Estimating Length of Stay by Patient Type in the Neonatal Intensive Care Unit

Rate of Urinary Tract Infections, Bacteremia, and Meningitis in Preterm and Term Infants

BACKGROUND AND OBJECTIVES

There are very limited data on the rate of urinary tract infections (UTI), bacteremia, and meningitis in preterm infants with fever. Many of the studies on the incidence of these infections excluded preterm infants. This study compared the rate of these infections in preterm infants born at 32-36 weeks to term infants born at 37-42 weeks.

METHODS

A multicenter observational cohort study was conducted to evaluate rates of UTI, bacteremia, and meningitis in term and preterm infants 8-60 days of age with a diagnosis of fever from 2016 through 2022 using encounter data from children's hospitals in the Pediatric Health Information System.

RESULTS

There were 19 507 total febrile infants identified, of which 2162 were preterm and 17 345 were term. Preterm infants had a lower rate of UTI than term infants (1.8% confidence interval [CI] [1.3-2.5] vs 3.0% CI [2.7-3.2], P = .001). Preterm and term infants did not have statistically different rates of bacteremia (1.5% CI [1.3-1.7] vs 1.2% CI [0.8-1.8], P = .44) or meningitis (0.16% CI [0.1-0.2] vs 0.05% CI [0-0.2], P = .36).

CONCLUSIONS

There was no difference in the rate of bacteremia or meningitis between term and preterm infants in a large multicenter cohort of febrile infants. Preterm infants had a lower rate of UTI than term infants. This is the first multicenter study to compare UTI, bacteremia, and meningitis between term and preterm febrile infants.

Variation in Length of Stay by Level of Neonatal Care Among Moderate and Late Preterm Infants

BACKGROUND AND OBJECTIVES

Moderate and late preterm infants are a growing subgroup of neonates with increased care needs after birth, yet standard protocols are lacking. We aim to describe variation in length of stay (LOS) by gestational age (GA) across hospitals within the same level of neonatal care and between different levels of neonatal care.

METHODS

Retrospective cohort study of hospitalizations for moderate (32-33 weeks GA) and late (34-36 weeks GA) preterm infants in 2019 Kid's Inpatient Database. We compared adjusted LOS in this cohort and evaluated variation within hospitals of the same level and across different levels of neonatal care.

RESULTS

This study includes 217 051 moderate (26.2%) and late (73.8%) preterm infants from level II (19.7%), III (66.3%), and IV (11.1%) hospitals. Patient-level (race and ethnicity, primary payor, delivery type, multiple gestation, birth weight) and hospital-level (birth region, level of neonatal care) factors were significantly associated with LOS. Adjusted mean LOS varied for hospitals within the same level of neonatal care with level II hospitals showing the greatest variability among 34- to 36- week GA infants when compared with level III and IV hospitals (P < .01). LOS also varied significantly between levels of neonatal care with the greatest variation (0.9 days) seen in 32-week GA between level III and level IV hospitals.

CONCLUSIONS

For moderate and late preterm infants, the level of neonatal care was associated with variation in LOS after adjusting for clinical severity. Hospitals providing level II neonatal care showed the greatest variation and may provide an opportunity to standardize care.

Developing a length of stay prediction model for newborns, achieving better accuracy with greater usability

BACKGROUND

One in ten newborn children is born prematurely. The elongated length of stay (LOS) of these children in the Neonatal Intensive Care Unit (NICU) has important implications on hospital occupancy figures, healthcare and management costs, as well as the psychology of parents. In order to allow accurate planning and resource allocation, this study aims to create a generalizable and robust model to predict the NICU LOS of preterm newborns.

METHODS

Data were collected from a large tertiary center NICU between 2011 and 2018 and relates to 5,362 newborns. The selected model was externally validated using a data set of 8,768 newborns from another tertiary center NICU. This report compares several models, such as Random Forest (RF), quantile RF, and other feature selection methods, including LASSO and AIC step-forward selection. In addition, a novel step-forward selection based on False Discovery Rate (FDR) for quantile regression is presented and evaluated.

RESULTS

A high-orderquantile regression model for predicting preterm newborns' LOS that uses only four features available at birth had more attractive properties than other richer ones. The model achieved a Mean Absolute Error (MAE) of 6.26 days on the internal validation set (average LOS 27.04) and an MAE of 6.04 days on the external validation set (average LOS 29.32). The suggested model surpassed the accuracy obtained by models in the literature. It is shown empirically that the FDR-based selection has better properties than the AIC-based step-forward selection approach.

CONCLUSION

This paper demonstrates a process to create a predictive model for NICU LOS in preterm newborns, where each step is reasoned. We obtain a simple and robust model for NICU LOS prediction, which achieves far better results than the current model used for financing NICUs. Utilizing this model, we have created an easy-to-use online web application to ease parents' worries and to assist NICU management: https://tzviel.shinyapps.io/calcuLOS.

Predictors of length of hospital stay for preterm infants in Ethiopia: a competing risk analysis

Background

Length of hospital stay (LOS) is one of the essential indicators for evaluating the efficiency and the quality-of-care service delivered. predicting LOS is critical for resource allocation, decision-making, lowering neonatal morbidity and death, enhancing clinical outcomes and parent counseling. In addition, extended hospital stays (long LOS_NICU) place a burden on the healthcare systems decreasing bed turnover rates as well as their financial stand and the mental stress on families. In Ethiopia, there is limited evidence on the determinant factors that influence on LOS.

Objectives

To determine factors affecting neonatal intensive care unit length of stay for all preterm newborns who were discharged alive.

Method

The study used a secondary data source, was collected for the Study of Illness in Preterm (SIP) infants project. The research study was a multicenter, cross-sectional, observational clinical study that took place in five Ethiopia hospitals from July 1, 2016, to May 31, 2018. The predictors of LOS were determined using Fine-Gray's competing risk analysis.

Results

For this study 3,511 preterm infants admitted to the NICU were analyzed. About 28.8% of the preterm infants died during their time in neonatal care while 66.6% were discharged alive. At the end of the study 4.6% babies were still in the NICU. The overall median LOS (death or discharge) was 7 days, with an interquartile range of 8 days. The cumulative incidence of discharge rose with increasing in gestational age and birth weight, on the contrary, the rate of discharge was decreased by 45.7% with the development of RDS (SDH ratio: 0.543), by 75.9% with the development of apnea (SDH ratio: 0.241), by 36.2% with sepsis, and by 43.6% with pneumonia (SDH ratio: 0.564).

Conclusions

Preterm newborns with a low gestational age and birth weight have a greater probability of having a prolonged LOS. Complications of the medical conditions RDS, apnea, sepsis, pneumonia, anemia, asphyxia, and NEC substantially raise LOS considerably.

Changes in neonatal morbidity, neonatal care practices, and length of hospital stay of surviving infants born very preterm in the Netherlands in the 1980s and in the 2000s: a comparison analysis with identical characteristics definitions

BACKGROUND

This study evaluates changes in the neonatal morbidity, the neonatal care practices, and the length of hospital stay of surviving very preterm (VP) infants born in the Netherlands in the 1980s and in the 2000s; a period over which historical improvements were introduced into neonatal care. We, herein, also study whether these changes in neonatal morbidity, neonatal care practices and length of hospital stay are associated with sociodemographic, prenatal, and infant characteristics.

METHODS

Two community-based cohorts from 1983 (POPS) and 2002-03 (LOLLIPOP) have provided the perinatal data for our study. The analysis enrolled 1,228 participants born VP (before the 32nd week of gestation) and surviving to 2 years of age without any severe congenital malformation. A rigorous harmonisation protocol ensured a precise comparison of the cohorts by using identical definitions of the perinatal characteristics.

RESULTS

In 2003, mothers were older when giving birth, had higher multiple birth rates, and significantly more parents had received higher education. In 2003, less VP infants had severe intraventricular haemorrhage and sepsis and relatively more received continuous positive airway pressure, mechanical ventilation and caffeine therapy than in 1983. Antenatal corticosteroids and surfactant therapy were provided only in 2003. The length of the stay in the neonatal intensive care unit and in hospital had decreased in 2003 by 22 and 11 days, respectively. Differences persisted after adjustment for sociodemographic, prenatal, and infant characteristics.

CONCLUSIONS

Neonatal morbidities of the surviving VP infants in this study have not increased, and exhibit improvements for various characteristics in two cohorts born 20 years apart with comparable gestational age and birth weight. Our data suggest that the improvements found are associated with more advanced therapeutic approaches and new national protocols in place, and less so with sociodemographic changes. This analysis provides a basis for further comparative analyses of the health and the development of VP children, particularly with regard to long-term outcomes.

Association of Primary Language with Very Low Birth Weight Outcomes in Hispanic Infants in California

OBJECTIVE

To determine the association of Spanish as a primary language for a family with the health outcomes of Hispanic infants with very low birth weight (VLBW, <1500g).

STUDY DESIGN

Data from the California Perinatal Quality Care Collaborative (CPQCC) linked to hospital discharge records were analyzed. Hispanic infants with VLBW born between 2009 and 2018 with a primary language of English or Spanish were included. Outcomes selected were hypothesized to be sensitive to language barriers. Multivariable logistic regression models and mixed models estimated associations between language and outcomes.

RESULTS

Of 18 364 infants meeting inclusion criteria, 27% (n = 4976) were born to families with Spanish as a primary language. In unadjusted analyses, compared with infants of primarily English-speaking families, these infants had higher odds of hospital readmission within 1 year (OR 1.11 [95% CI 1.02-1.21]), higher odds to receive human milk at discharge (OR 1.32 [95% CI 1.23-1.42]), and lower odds of discharge home with oxygen (OR 0.83 [95% CI 0.73-0.94]). In multivariable analyses, odds of readmission and home oxygen remained significant when adjusting for infant but not maternal and hospital characteristics. Higher odds for receipt of any human milk at discharge were significant in all models. Remaining outcomes did not differ between groups.

CONCLUSIONS

Significant differences exist between Hispanic infants with VLBW of primarily Spanish-vs English-speaking families. Exploration of strategies to prevent readmissions of infants of families with Spanish as a primary language is warranted.

The Role of Distance from Home to Hospital on Parental Experience in the NICU: A Qualitative Study

Prolonged admission to the neonatal intensive care unit presents challenges for families, especially those displaced far from home. Understanding specific barriers to parental engagement in the NICU is key to addressing these challenges with hospital-based interventions. The objective of this qualitative study was to explore the impact of distance from home to hospital on the engagement of parents of very preterm infants (VPT) in the neonatal intensive care unit (NICU). We used a grounded theory approach and conducted 13 qualitative interviews with parents of VPT who were admitted ≥14 days and resided ≥50 miles away using a semi-structured interview guide informed by the socio-ecological framework. We used constant comparative method with double coders for theme emergence. Our results highlight a multitude of facilitators and barriers to engagement. Facilitators included: (1) individual-delivery preparedness and social support; (2) environmental-medical team relationships; and (3) societal-access to perinatal care. Barriers included: (1) individual-transfer stressors, medical needs, mental health, and dependents; (2) environmental-NICU space, communication, and lack of technology; and (3) societal-lack of paid leave. NICU parents with geographic separation from home experienced a multitude of barriers to engagement, many of which could be addressed by hospital-based interventions.

A case-based reasoning system for neonatal survival and LOS prediction in neonatal intensive care units: a development and validation study

Early prediction of neonates' survival and Length of Stay (LOS) in Neonatal Intensive Care Units (NICU) is effective in decision-making. We developed an intelligent system to predict neonatal survival and LOS using the "Case-Based Reasoning" (CBR) method. We developed a web-based CBR system based on K-Nearest Neighborhood (KNN) on 1682 neonates and 17 variables for mortality and 13 variables for LOS and evaluated the system with 336 retrospectively collected data. We implemented the system in a NICU to externally validate the system and evaluate the system prediction acceptability and usability. Our internal validation on the balanced case base showed high accuracy (97.02%), and F-score (0.984) for survival prediction. The root Mean Square Error (RMSE) for LOS was 4.78 days. External validation on the balanced case base indicated high accuracy (98.91%), and F-score (0.993) to predict survival. RMSE for LOS was 3.27 days. Usability evaluation showed that more than half of the issues identified were related to appearance and rated as a low priority to be fixed. Acceptability assessment showed a high acceptance and confidence in responses. The usability score (80.71) indicated high system usability for neonatologists. This system is available at http://neonatalcdss.ir/ . Positive results of our system in terms of performance, acceptability, and usability indicated this system can be used to improve neonatal care.

Virtual family-centered hospital rounds in the neonatal intensive care unit: protocol for a cluster randomized controlled trial

BACKGROUND

Family-centered rounds is recognized as a best practice for hospitalized children, but it has only been possible for children whose families can physically be at the bedside during hospital rounds. The use of telehealth to bring a family member virtually to the child's bedside during hospital rounds is a promising solution. We aim to evaluate the impact of virtual family-centered hospital rounds in the neonatal intensive care unit on parental and neonatal outcomes.

METHODS

This two-arm cluster randomized controlled trial will randomize families of hospitalized infants to have the option to use telehealth for virtual hospital rounds (intervention) or usual care (control). The intervention-arm families will also have the option to participate in hospital rounds in-person or to not participate in hospital rounds. All eligible infants who are admitted to this single-site neonatal intensive care unit during the study period will be included. Eligibility requires that there be an English-proficient adult parent or guardian. We will measure participant-level outcome data to test the impact on family-centered rounds attendance, parent experience, family-centered care, parent activation, parent health-related quality of life, length of stay, breastmilk feeding, and neonatal growth. Additionally, we will conduct a mixed methods implementation evaluation using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework.

DISCUSSION

The findings from this trial will increase our understanding about virtual family-centered hospital rounds in the neonatal intensive care unit. The mixed methods implementation evaluation will enhance our understanding about the contextual factors that influence the implementation and rigorous evaluation of our intervention.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05762835. Status: Not yet recruiting. First posted: March 10, 2023; last update posted: March 10, 2023.

Virtual Family-Centered Rounds in the Neonatal Intensive Care Unit: Protocol for a Cluster Randomized Controlled Trial

Background: Family-centered rounds is recognized as a best practice for hospitalized children, but it has only been possible for children whose families can physically be at the bedside during hospital rounds. The use of telehealth to bring a family member virtually to the child’s bedside during rounds is a promising solution. We aim to evaluate the impact of virtual family-centered rounds in the neonatal intensive care unit on parental and neonatal outcomes. Methods: This two-arm cluster randomized controlled trial will randomize families of hospitalized infants to have the option to use telehealth for virtual rounds (intervention) or usual care (control). The intervention-arm families will also have the option to participate in rounds in-person or to not participate in rounds. All eligible infants who are admitted to this single-site neonatal intensive care unit during the study period will be included. Eligibility requires that there be an English-proficient adult parent or guardian. We will measure participant-level outcome data to test the impact on family-centered rounds attendance, parent experience, family-centered care, parent activation, parent health-related quality of life, length of stay, breastmilk feeding, and neonatal growth. Additionally, we will conduct a mixed methods implementation evaluation using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework. Discussion: The findings from this trial will increase our understanding about virtual family-centered rounds in the neonatal intensive care unit. The mixed methods implementation evaluation will enhance our understanding about the contextual factors that influence the implementation and rigorous evaluation of our intervention. Trial registration: ClinicalTrials.gov Identifier: NCT05762835. Status: Not yet recruiting. First Posted: 3/10/2023; Last Update Posted: 3/10/2023.

Neonatal intensive care unit occupancy rate and probability of discharge of very preterm infants

OBJECTIVE

To assess the association of NICU occupancy with probability of discharge and length of stay (LOS) among infants born <33 weeks gestational age (GA).

STUDY DESIGN

Retrospective study of 3388 infants born 23-32 weeks GA, admitted to five Level 3/4 NICUs (2014-2018) and discharged alive. Standardized ratios of observed-to-expected number of discharges were calculated for each quintile of unit occupancy. Multivariable linear regression models were used to assess the association between occupancy and LOS.

RESULTS

At the lowest unit occupancy quintiles (Q1 and Q2), infants were 12% and 11% less likely to be discharged compared to the expected number. At the highest unit occupancy quintile (Q5), infants were 20% more likely to be discharged. Highest occupancy (Q5) was also associated with a 4.7-day (95% CI 1.7, 7.7) reduction in LOS compared Q1.

CONCLUSION

NICU occupancy was associated with likelihood of discharge and LOS among infants born <33 weeks GA.

Risk factors for length of NICU stay of newborns: A systematic review

Background

The improvement in survival of preterm infants is accompanied by an increase in neonatal intensive care unit (NICU) admissions. Prolonged length of stay in the NICU (LOS-NICU) increases the incidence of neonatal complications and even mortality and places a significant economic burden on families and strain on healthcare systems. This review aims to identify risk factors influencing LOS-NICU of newborns and to provide a basis for interventions to shorten LOS-NICU and avoid prolonged LOS-NICU.

Methods

A systematic literature search was conducted in PubMed, Web of Science, Embase, and Cochrane library for studies that were published in English from January 1994 to October 2022. The PRISMA guidelines were followed in all phases of this systematic review. The Quality in Prognostic Studies (QUIPS) tool was used to assess methodological quality.

Results

Twenty-three studies were included, 5 of which were of high quality and 18 of moderate quality, with no low-quality literature. The studies reported 58 possible risk factors in six broad categories (inherent factors; antenatal treatment and maternal factors; diseases and adverse conditions of the newborn; treatment of the newborn; clinical scores and laboratory indicators; organizational factors).

Conclusions

We identified several of the most critical risk factors affecting LOS-NICU, including birth weight, gestational age, sepsis, necrotizing enterocolitis, bronchopulmonary dysplasia, and retinopathy of prematurity. As only a few high-quality studies are available at present, well-designed and more extensive prospective studies investigating the risk factors affecting LOS-NICU are still needed in the future.

Predicting clinical outcomes using artificial intelligence and machine learning in neonatal intensive care units: a systematic review

BACKGROUND

Advances in technology, data availability, and analytics have helped improve quality of care in the neonatal intensive care unit.

OBJECTIVE

To provide an in-depth review of artificial intelligence (AI) and machine learning techniques being utilized to predict neonatal outcomes.

METHODS

The PRISMA protocol was followed that considered articles from established digital repositories. Included articles were categorized based on predictions of: (a) major neonatal morbidities such as sepsis, bronchopulmonary dysplasia, intraventricular hemorrhage, necrotizing enterocolitis, and retinopathy of prematurity; (b) mortality; and (c) length of stay.

RESULTS

A total of 366 studies were considered; 68 studies were eligible for inclusion in the review. The current set of predictor models are primarily built on supervised learning and mostly used regression models built on retrospective data.

CONCLUSION

With the availability of EMR data and data-sharing of NICU outcomes across neonatal research networks, machine learning algorithms have shown breakthrough performance in predicting neonatal disease.

Measuring quality of care in moderate and late preterm infants

OBJECTIVE

To examine quality measures for moderate and late preterm (MLP) infants.

STUDY DESIGN

By prospectively analyzing Vermont Oxford Network's all NICU admissions database, we adapted Baby-MONITOR, a composite quality measure for extremely/very preterm infants, for MLP infants. We examined correlations between the adapted MLP quality measure (MLP-QM) in MLP infants and Baby-MONITOR in extremely and very preterm infants.

RESULT

We studied 376,219 MLP (30-36 weeks GA) and 57,595 extremely/very preterm (25-29 weeks GA) infants from 465 U.S. hospitals born from 2016 to 2020. MLP-QM summary scores in MLP infants had weak correlation with Baby-MONITOR scores in extremely and very preterm infants (r = 0.47). There was weak correlation among survival (r = 0.19), no pneumothorax (r = 0.35), and no infection after 3 days (r = 0.45), but strong correlation among human milk at discharge (r = 0.79) and no hypothermia (r = 0.76).

CONCLUSION

Modest correlation among hospital care measures in two preterm populations suggests the need for MLP-specific care measures.

Diagnosis and management of cardiopulmonary events in very low birth weight infants close to discharge: a quality improvement initiative

BACKGROUND

Cardiopulmonary events (CPE) have a central, obstructive, or mixed etiology. Lack of standardized diagnosis and management of CPE may prolong the length of stay (LOS).

OBJECTIVE

To increase the accuracy of CPE diagnosis and decrease LOS by 10% for preterm infants over a 12-month period.

METHODS

Develop an evidence-based algorithm to identify type of CPE, determine management approach, and evaluate cardio-respiratory monitors output. Apply model for improvement and statistical process control charts to determine special cause variation.

RESULTS

Identification of central apnea increased from 15 to 39% (p < 0.01). LOS decreased 26% from 52.6 days to 39.2 days, with an estimated cost savings of $13,119 per each of the 225 infants in the initiative.

CONCLUSION

After implementing an evidence-based algorithm for management of neonatal CPE, a significant increase in the accuracy of the diagnosis of central apnea and cost savings associated with a decrease in LOS were observed.

Associação entre peso ao nascer, idade gestacional e diagnósticos secundários na permanência hospitalar de recém-nascidos prematuros

Objetivo: verificar a associação entre peso ao nascer, idade gestacional e diagnósticos médicos secundários no tempo de permanência hospitalar de recém-nascidos prematuros. Métodos: estudo transversal, com 1.329 prontuários de recém-nascidos no período de julho de 2012 a setembro de 2015, em dois hospitais de Belo Horizonte, que utilizam o sistema Diagnosis Related Groups Brasil. Para determinar um ponto de corte para o peso ao nascer e a idade gestacional no nascimento que melhor determinasse o tempo de internação foi utilizada a curva Receive Operator Characteristic. Posteriormente, utilizou-se o teste de Análise de Variância e teste de Duncan para a comparação entre a média de tempo de permanência hospitalar. Resultados: a prematuridade sem problemas maiores (DRG792) foi a categoria mais prevalente (43,12%). O maior tempo médio de internação foi de 34,9 dias, identificado entre os recém-nascidos prematuros ou com Síndrome da angústia respiratória (DRG 790). A combinação de menor peso ao nascer e menor IG ao nascimento apresentaram o maior risco de permanência hospitalar, aumentada quando comparados ao demais perfis formados para esse DRG. Conclusão: os achados poderão direcionar a assistência em relação à mobilização de recursos físicos, humanos e de bens de consumo, além da análise crítica de condições que influenciam os desfechos clínicos. A possibilidade da otimização do uso desses recursos hospitalares aliada à melhoria da qualidade dos atendimentos e da segurança dos pacientes está associada a uma minimização do tempo de permanência hospitalar e da carga de morbidade e mortalidade neonatal.

A High-Fidelity Model to Predict Length-of-Stay in the Neonatal Intensive Care Unit (NICU)

Having an interpretable dynamic length-of-stay (LOS) model can help hospital administrators and clinicians make better decisions and improve the quality of care. The widespread implementation of electronic medical record (EMR) systems has enabled hospitals to collect massive amounts of health data. However, how to integrate this deluge of data into healthcare operations remains unclear. We propose a framework grounded in established clinical knowledge to model patients' lengths-of-stay. In particular, we impose expert knowledge when grouping raw clinical data into medically meaningful variables, which summarize patients' health trajectories. We use dynamic predictive models to output patients' remaining lengths-of-stay (RLOS), future discharges, and census probability distributions based on their health trajectories up to the current stay. Evaluated with large-scale EMR data, the dynamic model significantly improves predictive power over the performance of any model in previous literature and remains medically interpretable.

Cost-effectiveness analysis of heart rate characteristics monitoring to improve survival for very low birth weight infants

Introduction

Over 50,000 very low birth weight (VLBW) infants are born each year in the United States. Despite advances in care, these premature babies are subjected to long stays in a neonatal intensive care unit (NICU), and experience high rates of morbidity and mortality. In a large randomized controlled trial (RCT), heart rate characteristics (HRC) monitoring in addition to standard monitoring decreased all-cause mortality among VLBW infants by 22%. We sought to understand the cost-effectiveness of HRC monitoring to improve survival among VLBW infants.

Methods

We performed a secondary analysis of cost-effectiveness of heart rate characteristics (HRC) monitoring to improve survival from birth to NICU discharge, up to 120 days using data and outcomes from an RCT of 3,003 VLBW patients. We estimated each patient's cost from a third-party perspective in 2021 USD using the resource utilization data gathered during the RCT (NCT00307333) during their initial stay in the NICU and applied to specific per diem rates. We computed the incremental cost-effectiveness ratio and used non-parametric boot-strapping to evaluate uncertainty.

Results

The incremental cost-effectiveness ratio of HRC-monitoring was $34,720 per life saved. The 95th percentile of cost to save one additional life through HRC-monitoring was $449,291.

Conclusion

HRC-monitoring appears cost-effective for increasing survival among VLBW infants.

Nutritional Factors Associated with Late-Onset Sepsis in Very Low Birth Weight Newborns

BACKGROUND

Delayed onset of minimal enteral nutrition compromises the immune response of preterm infants, increasing the risk of colonization and clinical complications (e.g., late-onset sepsis). This study aimed to analyze associations between late-onset sepsis in very low birth weight infants (<1500 g) and days of parenteral nutrition, days to reach full enteral nutrition, and maternal and nutritional factors.

METHODS

A cross-sectional study was carried out with very low birth weight infants admitted to a neonatal intensive care unit (NICU) of a reference maternity hospital of high-risk deliveries. Data regarding days of parenteral nutrition, days to reach full enteral nutrition, fasting days, extrauterine growth restriction, and NICU length of stay were extracted from online medical records. Late-onset sepsis was diagnosed (clinical or laboratory) after 48 h of life. Chi-squared, Mann-Whitney tests, and binary logistic regression were applied.

RESULTS

A total of 97 preterm infants were included. Of those, 75 presented late-onset sepsis with clinical (n = 40) or laboratory (n = 35) diagnosis. Maternal urinary tract infection, prolonged parenteral nutrition (>14 days), and extrauterine growth restriction presented 4.24-fold, 4.86-fold, and 4.90-fold higher chance of late-onset sepsis, respectively.

CONCLUSION

Very low birth weight infants with late-onset sepsis had prolonged parenteral nutrition and took longer to reach full enteral nutrition. They also presented a higher prevalence of extrauterine growth restriction than infants without late-onset sepsis.

Predicting in-hospital length of stay for very-low-birth-weight preterm infants using machine learning techniques

BACKGROUND/PURPOSE

The in-hospital length of stay (LOS) among very-low-birth-weight (VLBW, BW < 1500 g) infants is an index for care quality and affects medical resource allocation. We aimed to analyze the LOS among VLBW infants in Taiwan, and to develop and compare the performance of different LOS prediction models using machine learning (ML) techniques.

METHODS

This retrospective study illustrated LOS data from VLBW infants born between 2016 and 2018 registered in the Taiwan Neonatal Network. Among infants discharged alive, continuous variables (LOS or postmenstrual age, PMA) and categorical variables (late and non-late discharge group) were used as outcome variables to build prediction models. We used 21 early neonatal variables and six algorithms. The performance was compared using the coefficient of determination (R²) for continuous variables and area under the curve (AUC) for categorical variables.

RESULTS

A total of 3519 VLBW infants were included to illustrate the profile of LOS. We found 59% of mortalities occurred within the first 7 days after birth. The median of LOS among surviving and deceased infants was 62 days and 5 days. For the ML prediction models, 2940 infants were enrolled. Prediction of LOS or PMA had R² values less than 0.6. Among the prediction models for prolonged LOS, the logistic regression (ROC: 0.724) and random forest (ROC: 0.712) approach had better performance.

CONCLUSION

We provide a benchmark of LOS among VLBW infants in each gestational age group in Taiwan. ML technique can improve the accuracy of the prediction model of prolonged LOS of VLBW.

Forecasting the length-of-stay of pediatric patients in hospitals: a scoping review

BACKGROUND

Healthcare management faces complex challenges in allocating hospital resources, and predicting patients' length-of-stay (LOS) is critical in effectively managing those resources. This work aims to map approaches used to forecast the LOS of Pediatric Patients in Hospitals (LOS-P) and patients' populations and environments used to develop the models.

METHODS

Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) methodology, we performed a scoping review that identified 28 studies and analyzed them. The search was conducted on four databases (Science Direct, Scopus, Web of Science, and Medline). The identification of relevant studies was structured around three axes related to the research questions: (i) forecast models, (ii) hospital length-of-stay, and (iii) pediatric patients. Two authors carried out all stages to ensure the reliability of the review process. Articles that passed the initial screening had their data charted on a spreadsheet. Methods reported in the literature were classified according to the stage in which they are used in the modeling process: (i) pre-processing of data, (ii) variable selection, and (iii) cross-validation.

RESULTS

Forecasting models are most often applied to newborn patients and, consequently, in neonatal intensive care units. Regression analysis is the most widely used modeling approach; techniques associated with Machine Learning are still incipient and primarily used in emergency departments to model patients in specific situations.

CONCLUSIONS

The studies' main benefits include informing family members about the patient's expected discharge date and enabling hospital resources' allocation and planning. Main research gaps are associated with the lack of generalization of forecasting models and limited reported applicability in hospital management. This study also provides a practical guide to LOS-P forecasting methods and a future research agenda.

The Association of Social Factors and Time Spent in the NICU for Mothers of Very Preterm Infants

OBJECTIVES

Evaluate the association between maternal social factors and maternal time spent in the NICU for very preterm infants admitted to 4 level III and IV NICUs.

METHODS

In this prospective observational cohort study, we enrolled mother-infant dyads whose infants were born <32 weeks' gestation. Enrollment occurred after 2 weeks of NICU exposure, when maternal social factors and demographic information was collected. Maternal time spent in the NICU was abstracted from the electronic medical record and was dichotomized into 0 to 6 days and ≥6 days per week. Demographic differences between the 2 groups were compared by using χ2 tests. Logistic regression was used to assess the independent association between maternal social factors and the average number of days per week spent in the NICU.

RESULTS

A total of 169 mother-infant dyads were analyzed. Maternal social factors associated with more time spent in the NICU included an annual household income of >$100 000, compared with those with an annual household income of <$50 000 (adjusted odds ratio [aOR]: 5.68; 95% confidence interval [CI] 1.77-18.19), a travel time <30 minutes to the NICU (compared with those who traveled >60 minutes [aOR: 7.85; 95% CI 2.81-21.96]), and the lack of other children in the household, compared with women with other children (aOR: 3.15; 95% CI 1.39-7.11).

CONCLUSIONS

Maternal time spent in the NICU during a prolonged birth hospitalization of a very preterm infant differed by socioeconomic status, travel time, and presence of other dependents. Strategies to better identify and reduce these disparities to optimize engagement and, subsequently, improve infant health outcomes is needed.

When is My Baby Going Home? Moderate to Late Preterm Infants are Discharged at 36 Weeks Based on Admission Data

OBJECTIVE

This study evaluates the effect of admission characteristics of uncomplicated moderate to late preterm infants on timing of discharge. One of the first questions that families of infants admitted to the Neonatal Intensive Care Unit (NICU) ask is, "When is my baby going home?" Moderate to late preterm infants are the largest cohort of NICU patients but little data exist about their length of stay (LOS).

STUDY DESIGN

A retrospective electronic chart review was completed on 12,498 infants admitted to our NICU between January 1, 2009 and December 31, 2015. All inborn infants with a gestational age between 32^0/7 and 36^6/7 weeks were studied.

RESULTS

A total of 3,240 infants met our inclusion criteria. The mean postmenstrual age at discharge was 36^3/7 weeks. Infants who were small for gestational age were significantly more likely to have an increased LOS. Infants born between 34 and 36^6/7 weeks had a significantly increased LOS if they had respiratory distress syndrome. Admission diagnoses of neonatal abstinence syndrome, meconium aspiration syndrome, hydrops, hypoxic ischemic encephalopathy, biliary emesis, ABO incompatibly, and a genetic diagnosis all had increased LOS for all late preterm infants.

CONCLUSION

For uncomplicated moderate to late preterm infants, clinicians can counsel families that their infants will likely be discharged at 36 weeks of postmenstrual age. Small for gestational age infants and those with specific diagnoses may stay longer.

Variations in Neonatal Length of Stay of Babies Born Extremely Preterm: An International Comparison Between iNeo Networks

OBJECTIVE

To compare length of stay (LOS) in neonatal care for babies born extremely preterm admitted to networks participating in the International Network for Evaluating Outcomes of Neonates (iNeo).

STUDY DESIGN

Data were extracted for babies admitted from 2014 to 2016 and born at 24 to 28 weeks of gestational age (n = 28 204). Median LOS was calculated for each network for babies who survived and those who died while in neonatal care. A linear regression model was used to investigate differences in LOS between networks after adjusting for gestational age, birth weight z score, sex, and multiplicity. A sensitivity analysis was conducted for babies who were discharged home directly.

RESULTS

Observed median LOS for babies who survived was longest in Japan (107 days); this result persisted after adjustment (20.7 days more than reference, 95% CI 19.3-22.1). Finland had the shortest adjusted LOS (-4.8 days less than reference, 95% CI -7.3 to -2.3). For each week's increase in gestational age at birth, LOS decreased by 12.1 days (95% CI -12.3 to -11.9). Multiplicity and male sex predicted mean increases in LOS of 2.6 (95% CI 2.0-3.2) and 2.1 (95% CI 1.6-2.6) days, respectively.

CONCLUSIONS

We identified between-network differences in LOS of up to 3 weeks for babies born extremely preterm. Some of these may be partly explained by differences in mortality, but unexplained variations also may be related to differences in clinical care practices and healthcare systems between countries.

Designing a bed-side system for predicting length of stay in a neonatal intensive care unit

Increased length of stay (LOS) in intensive care units is directly associated with the financial burden, anxiety, and increased mortality risks. In the current study, we have incorporated the association of day-to-day nutrition and medication data of the patient during its stay in hospital with its predicted LOS. To demonstrate the same, we developed a model to predict the LOS using risk factors (a) perinatal and antenatal details, (b) deviation of nutrition and medication dosage from guidelines, and (c) clinical diagnoses encountered during NICU stay. Data of 836 patient records (12 months) from two NICU sites were used and validated on 211 patient records (4 months). A bedside user interface integrated with EMR has been designed to display the model performance results on the validation dataset. The study shows that each gestation age group of patients has unique and independent risk factors associated with the LOS. The gestation is a significant risk factor for neonates < 34 weeks, nutrition deviation for < 32 weeks, and clinical diagnosis (sepsis) for ≥ 32 weeks. Patients on medications had considerable extra LOS for ≥ 32 weeks’ gestation. The presented LOS model is tailored for each patient, and deviations from the recommended nutrition and medication guidelines were significantly associated with the predicted LOS.

Newer bronchopulmonary dysplasia definitions and prediction of health economics impacts in very preterm infants

OBJECTIVE

To compare the abilities of bronchopulmonary dysplasia (BPD) definitions to predict hospital charges as a surrogate of disease complexity.

METHODS

Retrospective study of infants admitted to the neonatal intensive care unit (NICU) less than 32 weeks gestational age. Subjects were classified according to the Canadian Neonatal Network (CNN), the National Institute of Child Health and Human Development (NICHD) (2018), and Jensen BPD definitions as none, mild (1), moderate (2), or severe (3) BPD. Spearman's correlation was performed to evaluate the association of BPD definitions with health economics outcomes.

RESULTS

One hundred and sixty-eight infants were included with mean birth weight of 1197 g and mean gestational age of 28.4 weeks. More infants were classified as no BPD according to CNN definition (79%) in comparison to NICHD 2018 (64.3%) and Jensen (59.5%) definitions. There were fewer infants as the grade of severity increased for all definitions, this was most linear for Jensen definition with Grade 1 present in 25%, Grade 2 in 12.5%, and Grade 3 in 3%. A stronger correlation with NICU length of stay, NICU hospital charges, NICU charges per day, and first year of life hospital charges was detected for Jensen definition (correlation coefficient of 0.58, 0.66, 0.64, 0.67, respectively) in comparison to CNN and NICHD 2018 definitions (p < .0001).

CONCLUSION

Jensen BPD definition had the strongest correlation with first year health economics outcomes in our study. Validating recent BPD definitions using population-based data is imperative to improve family counseling and enhance the designs of quality improvement initiatives and therapeutic research studies targeting patient-centric outcomes.

Quality indicators in nutrition therapy and clinical outcomes in a neonatal intensive care unit

ABSTRACT Objective To associate quality indicators in nutritional therapy and pre-determined clinical outcomes in a neonatal unit. Methods A total of 81 premature newborns were monitored regarding the time to initiate nutrition therapy, time to meet energy needs, energy and protein adequacy, cumulative energy deficit, adequacy of the nutritional formula and fasting periods; weight gain, the occurrence of necrotizing enterocolitis, mortality and length of stay in the intensive care unit. The data were analyzed with the Statistical Package for the Social Sciences at 5% significance level. Results The time to start enteral nutrition and the calories infused/kg/day were predictors of length of hospital stay F(2.46)=6.148; p=0.004; R2=0.211; as well as the cumulative energy deficit+birth weight+infused calories/kg/day (F=3.52; p<0.001; R2=0.422); cumulative energy deficit+calories infused/kg/day+fasting time for Enteral Nutrition (F=15.041; p<0.001; R2=0.474) were predictors of weight gain. The time to start enteral nutrition, gestational age and birth weight were inversely associated with the occurrence of necrotizing enterocolitis (β=-0.38; β=-0.198; β=-0.002). Early enteral nutrition predisposed to mortality (β=0.33). Gestational age, birth weight and calories infused/kg/day were inversely related to mortality (β=-0.442; β=-0.004; β=-0.08). Conclusions Considering the associations between indicators and outcomes, routine monitoring of the time to start enteral nutrition, energy adequacy, energy deficit and fasting time is recommended.

Predictors of length of hospital stay among preterm infants admitted to neonatal intensive care unit: Data from a multicentre collaborative network from India (INNC: Indian National Neonatal Collaborative)

AIM

Prediction of length of stay (LOS) among preterm neonates is important for counselling of parents and for assessing neonatal intensive care unit (NICU) census and economic burden. The aim of this study is to evaluate perinatal and postnatal factors that influence LOS in preterm infants (25-33 weeks of gestation) admitted to participating NICUs of Indian National Neonatal Collaborative (INNC).

METHODS

From the INNC database, the data which were prospectively entered using uniformed pre-defined criteria were analysed.

RESULTS

A total of 3095 infants were included from 12 centres. Every week decrease in gestation increased LOS by 9 days. The median LOS for infants with gestational age of 25, 26, 27, 28, 29, 30, 31, 32 and 33 weeks were 86, 70, 62, 52, 40, 30, 23, 16 and 10 days, respectively. On multivariate analysis, abnormal antenatal umbilical artery doppler, severe small for gestational age (SGA), requirement of resuscitation, respiratory distress syndrome (RDS), seizures, sepsis, necrotising enterocolitis (NEC), major malformations and bronchopulmonary dysplasia (BPD) increased LOS by 5.4 (3.5-7.4), 21.6 (19-23.9), 4.7 (3.3-6.1), 3 (1.7-4.3), 15.2 (8.5-22.1), 11.2 (9.1-13.2), 9.8 (5.2-14.4), 8.8 (4.4-13.3) and 5.6 (0.5-10.7) days, respectively.

CONCLUSIONS

Apart from lower gestation and birth weight, abnormal antenatal umbilical artery doppler, severe SGA, resuscitation need, major malformations, RDS, seizures, sepsis, NEC and BPD influenced LOS in preterm infants. In comparison with other networks or data from developed countries, LOS in our network was comparatively less for similar gestational age infants.

Development and use of an adjusted nurse staffing metric in the neonatal intensive care unit

OBJECTIVE

To develop a nurse staffing prediction model and evaluate deviation from predicted nurse staffing as a contributor to patient outcomes.

DATA SOURCES

Secondary data collection conducted 2017-2018, using the California Office of Statewide Health Planning and Development and the California Perinatal Quality Care Collaborative databases. We included 276 054 infants born 2008-2016 and cared for in 99 California neonatal intensive care units (NICUs).

STUDY DESIGN

Repeated-measures observational study. We developed a nurse staffing prediction model using machine learning and hierarchical linear regression and then quantified deviation from predicted nurse staffing in relation to health care-associated infections, length of stay, and mortality using hierarchical logistic and linear regression.

DATA COLLECTION METHODS

We linked NICU-level nurse staffing and organizational data to patient-level risk factors and outcomes using unique identifiers for NICUs and patients.

PRINCIPAL FINDINGS

An 11-factor prediction model explained 35 percent of the nurse staffing variation among NICUs. Higher-than-predicted nurse staffing was associated with decreased risk-adjusted odds of health care-associated infection (OR: 0.79, 95% CI: 0.63-0.98), but not with length of stay or mortality.

CONCLUSIONS

Organizational and patient factors explain much of the variation in nurse staffing. Higher-than-predicted nurse staffing was associated with fewer infections. Prospective studies are needed to determine causality and to quantify the impact of staffing reforms on health outcomes.

Development of data dictionary for neonatal intensive care unit: advancement towards a better critical care unit

Background

Critical care units (CCUs) with extensive use of various monitoring devices generate massive data. To utilize the valuable information of these devices; data are collected and stored using systems like clinical information system and laboratory information management system. These systems are proprietary, allow limited access to their database and, have the vendor-specific clinical implementation. In this study, we focus on developing an open-source web-based meta-data repository for CCU representing stay of the patient with relevant details.

Methods

After developing the web-based open-source repository named data dictionary (DD), we analyzed prospective data from 2 sites for 4 months for data quality dimensions (completeness, timeliness, validity, accuracy, and consistency), morbidity, and clinical outcomes. We used a regression model to highlight the significance of practice variations linked with various quality indicators.

Results

DD with 1555 fields (89.6% categorical and 11.4% text fields) is presented to cover the clinical workflow of a CCU. The overall quality of 1795 patient days data with respect to standard quality dimensions is 87%. The data exhibit 88% completeness, 97% accuracy, 91% timeliness, and 94% validity in terms of representing CCU processes. The data scores only 67% in terms of consistency. Furthermore, quality indicators and practice variations are strongly correlated (P < 0.05).

Conclusion

This study documents DD for standardized data collection in CCU. DD provides robust data and insights for audit purposes and pathways for CCU to target practice improvements leading to specific quality improvements.

Safety climate, safety climate strength, and length of stay in the NICU

Background

Safety climate is an important marker of patient safety attitudes within health care units, but the significance of intra-unit variation of safety climate perceptions (safety climate strength) is poorly understood. This study sought to examine the standard safety climate measure (percent positive response (PPR)) and safety climate strength in relation to length of stay (LOS) of very low birth weight (VLBW) infants within California neonatal intensive care units (NICUs).

Methods

Observational study of safety climate from 2073 health care providers in 44 NICUs. Consistent perceptions among a NICU’s respondents, i.e., safety climate strength, was determined via intra-unit standard deviation of safety climate scores. The relation between safety climate PPR, safety climate strength, and LOS among VLBW (< 1500 g) infants was evaluated using log-linear regression. Secondary outcomes were infections, chronic lung disease, and mortality.

Results

NICUs had safety climate PPRs of 66 ± 12%, intra-unit standard deviations 11 (strongest) to 23 (weakest), and median LOS 60 days. NICUs with stronger climates had LOS 4 days shorter than those with weaker climates. In interaction modeling, NICUs with weak climates and low PPR had the longest LOS, NICUs with strong climates and low PPR had the shortest LOS, and NICUs with high PPR (both strong and weak) had intermediate LOS. Stronger climates were associated with lower odds of infections, but not with other secondary outcomes.

Conclusions

Safety climate strength is independently associated with LOS and moderates the association between PPR and LOS among VLBW infants. Strength and PPR together provided better prediction than PPR alone, capturing variance in outcomes missed by PPR. Evaluations of NICU safety climate consider both positivity (PPR) and consistency of responses (strength) across individuals.

Estimating neonatal length of stay for babies born very preterm

OBJECTIVE

To predict length of stay in neonatal care for all admissions of very preterm singleton babies.

SETTING

All neonatal units in England.

PATIENTS

Singleton babies born at 24-31 weeks gestational age from 2011 to 2014. Data were extracted from the National Neonatal Research Database.

METHODS

Competing risks methods were used to investigate the competing outcomes of death in neonatal care or discharge from the neonatal unit. The occurrence of one event prevents the other from occurring. This approach can be used to estimate the percentage of babies alive, or who have been discharged, over time.

RESULTS

A total of 20 571 very preterm babies were included. In the competing risks model, gestational age was adjusted for as a time-varying covariate, allowing the difference between weeks of gestational age to vary over time. The predicted percentage of death or discharge from the neonatal unit were estimated and presented graphically by week of gestational age. From these percentages, estimates of length of stay are provided as the number of days following birth and corrected gestational age at discharge.

CONCLUSIONS

These results can be used in the counselling of parents about length of stay and the risk of mortality.

Sequential risk of depression in children born prematurely: A nationwide population- based analysis

BACKGROUND

Whether children born prematurely are at a high risk of depression is still unknown. The present study examined the risk of depression in children who were born prematurely, by analyzing a national cohort in Taiwan.

METHODS

All premature births between January 1, 2000, and December 31, 2010, by using the Taiwan National Health Insurance Research Database. A total of 21,478 preterm children and 85,903 full-term children were enrolled in this study. Sex, level of urbanization of residential area, and parental occupation were considered. We included participants who received a diagnosis of depression in more than two clinical visits or were hospitalized due to depression.

RESULTS

Preterm children had a 2.75-fold higher risk of depression than full-term children (95% confidence interval [CI] = 1.58-4.79, p < 0.001). Sex was not likely to be associated with depression in this study (p = 0.95). The lowest level of urbanization significantly contributed to the risk of depression in preterm children (adjusted hazard ratio = 6.8, 95% CI = 1.63-28.46, p < 0.01). Regarding parental occupation, preterm children whose parents had blue-collar and other occupations had a 3.4- and 6.06-fold higher risk of depression, respectively, compared with other children (blue-collar occupations: 95% CI = 1.04-11.15, p < 0.05; other occupations: 95% CI = 1.71-21.49, p < 0.01).

CONCLUSIONS

Preterm children had a 2.7-fold higher risk of depression than children born full-term. Early identification, timely psychiatric care, intervention strategies, and support for their families may reduce the complications of mental illness in preterm children.

Duration and Time Trends in Hospital Stay for Very Preterm Infants Differ Across European Regions

OBJECTIVES

To compare duration and changes over time in length of hospital stay for very preterm and extremely preterm infants in 10 European regions.

DESIGN

Two area-based cohort studies from the same regions in 2003 and 2011/2012.

SETTING

Ten regions from nine European countries.

PATIENTS

Infants born between 22 + 0 and 31 + 6 weeks of gestational age and surviving to discharge (Models of Organising Access to Intensive Care for Very Preterm Births cohort in 2003, n = 4,011 and Effective Perinatal Intensive Care in Europe cohort in 2011/2012, n = 4,336).

INTERVENTIONS

Observational study, no intervention.

MEASUREMENTS AND MAIN RESULTS

Maternal and infant characteristics were abstracted from medical records using a common protocol and length of stay until discharge was adjusted for case-mix using negative binomial regression. Mean length of stay was 63.6 days in 2003 and varied from 52.4 to 76.5 days across regions. In 2011/2012, mean length of stay was 63.1 days, with a narrower regional range (54.0-70.1). Low gestational age, small for gestational age, low 5-minute Apgar score, surfactant administration, any surgery, and severe neonatal morbidities increased length of stay. Infant characteristics explained some of the differences between regions and over time, but large variations remained after adjustment. In 2011/2012, mean adjusted length of stay ranged from less than 54 days in the Northern region of the United Kingdom and Wielkopolska, Poland to over 67 days in the Ile-de-France region of France and the Eastern region of the Netherlands. No systematic decrease in very preterm length of stay was observed over time after adjustment for patient case-mix.

CONCLUSIONS

A better understanding of the discharge criteria and care practices that contribute to the wide differences in very preterm length of stay across European regions could inform policies to optimize discharge decisions in terms of infant outcomes and health system costs.

Comparison of Collaborative Versus Single-Site Quality Improvement to Reduce NICU Length of Stay

BACKGROUND

There is unexplained variation in length of stay (LOS) across NICUs, suggesting that there may be practices that can optimize LOS.

METHODS

Three groups of NICUs in the California Perinatal Quality Care Collaborative were followed: (1) collaborative centers participating in an 18-month collaborative quality improvement project to optimize LOS for preterm infants; (2) individual centers aiming to optimize LOS; and (3) nonparticipants. Our aim in the collaborative project was to decrease postmenstrual age (PMA) at discharge for infants born between 27 + 0 and <32 weeks' gestational age by 3 days. A secondary outcome was "early discharge," the proportion of infants discharged from the hospital before 36 + 5 weeks' PMA. The balancing measure of readmissions within 72 hours was tracked for the collaborative group.

RESULTS

From 2013 to 2015, 8917 infants were cared for in 20 collaborative NICUs, 19 individual project NICUs, and 71 nonparticipants. In the collaborative group, the PMA at discharge decreased from 37.8 to 37.5 weeks (P = .02), and early discharge increased from 31.6% to 41.9% (P = .006). The individual project group had no significant change. Nonparticipants had a decrease in PMA from 37.5 to 37.3 weeks (P = .01) but no significant change in early discharge (39.8% to 43.6%; P = .24). There was no significant change in readmissions over time in the collaborative group.

CONCLUSIONS

A structured collaborative project that was focused on optimizing LOS led to a 3-day decrease in LOS and was more effective than individualized quality improvement efforts.

Improving Uptake of Key Perinatal Interventions Using Statewide Quality Collaboratives

Regional and statewide quality improvement collaboratives have been instrumental in implementing evidence-based practices and facilitating quality improvement initiatives within neonatology. Statewide collaboratives emerged from larger collaborative organizations, like the Vermont Oxford Network, and play an increasing role in collecting and interpreting data, setting priorities for improvement, disseminating evidence-based clinical practice guidelines, and creating regional networks for synergistic learning. In this review, we highlight examples of successful statewide collaborative initiatives, as well as challenges that exist in initiating and sustaining collaborative efforts.

Impact of extremely low-birth-weight status on risk and resilience for depression and anxiety in adulthood

BACKGROUND

Preterm birth is associated with an increased risk of depression and anxiety, but it is not known if this is due to greater exposure to risk, or if perinatal adversity amplifies the impact of traditional risk factors. This study sought to determine if exposure to perinatal adversity modifies associations between traditional risk and resilience factors and depression and anxiety in adulthood.

METHODS

A sample of 142 extremely low-birth-weight (ELBW < 1,000 g) survivors and 133 sociodemographically matched normal birth weight (NBW) control participants was followed longitudinally to 22-26 years of age. Separate postnatal risk and resilience scales were created using eight risk and seven resilience factors, respectively. Depression and anxiety were assessed using the internalizing scale of the Young Adult Self-Report (YASR). This scale was also dichotomized at the 90th percentile to define clinically significant psychopathology.

RESULTS

While the average number of risk exposures did not differ between groups, ELBW survivors were more susceptible to risk than NBW control participants. For the ELBW group, each additional risk factor resulted in a 2-point increase in internalizing scores, and two and a half times the odds of clinically significant internalizing symptoms (OR = 2.47, 95% CI = 1.63, 3.76). The protective effect of resiliency factors was also blunted among ELBW survivors.

CONCLUSIONS

Extremely low-birth-weight survivors may be more sensitive to traditional risk factors for psychopathology and less protected by resiliency factors. Intervention strategies aimed at preventing or reducing exposure to traditional childhood risk factors for psychopathology may reduce the burden of mental illness in adult survivors of prematurity.

What factors predict length of stay in a neonatal unit: a systematic review

OBJECTIVE

In the UK, 1 in 10 babies require specialist neonatal care. This care can last from hours to months depending on the need of the baby. The increasing survival of very preterm babies has increased neonatal care resource use. Evidence from multiple studies is crucial to identify factors which may be important for predicting length of stay (LOS). The ability to predict LOS is vital for resource planning, decision-making and parent counselling. The objective of this review was to identify which factors are important to consider when predicting LOS in the neonatal unit.

DESIGN

A systematic review was undertaken which searched MEDLINE, EMBASE and Scopus for papers from 1994 to 2016 (May) for research investigating prediction of neonatal LOS. Strict inclusion and exclusion criteria were applied. Quality of each study was discussed, but not used as a reason for exclusion from the review.

MAIN OUTCOME MEASURE

Prediction of LOS in the neonatal unit.

RESULTS

9 studies were identified which investigated the prediction of neonatal LOS indicating a lack of evidence in the area. Inherent factors, particularly birth weight, sex and gestational age allow for a simple and objective prediction of LOS, which can be calculated on the first day of life. However, other early occurring factors may well also be important and estimates may need revising throughout the baby's stay in hospital.

CONCLUSIONS

Predicting LOS is vital to aid the commissioning of services and to help clinicians in their counselling of parents. The lack of evidence in this area indicates a need for larger studies to investigate methods of accurately predicting LOS.