and 30 and 60 days after discharge. CMC caregiver and child characteristics, social supports and hospital readmissions were examined using an investigator-developed survey. Resilience was measured using the Resilience Scale-14© (7-Point Likert Scale, score range 14-98), and feasibility was measured by calculating enrolment, attrition, survey completion and item response. Analysis included descriptive statistics and qualitative data visualization.

RESULTS

Of caregivers who were approached for participation, 81.1% consented  and completed 76 surveys. Attrition was 31%. Item response rates were ≥ 90% for all but one item. A total of 62.1% of children had hospital readmissions within 90 days and 37.9% within 30 days. Additionally, 70% of caregivers had home care nursing, but the approved hours were only partially filled. More than 70% of caregiver resilience scores were moderate to high (score range 74-98) and were stable across repeated measures and hospital readmissions. Open-ended question responses revealed the following five categories: All-consuming, Family Reliance, Impact of Covid, Taking Action and Broken System.

CONCLUSIONS

Studying CMC caregiver social supports and resilience using repeated measures is feasible. CMC caregivers reported stressors including coordinating their child's substantial healthcare needs and managing partially filled home care nursing hours. Caregiver resilience remained stable over time, amidst frequent CMC hospital readmissions. Findings can inform future research priorities and power analyses for CMC caregiver resilience.

Identifying the Prevalence and Causes of 30-Day Hospital Readmission in Children: A Case Study from a Tertiary Pediatric Hospital

Introduction

The objectives of this study were to determine the prevalence of unplanned readmissions in the pediatric population within 30 days of discharge, identify the possible reasons behind them, and develop a predictive model for unplanned admissions.

Methods

A retrospective chart review study of 25,211 patients was conducted to identify the prevalence of readmissions occurring within 30 days of discharge from the King Abdullah Specialized Children's Hospital (KASCH) in Riyadh, Saudi Arabia, between Jan 1, 2019, and Dec 31, 2021. The data were collected using the BestCare electronic health records system and analyzed using Jamovi statistical software version 1.6.

Results

Among the 25,211 patients admitted to the hospital during the study period, the prevalence of unplanned readmission within 30 days was 1291 (5.12%). Of the 1291 patients, 1.91% had subsequent unplanned readmissions. In 57.8% of the cases, the cause of the first unplanned readmission was related to the cause of the first admission, and in 90.64% of the cases, the cause of the subsequent unplanned readmission was related to the cause of the first unplanned readmission. The most common reason for the first unplanned readmission was postoperative complications (18.75%), whereas pneumonia (10.81%) was the most common reason for subsequent unplanned readmissions. Most patients with subsequent unplanned readmissions were also found to have either isolated central nervous system pathology or chronic complex medical conditions.

Conclusion

Internationally, the rate of unplanned readmissions in pediatric patients has been estimated to be 6.5% within 30 days, which is comparable to the results of our study (5.12%). Most of the causes of first and subsequent unplanned readmission were found to be related to primary admission. The diagnosis/causes of readmission vary depending on the patient's age. A predictive model for pediatric readmission should be established so that preventive measures can be implemented.

Management of Discharge Instructions for Children With Medical Complexity: A Systematic Review

CONTEXT

Children with medical complexity (CMC) are at risk for adverse outcomes after discharge. Difficulties with comprehension of and adherence to discharge instructions contribute to these errors. Comprehensive reviews of patient-, caregiver-, provider-, and system-level characteristics and interventions associated with discharge instruction comprehension and adherence for CMC are lacking.

OBJECTIVE

To systematically review the literature related to factors associated with comprehension of and adherence to discharge instructions for CMC.

DATA SOURCES

PubMed/Medline, Embase, Cochrane Central Register of Controlled Trials, PsycInfo, Cumulative Index to Nursing and Allied Health Literature, Web of Science (database initiation until March 2023), and OAIster (gray literature) were searched.

STUDY SELECTION

Original studies examining caregiver comprehension of and adherence to discharge instructions for CMC (Patient Medical Complexity Algorithm) were evaluated.

DATA EXTRACTION

Two authors independently screened titles/abstracts and reviewed full-text articles. Two authors extracted data related to study characteristics, methodology, subjects, and results.

RESULTS

Fifty-one studies were included. More than half were qualitative or mixed methods studies. Few interventional studies examined objective outcomes. More than half of studies examined instructions for equipment (eg, tracheostomies). Common issues related to access, care coordination, and stress/anxiety. Facilitators included accounting for family context and using health literacy-informed strategies.

LIMITATIONS

No randomized trials met inclusion criteria. Several groups (eg, oncologic diagnoses, NICU patients) were not examined in this review.

CONCLUSIONS

Multiple factors affect comprehension of and adherence to discharge instructions for CMC. Several areas (eg, appointments, feeding tubes) were understudied. Future work should focus on design of interventions to optimize transitions.

Pediatric Resident Communication of Hospital Discharge Instructions

OBJECTIVE

Suboptimal provider-parent communication contributes to poor parent comprehension of pediatric discharge instructions, which can lead to adverse outcomes. Residency is a critical window to acquire and learn to utilize key communication skills, potentially supported by formal training programs or visual reminders. Few studies have examined resident counseling practices or predictors of counseling quality. Our objectives were to (1) examine pediatric resident counseling practices and (2) determine how formal training and presence of discharge templates with domain-specific prompts are associated with counseling.

METHODS

We conducted a cross-sectional survey of a convenience sample of residents in the American Academy of Pediatrics Section on Pediatric Trainees. Outcomes included resident self-report of frequency of (1) counseling in domains of care and (2) use of health literacy-informed counseling strategies (pictures, demonstration, Teach Back, Show Back) (6-point scales; frequent = often/usually/always). Predictor variables were (1) formal discharge-related training (e.g., lectures) and (2) hospital discharge instruction template with space for individual domains. Logistic regression analyses, utilizing generalized estimating equations when appropriate to account for multiple domains (adjusting for resident gender, postgraduate year), were performed.

KEY RESULTS

Few residents (N = 317) (13.9%) reported formal training. Over 25% of residents infrequently counsel on side effects, diagnosis, and restrictions. Resident reported use of communication strategies was infrequent: drawing pictures (24.1%), demonstration (15.8%), Teach Back (36.8%), Show Back (11.4%). Designated spaces in instruction templates for individual domains were associated with frequent domain-specific counseling (adjusted odds ratio [aOR] 4.1 [95% confidence interval: 3.5-4.8]). Formal training was associated with frequent Teach Back (aOR 2.6 [1.4-5.1]) and Show Back (aOR 2.7 [1.2-6.2]).

CONCLUSIONS

Lack of formal training and designated space for domain-specific instructions are associated with suboptimal counseling at discharge by pediatric residents. Future research should focus on determining the best mechanisms for teaching trainees communication skills and optimizing written instruction templates to support verbal counseling. [HLRP: Health Literacy Research and Practice. 2023;7(4):e178-e186.].

Transitions from hospital to home: A mixed methods study to evaluate pediatric discharges in Uganda

The World Health Organization (WHO) Integrated Management of Childhood Illness (IMCI) guidelines recognize the importance of discharge planning to ensure continuation of care at home and appropriate follow-up. However, insufficient attention has been paid to post discharge planning in many hospitals contributing to poor implementation. To understand the reasons for suboptimal discharge, we evaluated the pediatric discharge process from hospital admission through the transition to care within the community in Ugandan hospitals. This mixed methods prospective study enrolled 92 study participants in three phases: patient journey mapping for 32 admitted children under-5 years of age with suspected or proven infection, discharge process mapping with 24 pediatric healthcare workers, and focus group discussions with 36 primary caregivers and fathers of discharged children. Data were descriptively and thematically analyzed. We found that the typical discharge process is often not centered around the needs of the child and family. Discharge planning often does not begin until immediately prior to discharge and generally does not include caregiver input. Discharge education and counselling are generally limited, rarely involves the father, and does not focus significantly on post-discharge care or follow-up. Delays in the discharge process itself occur at multiple points, including while awaiting a physical discharge order and then following a discharge order, mainly with billing or transportation issues. Poor peri-discharge care is a significant barrier to optimizing health outcomes among children in Uganda. Process improvements including initiation of early discharge planning, improved communication between healthcare workers and caregivers, as well as an increased focus on post-discharge care, are key to ensuring safe transitions from facility-based care to home-based care among children recovering from severe illness.

Factors associated with hospital admission and 30-day readmission for children less than 18 years of age in 2018 in France: a one-year nationwide observational study

BACKGROUND

Nationwide data for children for short-stay hospitalisation (SSH) and associated factors are scarce. This retrospective study of children in France < 18 years of age followed after their birth or birthday in 2018 focused on at least one annual SSH, stay < 1 night or ≥ 1 night, or 30-day readmission ≥ 1 night.

METHODS

Children were selected from the national health data system (SNDS), which includes data on long-term chronic disease (LTD) status with full reimbursement and complementary universal coverage based on low household income (CMUC). Uni and multivariate quasi-Poisson regression were applied for each outcome.

RESULTS

Among 13.211 million children (94.4% population, 51.2% boys), CMUC was identified for 17.5% and at least one LTD for 4% (0-<1 year: 1.5%; 14-<18 year: 5.2%). The most frequent LTDs were pervasive developmental diseases (0.53%), asthma (0.24%), epilepsy (0.17%), and type 1 diabetes (0.15%). At least one SSH was found for 8.8%: SSH < 1 night (4.9%), SSH ≥ 1 night (4.5%), readmission (0.4%). Children with at least one SSH were younger (median 6 vs. 9 years) and more often had CMUC (21%), a LTD (12%), an emergency department (ED) visit (56%), or various primary healthcare visits than all children. Those with a SSH ≥1 night vs. < 1 night were older (median: 9 vs. 4 years). They had the same frequency of LTD (13.4%) but more often an ED visit (78% vs. 42%). Children with readmissions were younger (median 3 years). They had the highest levels of CMUC (29.3%), LTD (34%), EDs in their municipality (35% vs. 29% for the whole population) and ED visits (87%). In adjusted analysis, each outcome was significantly less frequent among girls than boys and more frequent for children with CMUC. LTDs with the largest association with SSH < 1 night were cystic fibrosis, sickle cell diseases (SCD), diabetes type 1, those with SSH ≥1 night type 1 diabetes epilepsy and SCD, and those for readmissions lymphoid leukaemia, malignant neoplasm of the brain, and SCD. Among all SSH admissions of children < 10 years, 25.8% were potentially preventable.

CONCLUSION

Higher SSH and readmission rates were found for children with certain LTD living in low-income households, suggesting the need or increase of specific policy actions and research.

Applying machine learning to consumer wearable data for the early detection of complications after pediatric appendectomy

When children are discharged from the hospital after surgery, their caregivers often rely on subjective assessments (e.g., appetite, fatigue) to monitor postoperative recovery as objective assessment tools are scarce at home. Such imprecise and one-dimensional evaluations can result in unwarranted emergency department visits or delayed care. To address this gap in postoperative monitoring, we evaluated the ability of a consumer-grade wearable device, Fitbit, which records multimodal data about daily physical activity, heart rate, and sleep, in detecting abnormal recovery early in children recovering after appendectomy. One hundred and sixty-two children, ages 3-17 years old, who underwent an appendectomy (86 complicated and 76 simple cases of appendicitis) wore a Fitbit device on their wrist for 21 days postoperatively. Abnormal recovery events (i.e., abnormal symptoms or confirmed postoperative complications) that arose during this period were gathered from medical records and patient reports. Fitbit-derived measures, as well as demographic and clinical characteristics, were used to train machine learning models to retrospectively detect abnormal recovery in the two days leading up to the event for patients with complicated and simple appendicitis. A balanced random forest classifier accurately detected 83% of these abnormal recovery days in complicated appendicitis and 70% of abnormal recovery days in simple appendicitis prior to the true report of a symptom/complication. These results support the development of machine learning algorithms to predict onset of abnormal symptoms and complications in children undergoing surgery, and the use of consumer wearables as monitoring tools for early detection of postoperative events.

Causes & risk factors for unscheduled readmissions in the paediatric ward of a major public hospital

Background & objectives

Readmissions are often considered as an indicator of poor quality of care during previous hospitalization, although many of these are unavoidable or unrelated to the past admission. The identification of high-risk cases for readmissions and appropriate interventions will help not only reduce the hospital burden but also to establish the credibility of the hospital. So this study aimed to determine the readmission percentage in the paediatric wards of a tertiary care hospital and to identify the reasons and risk factors that can help minimize preventable re-hospitalizations.

Methods

This prospective study from a public hospital included 563 hospitalized children, classified as first admission or readmissions. Readmissions were defined as one or more hospitalizations within preceding six months, excluding scheduled admissions for investigations or treatment. Reason-wise, the readmissions were classified into various categories, based on the opinion of three paediatricians.

Results

The percentage of children getting readmitted within six, three and one month time from the index admission was 18.8, 11.1 and 6.4 per cent, respectively. Among readmissions, 61.2 per cent were disease-related, 16.5 per cent unrelated, 15.5 per cent patient-related, 3.8 per cent medication/procedure-related and 2.9 per cent physician-related causes. Patient- and physician-related causes were deemed preventable, contributing to 18.4 per cent. The proximity of residence, undernutrition, poor education of the caretaker and non-infectious diseases were associated with increased risk of readmission.

Interpretation & conclusions

The findings of this study suggest that readmissions pose a substantial burden on the hospital services. The primary disease process and certain sociodemographic factors are the major determinants for the increased risk of readmissions among paediatric patients.

Development and Validation of an Integrated Suite of Prediction Models for All-Cause 30-Day Readmissions of Children and Adolescents Aged 0 to 18 Years

IMPORTANCE

Readmission is often considered a hospital quality measure, yet no validated risk prediction models exist for children.

OBJECTIVE

To develop and validate a tool identifying patients before hospital discharge who are at risk for subsequent readmission, applicable to all ages.

DESIGN, SETTING, AND PARTICIPANTS

This population-based prognostic analysis used electronic health record-derived data from a freestanding children's hospital from January 1, 2016, to December 31, 2019. All-cause 30-day readmission was modeled using 3 years of discharge data. Data were analyzed from June 1 to November 30, 2021.

MAIN OUTCOMES AND MEASURES

Three models were derived as a complementary suite to include (1) children 6 months or older with 1 or more prior hospitalizations within the last 6 months (recent admission model [RAM]), (2) children 6 months or older with no prior hospitalizations in the last 6 months (new admission model [NAM]), and (3) children younger than 6 months (young infant model [YIM]). Generalized mixed linear models were used for all analyses. Models were validated using an additional year of discharges.

RESULTS

The derivation set contained 29 988 patients with 48 019 hospitalizations; 50.1% of these admissions were for children younger than 5 years and 54.7% were boys. In the derivation set, 4878 of 13 490 admissions (36.2%) in the RAM cohort, 2044 of 27 531 (7.4%) in the NAM cohort, and 855 of 6998 (12.2%) in the YIM cohort were followed within 30 days by a readmission. In the RAM cohort, prior utilization, current or prior procedures indicative of severity of illness (transfusion, ventilation, or central venous catheter), commercial insurance, and prolonged length of stay (LOS) were associated with readmission. In the NAM cohort, procedures, prolonged LOS, and emergency department visit in the past 6 months were associated with readmission. In the YIM cohort, LOS, prior visits, and critical procedures were associated with readmission. The area under the receiver operating characteristics curve was 83.1 (95% CI, 82.4-83.8) for the RAM cohort, 76.1 (95% CI, 75.0-77.2) for the NAM cohort, and 80.3 (95% CI, 78.8-81.9) for the YIM cohort.

CONCLUSIONS AND RELEVANCE

In this prognostic study, the suite of 3 prediction models had acceptable to excellent discrimination for children. These models may allow future improvements in tailored discharge preparedness to prevent high-risk readmissions.

Hospital-Level Neighborhood Opportunity and Rehospitalization for Common Diagnoses at US Children's Hospitals

OBJECTIVE

Neighborhood conditions influence child health outcomes, but data examining association between local factors and hospital utilization are lacking. We determined if hospitals' mix of patients by neighborhood opportunity correlates with rehospitalization for common diagnoses at US children's hospitals.

METHODS

We analyzed all discharges in 2018 for children ≤18 years at 47 children's hospitals for 14 common diagnoses. The exposure was hospital-level mean neighborhood opportunity - measured by Child Opportunity Index (COI) - for each diagnosis. The outcome was same-cause rehospitalization within 365 days. We measured association via Pearson correlation coefficient. For diagnoses with significant associations, we also examined shorter rehospitalization time windows and compared unadjusted and COI-adjusted rehospitalization rates.

RESULTS

There were 256,871 discharges included. Hospital-level COI ranged from 17th to 70th percentile nationally. Hospitals serving lower COI neighborhoods had more frequent rehospitalization for asthma (ρ -0.34 [95% confidence interval -0.57, -0.06]) and diabetes (ρ -0.33 [-0.56, -0.04]), but fewer primary mental health rehospitalizations (ρ 0.47 [0.21, 0.67]). There was no association for 11 other diagnoses. Secondary timepoint analysis revealed increasing correlation over time, with differences by diagnosis. Adjustment for hospital-level COI resulted in 26%, 32%, and 45% of hospitals changing >1 decile in rehospitalization rank order for diabetes, asthma, and mental health diagnoses, respectively.

CONCLUSIONS

Children's hospitals vary widely in their mix of neighborhoods served. Asthma, diabetes, and mental health rehospitalization rates correlate with COI, suggesting that neighborhood factors may influence outcome disparities for these conditions. Hospital outcomes may be affected by neighborhood opportunity, which has implications for benchmarking.

Hospital Discharge Instructions: Characteristics, Accessibility, and National Guideline Adherence

OBJECTIVES

The content of pediatric hospital discharge instructions is highly variable. This study aimed to describe the characteristics, accessibility per patient literacy level and language, and national guideline adherence of pediatric hospital discharge instructions.

METHODS

This retrospective study assessed discharge instructions at a tertiary children's hospital. Patient and instruction characteristics, including patient health literacy level, grade level of instructions, patient language preference, and language of instructions were collected via chart review and electronic medical record query. Standard admission processes assessed health literacy via Brief Health Literacy Screening. The association between demographic and clinical characteristics and adherence to Solutions for Patient Safety guidelines was analyzed by using unadjusted and adjusted analysis methods.

RESULTS

Of 240 discharge instructions, 25% were missing at least 1 recommended content area: signs of worsening, where to seek help, or medication reconciliation. A patient health literacy deficit was identified in 15%; the mean grade level of instructions was 10.1. Limited English proficiency was reported among 17% one quarter of whom received language concordant instructions. Use of discharge instruction templates and discharge services were associated with improved guideline adherence (P <.001). Almost one-half of the study population had a complex medical history, which was associated with decreased guideline adherence (P = .04).

CONCLUSIONS

One-quarter of discharge instructions for this predominantly medically complex population failed to meet national standards. Accessibility was often limited by the reading grade level or discordant language of instructions. Templates may be a valuable tool for improving discharge instruction content, accessibility, and adherence to national guidelines.

Performance Characteristics of a Machine-Learning Tool to Predict 7-Day Hospital Readmissions

OBJECTIVES

To develop an institutional machine-learning (ML) tool that utilizes demographic, socioeconomic, and medical information to stratify risk for 7-day readmission after hospital discharge; assess the validity and reliability of the tool; and demonstrate its discriminatory capacity to predict readmissions.

PATIENTS AND METHODS

We performed a combined single-center, cross-sectional, and prospective study of pediatric hospitalists assessing the face and content validity of the developed readmission ML tool. The cross-sectional analyses used data from questionnaire Likert scale responses regarding face and content validity. Prospectively, we compared the discriminatory capacity of provider readmission risk versus the ML tool to predict 7-day readmissions assessed via area under the receiver operating characteristic curve analyses.

RESULTS

Overall, 80% (15 of 20) of hospitalists reported being somewhat to very confident with their ability to accurately predict readmission risk; 53% reported that an ML tool would influence clinical decision-making (face validity). The ML tool variable exhibiting the highest content validity was history of previous 7-day readmission. Prospective provider assessment of risk of 413 discharges showed minimal agreement with the ML tool (κ = 0.104 [95% confidence interval 0.028-0.179]). Both provider gestalt and ML calculations poorly predicted 7-day readmissions (area under the receiver operating characteristic curve: 0.67 vs 0.52; P = .11).

CONCLUSIONS

An ML tool for predicting 7-day hospital readmissions after discharge from the general pediatric ward had limited face and content validity among pediatric hospitalists. Both provider and ML-based determinations of readmission risk were of limited discriminatory value. Before incorporating similar tools into real-time discharge planning, model calibration efforts are needed.

Variation in Condition-Specific Readmission Rates Across US Children's Hospitals

OBJECTIVE

Despite extensive efforts, overall readmission rates at US children's hospitals have not materially declined over the past decade, raising questions about how to direct future efforts. Using measures of prevalence and performance variation we describe readmission rates by condition and identify priority conditions for future intervention.

METHODS

Retrospective cohort study of 49 US children's hospitals in the Pediatric Health Information System in 2017. Conditions were classified using All Patients Refined Diagnosis Related Groups. 30-day unadjusted and risk-adjusted readmission rates were calculated for each hospital/condition using the Pediatric All Cause Readmission measure. We ranked the highest volume conditions by rate variation (RV, interquartile range divided by the median) for each condition across hospitals.

RESULTS

The sample included 811,434 index hospitalizations with 50,196 (6.2%) 30-day readmissions. The RV across hospitals/conditions was between 0 and 2.8 (median = 0.7). Common reasons for admission had low RVs across hospitals, for example, bronchiolitis (readmission rate = 5.6%, RV = 0.4), seizure (readmission rate = 6.6%, RV = 0.3), and asthma (readmission rate = 3.1%, RV = 0.4). We identified 33 conditions with high variation in readmission rates across hospitals, which accounted for 18% of all discharges and 11% of all pediatric readmissions. These conditions may serve as candidates for future readmission reduction activities.

CONCLUSIONS

Many common childhood conditions have little variation in readmission rates across children's hospitals, suggesting limited future improvement opportunities. Conditions with high rate variation may provide opportunities for quality improvement; however, these conditions account for a relatively small share of total discharges suggesting modest potential impacts on national rates.

Association of Neighborhood Resources and Race and Ethnicity With Readmissions for Diabetic Ketoacidosis at US Children's Hospitals

Importance

The Child Opportunity Index 2.0 (COI) assesses neighborhood resources and conditions that influence health. It is unclear whether the COI scores are associated with health outcomes by race and ethnicity among children with type 1 diabetes (T1D).

Objective

To determine whether COI categories are associated with diabetes-related outcomes by race and ethnicity, including readmissions for diabetic ketoacidosis (DKA) and co-occurring acute kidney injury (AKI) or cerebral edema (CE).

Design, Setting, and Participants

This cross-sectional study included children discharged with a primary diagnosis of T1D with DKA between January 1, 2009, and December 31, 2018. Merged data were obtained from the Pediatric Health Information System and COI. Participants included children and adolescents younger than 21 years with an encounter for DKA. Data were analyzed from April 29, 2021, to January 5, 2022.

Exposures

Neighborhood opportunity, measured with the COI as an ordered, categorical score (where a higher score indicates more opportunity), and race and ethnicity.

Main Outcomes and Measures

The primary outcome was readmission for DKA within 30 and 365 days from an index visit. Secondary outcomes included the proportion of encounters with AKI or CE. Mixed-effects logistic regression was used to generate probabilities of readmission, AKI, and CE for each quintile of COI category by race and ethnicity.

Results

A total of 72 726 patient encounters were identified, including 38 924 (53.5%) for girls; the median patient age was 13 (IQR, 9-15) years. In terms of race and ethnicity, 600 (0.8%) of the encounters occurred in Asian patients, 9969 (13.7%) occurred in Hispanic patients, 16 876 (23.2%) occurred in non-Hispanic Black (hereinafter Black) patients, 40 129 (55.2%) occurred in non-Hispanic White (hereinafter White) patients, and 5152 (7.1%) occurred in patients of other race or ethnicity. The probability of readmission within 365 days was significantly higher among Black children with a very low COI category compared with Hispanic children (risk difference, 7.8 [95% CI, 6.0-9.6] percentage points) and White children (risk difference, 7.5 [95% CI, 5.9-9.1] percentage points) at the same COI category. Similar differences were seen for children with very high COI scores and across racial groups. The COI category was not associated with AKI or CE. However, race and ethnicity constituted a significant factor associated with AKI across all COI categories. The probability of AKI was 6.8% among Black children compared with 4.2% among Hispanic children (risk difference, 2.5 [95% CI, 1.7-3.3] percentage points) and 4.8% among White children (risk difference, 2.0 [95% CI, 1.3-2.6] percentage points).

Conclusions and Relevance

These results suggest that Black children with T1D experience disparities in health outcomes compared with other racial and ethnic groups with similar COI categories. Measures to prevent readmissions for DKA should include interventions that target racial disparities and community factors.

Disease Severity and Risk Factors of 30-Day Hospital Readmission in Pediatric Hospitalizations for Pneumonia

Pneumonia is the leading cause of hospitalization in pediatric patients. Disease severity greatly influences pneumonia progression and adverse health outcomes such as hospital readmission. Hospital readmissions have become a measure of healthcare quality to reduce excess expenditures. The aim of this study was to examine 30-day all-cause readmission rates and evaluate the association between pneumonia severity and readmission among pediatric pneumonia hospitalizations. Using 2018 Nationwide Readmissions Database (NRD), we conducted a cross-sectional study of pediatric hospitalizations for pneumonia. Pneumonia severity was defined by the presence of respiratory failure, sepsis, mechanical ventilation, dependence on long-term supplemental oxygen, and/or respiratory intubation. Outcomes of interest were 30-day all-cause readmission, length of stay, and cost. The rate of 30-day readmission for the total sample was 5.9%, 4.7% for non-severe pneumonia, and 8.7% for severe pneumonia (p < 0.01). Among those who were readmitted, hospitalizations for severe pneumonia had a longer length of stay (6.5 vs. 5.4 days, p < 0.01) and higher daily cost (USD 3246 vs. USD 2679, p < 0.01) than admissions for non-severe pneumonia. Factors associated with 30-day readmission were pneumonia severity, immunosuppressive conditions, length of stay, and hospital case volume. To reduce potentially preventable readmissions, clinical interventions to improve the disease course and hospital system interventions are necessary.

Nurse’s performance in the hospital discharge process of children with chronic disease

ABSTRACT Objective: To analyze the nurse’s performance in the hospital discharge process of children with chronic disease. Method: Qualitative research conducted from May to August/2019 with ten nurses working in a pediatric unit of a public hospital. The data, collected through semi-structured interviews, were submitted to inductive thematic analysis. Results: In the preparation for hospital discharge, nurses recognize health education as their attribution, valuing family knowledge in the training regarding home care. Nevertheless, their practice is weakened by the little articulation among the multiprofessional team, reduced nursing sizing and disarticulation in the health care network. Conclusion: There is a paradox between the report and the practice of the hospital discharge process accomplished by nurses. Although they have theoretical knowledge, their work process is influenced by the disarticulated way in which the multiprofessional team interacts, and the conditions provided by the institution to work in the preparation for hospital discharge of these children.

Atuação da enfermeira no processo de alta hospitalar de criança com doença crônica

RESUMO Objetivo: Analisar a atuação da enfermeira no processo de alta hospitalar de crianças com doença crônica. Método: Pesquisa qualitativa realizada de maio a agosto/2019 com dez enfermeiras de unidade pediátrica de hospital público. Os dados, coletados por meio de entrevistas semiestruturadas, foram submetidos à análise temática indutiva. Resultados: No preparo para alta hospitalar, as enfermeiras reconhecem como sua atribuição a educação em saúde, valorizando o saber familiar na capacitação quanto aos cuidados domiciliares. Entretanto, sua prática é fragilizada pela pouca articulação entre a equipe multiprofissional, dimensionamento de enfermagem reduzido e desarticulação na rede de atenção à saúde. Conclusão: Evidencia-se paradoxo entre o relato e a prática do processo de alta hospitalar efetivado pelas enfermeiras. Embora possuam conhecimento teórico, seu processo de trabalho sofre influência do modo desarticulado como a equipe multiprofissional interage e das condições disponibilizadas pela instituição para atuarem no preparo para alta hospitalar dessas crianças.

Age- and Diagnosis-Based Trends for Unplanned Pediatric Rehospitalizations in the United States

Background and objectives: Hospital readmission rate helps to highlight the effectiveness of post-discharge care. There remains a paucity of plausible age-based categorization especially for ages below one year for hospital readmission rates.

Methods: Data from the 2017 Healthcare Cost and Utilization Project National Readmissions Database was analyzed for ages 0-18 years. Logistic regression analysis was performed to identify predictors for unplanned early readmissions. 

Results: We identified 5,529,389 inpatient pediatric encounters which were further divided into age group cohorts. The overall rate of readmissions was identified at 3.2%. Beyond infancy, the readmission rate was found to be 6.7%. Across all age groups, the major predictors of unplanned readmission were cancers, diseases affecting transplant recipients and sickle cell patients. It was determined that reflux, milk protein allergy, hepatitis and inflammatory bowel diseases were significant diagnoses leading to readmission. Anxiety, depression and suicidal ideation depicted higher readmission rates in those older than 13 years. Across ages one to four years, dehydration, asthma and bronchiolitis were negative predictors of unplanned readmission. 

Conclusions: Thirty-day unplanned readmissions remain a problem leading to billions of taxpayer dollars lost per annum. Effective strategies for mandatory outpatient follow-up may help the financial aspect of care while also enhancing the quality of care.

Development of Prediction Models for Unplanned Hospital Readmission within 30 Days Based on Common Data Model: A Feasibility Study

Background  Unplanned hospital readmission after discharge reflects low satisfaction and reliability in care and the possibility of potential medical accidents, and is thus indicative of the quality of patient care and the appropriateness of discharge plans.

Objectives  The purpose of this study was to develop and validate prediction models for all-cause unplanned hospital readmissions within 30 days of discharge, based on a common data model (CDM), which can be applied to multiple institutions for efficient readmission management.

Methods  Retrospective patient-level prediction models were developed based on clinical data of two tertiary general university hospitals converted into a CDM developed by Observational Medical Outcomes Partnership. Machine learning classification models based on the LASSO logistic regression model, decision tree, AdaBoost, random forest, and gradient boosting machine (GBM) were developed and tested by manipulating a set of CDM variables. An internal 10-fold cross-validation was performed on the target data of the model. To examine its transportability, the model was externally validated. Verification indicators helped evaluate the model performance based on the values of area under the curve (AUC).

Results  Based on the time interval for outcome prediction, it was confirmed that the prediction model targeting the variables obtained within 30 days of discharge was the most efficient (AUC of 82.75). The external validation showed that the model is transferable, with the combination of various clinical covariates. Above all, the prediction model based on the GBM showed the highest AUC performance of 84.14 ± 0.015 for the Seoul National University Hospital cohort, yielding in 78.33 in external validation.

Conclusions  This study showed that readmission prediction models developed using machine-learning techniques and CDM can be a useful tool to compare two hospitals in terms of patient-data features.

Targeted Clinical Interventions for Reducing Pediatric Readmissions

BACKGROUND

In this interventional study, we addressed the selection and application of clinical interventions on pediatric patients identified as at risk by a predictive model for readmissions.

METHODS

A predictive model for readmissions was implemented, and a team of providers expanded corresponding clinical interventions for at-risk patients at a freestanding children's hospital. Interventions encompassed social determinants of health, outpatient care, medication reconciliation, inpatient and discharge planning, and postdischarge calls and/or follow-up. Statistical process control charts were used to compare readmission rates for the 3-year period preceding adoption of the model and clinical interventions with those for the 2-year period after adoption of the model and clinical interventions. Potential financial savings were estimated by using national estimates of the cost of pediatric inpatient readmissions.

RESULTS

The 30-day all-cause readmission rates during the periods before and after predictive modeling (and corresponding 95% confidence intervals [CI]) were 12.5% (95% CI: 12.2%-12.8%) and 11.1% (95% CI: 10.8%-11.5%), respectively. More modest but similar improvements were observed for 7-day readmissions. Statistical process control charts indicated nonrandom reductions in readmissions after predictive model adoption. The national estimate of the cost of pediatric readmissions indicates an associated health care savings due to reduced 30-day readmission during the 2-year predictive modeling period at $2 673 264 (95% CI: $2 612 431-$2 735 364).

CONCLUSIONS

A combination of predictive modeling and targeted clinical interventions to improve the management of pediatric patients at high risk for readmission was successful in reducing the rate of readmission and reducing overall health care costs. The continued prioritization of patients with potentially modifiable outcomes is key to improving patient outcomes.

Perspectives of Parents and Providers on Reasons for Mental Health Readmissions: A Content Analysis Study

Pediatric hospitalizations for mental health conditions are rapidly increasing, with readmission rates for mental health conditions surpassing those for non-mental health conditions. The objective of this study was to identify reasons for pediatric mental health readmissions from the perspectives of parents and providers. We performed a retrospective content analysis of surveys administered to parents and providers of patients with a 14-day readmission to an inpatient pediatric psychiatry unit between 5/2017 and 8/2018. Open-ended survey items assessed parent and provider perceptions of readmission reasons. We used deductive coding to categorize survey responses into an a priori coding scheme based on prior research. We used inductive coding to identify and categorize responses that did not fit into the a priori coding scheme. All data were recoded using the revised schema and reliability of the coding process was assessed using kappa statistics and consensus building. We had completed survey responses from 89 (64%) of 138 readmission encounters (56 parent surveys; 61 provider surveys). The top three readmission reasons that we identified from parent responses were: discordant inpatient stay expectations with providers (41%), discharge hesitancy (34%), and treatment plan failure (13%). Among providers, the top readmission reasons that we identified were: access to outpatient care (30%), treatment adherence (13%), and a challenging home (11%) and social environment (11%). We identified inpatient stay expectations, discharge hesitancy, and suboptimal access to outpatient care as the most prominent reasons for mental health readmissions, which provide targets for future quality improvement efforts.

Variables Prevalent Among Early Unplanned Readmissions in Infants Following Congenital Heart Surgery

Medically complex children including infants undergoing cardiac surgery are at increased risk for hospital readmissions. Investigation of this population may reveal opportunities to optimize systems and coordination of care. A retrospective study of all infants undergoing cardiac surgery from 2015 through 2016 at a large tertiary institution who were readmitted within 1 year of discharge from cardiac surgical hospitalization was performed. Data specific to patient characteristics, surgical hospitalization, and readmission hospitalization are described. Unplanned readmissions within 1 year of hospital discharge were analyzed with Cox proportional hazard regression to identify factors associated with increased hazard for earlier unplanned readmission. Comparable to previous reports, 12% (78/658) of all surgical hospitalizations were associated with unplanned readmission within 30 days. Infectious etiology, followed by cardiac and gastrointestinal problems, was the most common reasons for unplanned 30-day readmission. Unplanned readmissions within 2 weeks of discharge were multifactorial and less commonly related to cardiac or surgical care. Primary nasogastric tube feeding at the time of discharge was the only significant risk factor for earlier unplanned readmission (p = 0.032) on multivariable analysis. Increased care coordination with particular attention to feeding and comorbidity management may be future targets to effectively mitigate readmissions and improve quality of care in this population.

Preventability of 7-Day Versus 30-Day Readmissions at an Academic Children's Hospital

BACKGROUND AND OBJECTIVES

The 30-day readmission rate is a common quality metric used by Medicare for adult patients. However, studies in pediatrics have shown lower readmission rates and potentially less preventability. Therefore, some question the utility of the 30-day readmission time frame in pediatrics. Our objective was to describe the characteristics of patients readmitted within 30 days of discharge over a 1-year period and determine the preventability of readmissions occurring 0 to 7 vs 8 to 30 days after discharge from a pediatric hospitalist service at an academic children's hospital.

METHODS

Retrospective chart review and hospital administrative data were used to gather medical characteristics, demographics, and process-level metrics for readmitted patients between July 1, 2015, and June 30, 2016. All readmissions were reviewed by 2 senior authors and assigned a preventability category. Subgroup analysis comparing preventability in 0-to-7- and 8-to-30-day readmissions groups was performed. Qualitative thematic analysis was performed on readmissions deemed preventable.

RESULTS

Of 1523 discharges that occurred during the study period, 49 patients, with 65 distinct readmission encounters, were readmitted for an overall 30-day readmission rate of 4.3% (65 of 1523). Twenty-eight percent (9 of 32) of readmissions within 7 days of discharge and 12.1% (4 of 33) occurring 8 to 30 days after discharge were deemed potentially preventable (P = .13). Combined, the 30-day preventable readmission rate was 20% (13 of 65).

CONCLUSIONS

We identified a possible association between preventability and time to readmission. If confirmed by larger studies, the 7-day, rather than 30-day, time frame may represent a better quality metric for readmitted pediatric patients.

A Quality Improvement Initiative to Improve Discharge Timeliness and Documentation

Introduction:

Discharge communication is critical for the continuity of patient care. However, discharge summaries are often not available in time for follow-up visits, and the content is inconsistent. We aimed to decrease the average time to discharge summary completion by 25%, reduce deficiencies (information errors) by 50%, and increase discharge summary template use to >80% in 6 months.

Methods:

A pediatric interprofessional team used quality improvement methods to identify barriers and implement interventions, including discharge summary completion time expectation, electronic health record discharge summary template changes addressing gaps, and training. Notable changes to the template included embedded writing tips to guide writers and specific template choices for common diagnoses to standardize content. The primary outcome measure was the mean discharge summary completion time. Secondary measures were the percentage of discharge summaries with deficiencies and the rate of template use.

Results:

After interventions, the mean discharge summary completion time decreased by 70% (from 71.5 to 21.8 hours). Discharge summary deficiencies decreased 44% (from 4.5% to 2.5%), and template use increased from 62% to 97%.

Conclusion:

Quality improvement methods and a newly designed electronic health record-discharge summary template were used to dramatically improve discharge summary timeliness and standardize content to streamline continuity of care.

Trends in Length of Stay and Readmissions in Children's Hospitals

BACKGROUND AND OBJECTIVES

Patient complexity at US children's hospitals is increasing. Hospitals experience concurrent pressure to reduce length of stay (LOS) and readmissions, yet little is known about how these common measures of resource use and quality have changed over time. Our aim was to examine temporal trends in medical complexity, hospital LOS, and readmissions across a sample of US children's hospitals.

METHODS

Retrospective cohort study of hospitalized patients from 42 children's hospitals in the Pediatric Health Information System from 2013 to 2017. After excluding deaths, healthy newborns, obstetric care, and low volume service lines, we analyzed trends in medical complexity, LOS, and 14-day all-cause readmissions using generalized linear mixed effects models, adjusting for changes in patient factors and case-mix.

RESULTS

Between 2013 and 2017, a total of 3 355 815 discharges were included. Over time, the mean case-mix index and the proportion of hospitalized patients with complex chronic conditions or receiving intensive care increased (P < .001 for all). In adjusted analyses, mean LOS declined 3% (61.1 hours versus 59.3 hours from 2013 to 2017, P < .001), whereas 14-day readmissions were unchanged (7.0% vs 6.9%; P = .03). Reductions in adjusted LOS were noted in both medical and surgical service lines (3.6% and 2.0% decline, respectively; P < .001).

CONCLUSIONS

Across US children's hospitals, adjusted LOS declined whereas readmissions remained stable, suggesting that children's hospitals are providing more efficient care for an increasingly complex patient population.

Predictors of hospital readmission in infants less than 3 months old

AIM

To examine rates and predictors of 7-day readmission in infants hospitalised before 3 months of age with infectious and non-infectious conditions.

METHODS

Retrospective population-based data-linkage study of 121 854 infants from a 5-year metropolitan birth cohort (2008-2012). Cox proportional hazard models were used to examine associations between infant and maternal factors with 7-day readmission.

RESULTS

A total of 11 669 (9.6%) infants were hospitalised at least once by 3 months of age (median 23 days old, 56% male) with 12 602 total index hospitalisations. Infection-related conditions accounted for 29.4% (n = 3705). Readmission within 7 days occurred after 4.8% of all index hospitalisations and 5.4% of infection-related hospitalisations. Age ≤21 days was the strongest readmission risk factor (hazard ratio 7.7 (95% confidence interval 4.7-12.7) compared to infants 61-90 days old). Other risk factors included shorter index hospitalisations, younger maternal age and multi-gravidity.

CONCLUSION

Hospitalisations and readmissions occur for many young infants. Risk factors for readmission should inform risk-based management guidelines.

Children's Opioid Use at Home After Laparoscopic Appendectomy

BACKGROUND

To combat the opioid epidemic, prescribers need accurate information about pediatric home opioid requirements to manage acute pain after surgery. Current opioid use estimates come from retrospective surveys; this study used medication adherence technology (eCAP) to track home opioid use.

PURPOSE

To describe children's pain treatment at home after laparoscopic appendectomy, and to compare self-reported opioid analgesic use to eCAP data and counts of returned pills.

DESIGN

Prospective exploratory and descriptive study METHODS: A convenience sample of 96 patients, 10-17 years of age, from a single urban nonprofit children's hospital consented to self-report pain treatment in 14-day diaries and use eCAP to monitor prescribed opioid use at home after laparoscopic appendectomy.

RESULTS

Patients were prescribed 5-45 opioid-containing pills (mean ± standard deviation 15 ± 7.2). Of 749 opioid-containing pills prescribed to 49 patients who returned data, 689 pills were dispensed, 167.5 were used for the reason prescribed, 488 were returned to families for disposal, and 53.5 were missing. The majority of the 49 patients were opioid naïve (72%), Caucasian (64%), and male (56%), with a mean age of 14 years. Patients used 6.6 ± 6.3 opioid-containing pills by pill count and 5.6 ± 5.1 by self-report, a significant difference (p = .004). Unreported eCAP-enabled pill bottle openings typically occurred on weekends.

CONCLUSION

Medication adherence technology (eCAP) is a more rigorous method than self-report to estimate opioid needs and detect early opioid misuse. Additional rigorously designed studies of postoperative opioid use are needed to guide opioid prescribing.

Children's Pain at Home After Laparoscopic Appendectomy

BACKGROUND

Hospitalized children experience moderate-to-severe pain after laparoscopic appendectomy, but knowledge of children's pain experiences after discharge home is limited. Accurate pain assessments are needed to guide appropriate pain treatment.

AIMS

To describe children's pain at home after laparoscopic appendectomy.

DESIGN

Prospective exploratory and descriptive METHODS: A convenience sample of 100 patients, aged 10-17 years, who spoke or wrote in English or Spanish, volunteered to complete 14-day pain diaries at home after laparoscopic appendectomy. Visual analytic techniques were used to analyze patterns of pain experiences.

RESULTS

Diaries were returned by 45 patients/parents, the majority of whom were White (64%), male (56%), adolescents (mean age 14 years) with no previous surgical history (70%), and whose appendix was inflamed (87%) but not perforated. More than 50% reported severe pain (4 or 5 on a 0-5 scale) on the first full day home after laparoscopic appendectomy. On day 7, 40% reported pain and on day 14, 16% were still reporting pain. Only rarely were pain scores not clinically significantly lower 1 hour after pain treatment, regardless of treatment type (e.g., nondrug, nonopioid, opioid). Reported pain intensity steadily decreased over time as did frequency of recorded pain scores.

CONCLUSION

Adolescents experience severe pain at home after laparoscopic appendectomy and some experience pain for 7 to 14 days after hospital discharge. Visual analytics better represent the dynamics of pain experiences than measures of central tendency.

Readmissions Following Hospitalization for Infection in Children With or Without Medical Complexity

OBJECTIVE

To describe the prevalence and characteristics of infection-related readmissions in children and to identify opportunities for readmission reduction and estimate associated cost savings.

STUDY DESIGN

Retrospective analysis of 380,067 nationally representative index hospitalizations for children using the 2014 Nationwide Readmissions Database. We compared 30-day, all-cause unplanned readmissions and costs across 22 infection categories. We used the Inpatient Essentials database to measure hospital-level readmission rates and to establish readmission benchmarks for individual infections. We then estimated the number of readmissions avoided and costs saved if hospitals achieved the 10th percentile of hospitals' readmission rates (ie, readmission benchmark). All analyses were stratified by the presence/absence of a complex chronic condition (CCC).

RESULTS

The overall 30-day readmission rate was 4.9%. Readmission rates varied substantially across infections and by presence/absence of a CCC (CCC: range, 0%-21.6%; no CCC: range, 1.5%-8.6%). Approximately 42.6% of readmissions (n = 3,576) for children with a CCC and 54.7% of readmissions (n = 5,507) for children without a CCC could have been potentially avoided if hospitals achieved infection-specific benchmark readmission rates, which could result in an estimated savings of $70.8 million and $44.5 million, respectively. Bronchiolitis, pneumonia, and upper respiratory tract infections were among infections with the greatest number of potentially avoidable readmissions and cost savings for children with and without a CCC.

CONCLUSION

Readmissions following hospitalizations for infection in children vary significantly by infection type. To improve hospital resource use for infections, future preventative measures may prioritize children with complex chronic conditions and those with specific diagnoses (eg, respiratory illnesses).

The risks, reasons, and costs for 30- and 90-day readmissions after fusion surgery for adolescent idiopathic scoliosis

OBJECTIVE

With the continued evolution of bundled payment plans, there has been a greater focus within orthopedic surgery on quality metrics up to 90 days of care. Although the Centers for Medicare and Medicaid Services does not currently penalize hospitals based on their pediatric readmission rates, it is important to understand the drivers for unplanned readmission to improve the quality of care and reduce costs.

METHODS

The National Readmission Database provides a nationally representative sample of all discharges from US hospitals and allows follow-up across hospitals up to 1 calendar year. Adolescents (age 10-18 years) who underwent idiopathic scoliosis surgery from 2012 to 2015 were included. Patients were separated into those with and those without readmission within 30 days or between 31 and 90 days. Demographics, operative conditions, hospital factors, and surgical outcomes were compared using the chi-square test and t-test. Independent predictors for readmissions were identified using stepwise multivariate logistic regression.

RESULTS

A total of 30,677 patients underwent adolescent idiopathic scoliosis surgery from 2012 to 2015. The rates of 30- and 90-day readmissions were 2.9% and 1.4%, respectively. The mean costs associated with the index admission and 30- and 90-day readmissions were $60,680, $23,567, and $16,916, respectively. Common risk factors for readmissions included length of stay > 5 days, obesity, neurological disorders, and chronic use of antiplatelets or anticoagulants. The index admission complications associated with readmissions were unintended durotomy, syndrome of inappropriate antidiuretic hormone, and superior mesenteric artery syndrome. Hospital factors, discharge disposition, and operative conditions appeared to be less important for readmission risk. The top reasons for 30-day and 90-day readmissions were wound infection (34.7%) and implant complications (17.3%), respectively. Readmissions requiring a reoperation were significantly higher for those that occurred between 31 and 90 days after the index readmission.

CONCLUSIONS

Readmission rates were low for both 30- and 90-day readmissions for adolescent idiopathic scoliosis surgery patients. Nevertheless, readmissions are costly and appear to be associated with potentially modifiable risk factors, although some risk factors remain potentially unavoidable.

Epidemiology of readmissions in early infancy following nonelective cesarean delivery

OBJECTIVE

Determine incidence and risk factors for readmissions in early infancy.

STUDY DESIGN

Secondary analysis of data from the Cesarean Section Optimal Antibiotic Prophylaxis trial. All unplanned revisits (unplanned clinic, ER visits, and hospital readmissions) and hospital readmissions (initial discharge to 3-month follow-up) were analyzed.

RESULTS

295 (15.9%) of 1850 infants had revisits with risk factors being ethnicity (adjusted odds ratio (aOR): 0.6 for Hispanic), maternal postpartum antibiotics (1.89), azithromycin treatment (1.22), small for gestational age (1.68), apnea (3.82), and hospital stay after birth >90th percentile (0.49). 71 (3.8%) of 1850 infants were readmitted with risk factors being antenatal steroids (aOR 2.49), elective repeat C/section (0.72), postpartum maternal antibiotics (2.22), O₂ requirement after delivery room (2.82), and suspected/proven neonatal sepsis (0.55).

CONCLUSION(S)

Multiple risk factors were identified, suggesting potential impact on the neonatal microbiome (maternal postpartum antibiotics) or issues related to access/cost of care (Hispanic ethnicity associated with fewer revisits).

Performance of Pediatric Readmission Measures

BACKGROUND

Readmission rates are frequently used as a hospital quality metric; yet multiple measures exist to evaluate pediatric readmission rates. We sought to assess how four different measures of pediatric readmission compare with assessment of both preventable and unplanned readmission.

METHODS

Clinicians on hospital medicine, cardiology, neonatology, and neurology teams reviewed medical records for 30-day readmissions using an abstraction tool with high interrater reliability for preventability assessment. Readmissions between July 2014 and June 2016 were classified separately as preventable or not preventable and planned or unplanned. We compared the classifications to four existing readmission metrics: all-cause readmission, unplanned readmission/time flag classification, the pediatric all-condition readmission, and potentially preventable readmission. We calculated sensitivity and specificity for all readmission metrics.

RESULTS

Among 30-day readmissions considered, 1,643 were eligible for medical record review; 1,125 reviews were completed by the clinical teams (68%). On medical record review, the majority of readmissions were determined not preventable (85%). Only 15% were classified as unplanned and preventable. None of the four readmission measures had appropriate sensitivity or specificity for identifying preventable readmission. The unplanned readmission/time flag classification had the highest sensitivity (95%) and specificity (90%) in identifying unplanned readmissions.

CONCLUSION

None of the existing pediatric readmission measures can reliably determine preventability. The unplanned readmission/time flag measure performed best in identifying unplanned readmissions.

A 5-year retrospective cohort study of unplanned readmissions in an Australian tertiary paediatric hospital

Objective The aim of this study was to examine the characteristics and prevalence of all-cause unplanned hospital readmissions at a tertiary paediatric hospital in Western Australia from 2010 to 2014. Methods A retrospective cohort descriptive study was conducted. Unplanned hospital readmission was identified using both 28- and 30-day measurements from discharge date of an index hospital admission to the subsequent related unplanned admission date. This allowed international comparison. Results In all, 73132 patients with 134314 discharges were identified. During the 5-year period, 4070 discharges (3.03%) and 3330 patients (4.55%) were identified as 30-day unplanned hospital readmissions. There were minimal differences in the rate of readmissions on Days 28, 29 and 30 (0.2%). More than 50% of readmissions were identified as a 5-day readmission. Nearly all readmissions for croup and epiglottitis occurred by Day 5; those for acute bronchiolitis and obstructive sleep apnoea requiring tonsillectomy and/or adenoidectomy occurred by Day 15 and those for acute appendicitis and abdominal and pelvic pain occurred by Day 30. Conclusion This study highlights the variability in the distribution of time intervals from discharge to readmission among diagnoses, suggesting the commonly used 28- or 30-day readmission measurement requires review. It is crucial to establish an appropriate measurement for specific paediatric conditions related to readmissions for the accurate determination of the prevalence and actual costs associated with readmissions. What is known about this topic? Unplanned hospital readmissions result in inefficient use of health resources. Australia has used 28 days to measure unplanned readmissions. However, the 30-day measurement is commonly used in the literature. Only five Australian studies were identified with a focus on readmissions associated with specific paediatric health conditions. What does this paper add? This is the first known study examining paediatric all-cause unplanned same-hospital readmissions in Western Australia. The study used both 28- and 30-day measures from discharge to unplanned readmission to allow international comparison. More than half the unplanned hospital readmissions occurred between Day 0 and Day 5 following discharge from the index admission. Time intervals from discharge date to readmission date varied for diagnosis-specific readmissions of paediatric patients. What are the implications for practitioners? Targeting the top principal index admission diagnoses identified for paediatric readmissions is critical for improvement in the continuity of discharge care delivery, health resource utilisation and associated costs. Because 52% of unplanned readmissions occurred in the first 5 days, urgent investigation and implementation of prevention strategies are required, especially when the readmission occurs on the date of discharge.

Etiologies, trends, and predictors of 30-day pediatric readmissions after hospitalizations for diabetic ketoacidosis in the United States

OBJECTIVE

To determine the causes, predictors, and trends of 30-day readmissions following hospitalizations for pediatric diabetic ketoacidosis (DKA) in the United States (US) from 2010 to 2014.

RESEARCH DESIGN AND METHODS

We used International Classification of Diseases, ninth revision, Clinical Modification codes to identify children with DKA aged 2 to 18 years from the National Readmission Database in the US. Patients who had readmission within 30 days after an index admission for DKA were included in the study. We combined similar diagnoses into clinically important categories to determine the cause of readmission. The primary outcome was all-cause 30-day (AC30) readmissions. Categorical and continuous variables were analyzed using chi-square or student's t-test or Wilcoxon rank sum tests respectively. We performed multivariable logistic regression to identify predictors of 30-day readmission.

RESULTS

From 2010 through 2014, a weighted total of 87 815 index DKA-related pediatric hospitalizations were identified of which, 4055 patients (4.6%) had AC30 readmissions and this remained unchanged during the study period. Of all the readmissions, 69% were attributed to DKA. In multivariable regression analysis, the odds of AC30 readmission and 30-day readmission attributed to DKA alone were increased for females, adolescents, patients with depression and psychosis, and discharge against medical advice, while private insurance, the highest income quartile, and admission at teaching hospitals were associated with lower odds of AC30 readmission and 30-day readmission attributed to DKA only.

CONCLUSION

We identified several factors associated with readmission after hospitalization for DKA. Addressing these factors such as depression may help lower readmissions after an admission for DKA.

A Qualitative Study of Increased Pediatric Reutilization After a Postdischarge Home Nurse Visit

BACKGROUND

The Hospital to Home Outcomes (H2O) trial was a 2-arm, randomized controlled trial that assessed the effects of a nurse home visit after a pediatric hospital discharge. Children randomized to the intervention had higher 30-day postdischarge reutilization rates compared with those with standard discharge. We sought to understand perspectives on why postdischarge home nurse visits resulted in higher reutilization rates and to elicit suggestions on how to improve future interventions.

METHODS

We sought qualitative input using focus groups and interviews from stakeholder groups: parents, primary care physicians (PCP), hospital medicine physicians, and home care registered nurses (RNs). A multidisciplinary team coded and analyzed transcripts using an inductive, iterative approach.

RESULTS

Thirty-three parents participated in interviews. Three focus groups were completed with PCPs (n = 7), 2 with hospital medicine physicians (n = 12), and 2 with RNs (n = 10). Major themes in the explanation of increased reutilization included: appropriateness of patient reutilization; impact of red flags/warning sign instructions on family's reutilization decisions; hospital-affiliated RNs "directing traffic" back to hospital; and home visit RNs had a low threshold for escalating care. Major themes for improving design of the intervention included: need for improved postdischarge communication; individualizing home visits-one size does not fit all; and providing context and framing of red flags.

CONCLUSION

Stakeholders questioned whether hospital reutilization was appropriate and whether the intervention unintentionally directed patients back to the hospital. Future interventions could individualize the visit to specific needs or diagnoses, enhance postdischarge communication, and better connect patients and home nurses to primary care.

Comparing Software Determination of Readmission Preventability With Chart Review, Provider, and Family Assessments

OBJECTIVES

To explore the concordance between software, chart reviewer, provider, and parent perspectives when assessing whether readmissions are preventable or clinically related to the initial admission.

METHODS

Providers and parents of patients readmitted within 3 days to a tertiary children's hospital were enrolled in this single-site observational study. 3M Potentially Preventable Readmissions Grouping Software, chart reviewers, discharge and readmission providers, and parents assessed if readmissions were clinically related to the index admission or potentially preventable. Agreement between perspectives was measured by using Cohen's κ values.

RESULTS

The software found 67 of 118 (57%) clinically related readmissions; the identical 67 of 118 cases (57%) were found to be potentially preventable. Chart reviewers found 107 of 125 (86%) clinically related and 60 of 125 (47%) preventable readmissions compared to 68 of 92 (74%) and 27 of 92 (28%) for discharge physicians and 69 of 93 (74%) and 33 of 93 (34%) for readmitting physicians. Parents reported 9 of 36 (25%) preventable readmissions. Cohen κ values revealed no to minimal agreement on clinical relatedness of readmissions between software and chart reviewer, discharge provider, and readmission provider (0.12-0.20), whereas chart reviewers and providers had weak to moderate agreement with each other (0.43-0.75). There was no to minimal agreement on preventability between software and the other perspectives (-0.04 to 0.21), whereas chart reviewers and providers had minimal to weak agreement (0.27-0.56).

CONCLUSIONS

Measurement of preventable readmissions remains problematic, and using financial penalties for readmissions on the basis of software determinations may be unwise given low levels of agreement. Chart review supplemented by information from providers and families offers a more inclusive way to identify potentially preventable readmissions.

How Measurement Variability Affects Reporting of a Single Readmission Metric

Readmissions are an important quality measure for public reporting, payment, and collaborative research. Lack of measure standardization may lead to inconsistent reporting of outcomes across study sites. In this study, we examined the impact of measurement variability on reporting of a single readmission metric, 30-day all-condition readmission rates (ARRs). We conducted a secondary database analysis of 2006-2008 Medicaid Analytic eXtract data merged from four states of children younger than 21 years. We calculated 30-day ARRs for this cohort using three previously described models varying in their inclusions and exclusions of index hospitalizations and readmissions. The 30-day ARR was highest for the model allowing each readmission to serve as an index admission for subsequent readmissions (ARR: 7%); intermediate for the model allowing one index admission and more than one readmissions in each 30-day period (ARR: 6.2%); and lowest for the model allowing only one readmission in each 30-day period (ARR: 5.6%). Similar variation was seen when stratifying patients by individual diagnostic groups. In conclusion, measurement variability impacts reported outcomes of a single readmission metric. To improve the value of readmission as a quality metric, stakeholders engaged in multisite quality improvement or research should ensure that definitions are standardized across sites.

Preventability of unplanned readmissions within 30 days of discharge. A cross-sectional, single-center study

Objectives

To identify the preventability, determinants and causes of unplanned hospital readmissions within 30 days of discharge using a multidisciplinary approach and including patients’ perspectives.

Design

A prospective cross-sectional single-center study.

Setting

Urban teaching hospital in Amsterdam, the Netherlands.

Participants

430 patients were included. Inclusion criteria were: age ≥ 18 years, discharged from one of seven participating clinical departments and an unplanned readmission within 30 days.

Methods

Residents from the participating departments individually assessed whether the readmission was caused by healthcare, the preventability and possible causes of readmissions using a tool. Thereafter, the preventability of the cases was discussed in a multidisciplinary meeting with residents of all participating departments and clinical pharmacists. The primary outcome was the proportion of readmissions that were potentially preventable. Secondary outcomes were the determinants for a readmission, causes for preventable readmissions, the change in the final decision on preventability after the multidisciplinary meeting and the value of patient interviews in assessing preventability. Differences in characteristics of potentially preventable readmissions (PPRs) and non-PPRs were analyzed using multivariable logistic regression.

Results

Of 430 readmissions, 56 (13%) were assessed as PPRs. Age was significantly associated with a PPR (adjusted OR: 2.42; 95%, CI 1.23–4.74; p = 0.01). The main causes for PPRs were diagnostic (30%), medication (27%) and management problems (27%). During the multidisciplinary meeting, the final decision on preventability changed in 11% of the cases. When a patient interview was available, it was used as a source of information to assess preventability in 26% of readmissions. In 7% of cases, the patient interview was mentioned as the most important source.

Conclusion and implications

13% of readmissions were potentially preventable with diagnostic, medication or management problems being main causes. A multidisciplinary review approach and including the patient’s perspective could contribute to a better understanding of the complexity of readmissions and possible improvements.

Factors Associated With Return Visits at 7 Days After Hospital Discharge

OBJECTIVE

To identify variables associated with return visits to the hospital within 7 days after discharge.

METHODS

We performed a retrospective study of 7-day revisits and readmissions between October 2012 and September 2015 using the Pediatric Health Information System database supplemented by electronic medical record data from a tertiary-care children's hospital. We examined factors associated with revisits among the top 10 most frequent indications for hospitalization using generalized estimating equations.

RESULTS

There were 736 (4.2%) revisits and 416 (2.3%) readmissions within 7 days. Predictors of 7-day revisits and readmissions included age, length of hospital stay, and presence of a chronic medical condition. In addition, insurance status was associated with risk of revisits and race was associated with risk of readmissions in the bivariate analysis.

CONCLUSIONS

In this study, we identified patient characteristics that may be associated with a higher risk of early return to the emergency department and/or readmissions. Early identification of this at-risk group of patients may provide opportunities for intervention and enhanced care coordination at discharge.

Parent Perspectives During Hospital Readmissions for Children With Medical Complexity: A Qualitative Study

OBJECTIVES

Children with medical complexity (CMC) have high readmission rates, but relatively little is known from the parent perspective regarding care experiences surrounding and factors contributing to readmissions. We aimed to elicit parent perspectives on circumstances surrounding 30-day readmissions for CMC.

METHODS

We conducted 20 semistructured interviews with parents of CMC experiencing an unplanned 30-day readmission at 1 academic medical center between December 2016 and January 2018, asking about topics such as previous discharge experiences, medical services and resources, and home environment and social support. Interviews were recorded, professionally transcribed, and analyzed thematically by using a modified grounded theory approach.

RESULTS

Children ranged in age from 0 to 15 years, with neurologic complex chronic conditions being predominant (35%). Although the majority of parents did not identify any factors that they perceived to have contributed to readmission, themes emerged regarding challenges associated with chronicity of care and transitions of care that might influence readmissions, including frequency of hospital use, symptom confusion, lack of inpatient continuity, resources needed but not received, and difficulty filling prescriptions.

CONCLUSIONS

Parents identified multiple challenges associated with chronicity of medical management and transitions of care for CMC. Future interventions aiming to improve continuity and communication between admissions, ensure that home services are provided when applicable and prescriptions are filled, and provide comprehensive support for families in both the short- and long-term may help improve patient and family experiences while potentially decreasing readmissions.

A Quality Improvement Intervention Bundle to Reduce 30-Day Pediatric Readmissions

Supplemental Digital Content is available in the text.

Introduction:

Pediatric hospital readmissions can represent gaps in care quality between discharge and follow-up, including social factors not typically addressed by hospitals. This study aimed to reduce the 30-day pediatric readmission rate on 2 general pediatric services through an intervention to enhance care spanning the hospital stay, discharge, and follow-up process.

Methods:

A multidisciplinary team developed an intervention bundle based on a needs assessment and evidence-based models of transitional care. The intervention included pre-discharge planning with a transition coordinator, screening and intervention for adverse social determinants of health (SDH), medication reconciliation after discharge, communication with the primary care provider, access to a hospital-based transition clinic, and access to a 24-hour direct telephone line staffed by hospital attending pediatricians. These were implemented sequentially from October 2013 to February 2017. The primary outcome was the readmission rate within 30 days of index discharge. The length of stay was a balancing measure.

Results:

During the intervention, the included services discharged 4,853 children. The pre-implementation readmission rate of 10.3% declined to 7.4% and remained stable during a 4-month post-intervention observation period. Among 1,394 families screened for adverse SDH, 48% reported and received assistance with ≥ 1 concern. The length of stay increased from 4.10 days in 2013 to 4.30 days in 2017.

Conclusions:

An intervention bundle, including SDH, was associated with a sustained reduction in readmission rates to 2 general pediatric services. Transitional care that addresses multiple domains of family need during a child’s health crisis can help reduce pediatric readmissions.

Development and Validation of a Web-Based Pediatric Readmission Risk Assessment Tool

OBJECTIVES

Accurately predicting and reducing risk of unplanned readmissions (URs) in pediatric care remains difficult. We sought to develop a set of accurate algorithms to predict URs within 3, 7, and 30 days of discharge from inpatient admission that can be used before the patient is discharged from a current hospital stay.

METHODS

We used the Children's Hospital Association Pediatric Health Information System to identify a large retrospective cohort of 1 111 323 children with 1 321 376 admissions admitted to inpatient care at least once between January 1, 2016, and December 31, 2017. We used gradient boosting trees (XGBoost) to accommodate complex interactions between these predictors.

RESULTS

In the full cohort, 1.6% of patients had at least 1 UR in 3 days, 2.4% had at least 1 UR in 7 days, and 4.4% had at least 1 UR within 30 days. Prediction model discrimination was strongest for URs within 30 days (area under the curve [AUC] = 0.811; 95% confidence interval [CI]: 0.808-0.814) and was nearly identical for UR risk prediction within 3 days (AUC = 0.771; 95% CI: 0.765-0.777) and 7 days (AUC = 0.778; 95% CI: 0.773-0.782), respectively. Using these prediction models, we developed a publicly available pediatric readmission risk scores prediction tool that can be used before or during discharge planning.

CONCLUSIONS

Risk of pediatric UR can be predicted with information known before the patient's discharge and that is easily extracted in many electronic medical record systems. This information can be used to predict risk of readmission to support hospital-discharge-planning resources.