Information technology infrastructure, quality improvement and research: the UK National Neonatal Research Database

Paediatric intensive care admissions of preterm children born <32 weeks gestation: a national retrospective cohort study using data linkage

OBJECTIVE

Survival of babies born very preterm (<32 weeks gestational age) has increased, although preterm-born children may have ongoing morbidity. We aimed to investigate the risk of admission to paediatric intensive care units (PICUs) of children born very preterm following discharge home from neonatal care.

DESIGN

Retrospective cohort study, using data linkage of National Neonatal Research Database and the Paediatric Intensive Care Audit Network datasets.

SETTING

All neonatal units and PICUs in England and Wales.

PATIENTS

Children born very preterm between 1 January 2013 and 31 December 2018 and admitted to neonatal units.

MAIN OUTCOME MEASURES

Admission to PICU after discharge home from neonatal care, before 2 years of age.

RESULTS

Of the 40 690 children discharged home from neonatal care, there were 2308 children (5.7%) with at least one admission to PICU after discharge. Of these children, there were 1901 whose first PICU admission after discharge was unplanned.The percentage of children with unplanned PICU admission varied by gestation, from 10.2% of children born <24 weeks to 3.3% born at 31 weeks.Following adjustment, unplanned PICU admission was associated with lower gestation, male sex (adjusted OR (aOR) 0.79), bronchopulmonary dysplasia (aOR 1.37), necrotising enterocolitis requiring surgery (aOR 1.39) and brain injury (aOR 1.42). For each week of increased gestation, the aOR was 0.90.

CONCLUSIONS

Most babies born <32 weeks and discharged home from neonatal care do not require PICU admission in the first 2 years. The odds of unplanned admissions to PICU were greater in the most preterm and those with significant neonatal morbidity.

A clinical informatics approach to bronchopulmonary dysplasia: current barriers and future possibilities

Bronchopulmonary dysplasia (BPD) is a complex, multifactorial lung disease affecting preterm neonates that can result in long-term pulmonary and non-pulmonary complications. Current therapies mainly focus on symptom management after the development of BPD, indicating a need for innovative approaches to predict and identify neonates who would benefit most from targeted or earlier interventions. Clinical informatics, a subfield of biomedical informatics, is transforming healthcare by integrating computational methods with patient data to improve patient outcomes. The application of clinical informatics to develop and enhance clinical therapies for BPD presents opportunities by leveraging electronic health record data, applying machine learning algorithms, and implementing clinical decision support systems. This review highlights the current barriers and the future potential of clinical informatics in identifying clinically relevant BPD phenotypes and developing clinical decision support tools to improve the management of extremely preterm neonates developing or with established BPD. However, the full potential of clinical informatics in advancing our understanding of BPD with the goal of improving patient outcomes cannot be achieved unless we address current challenges such as data collection, storage, privacy, and inherent data bias.

Place of birth and postnatal transfers in infants with congenital diaphragmatic hernia in England and Wales: a descriptive observational cohort study

OBJECTIVE

To describe clinical pathways for infants with congenital diaphragmatic hernia (CDH) and short-term outcomes.

DESIGN

Retrospective observational cohort study using the UK National Neonatal Research Database (NNRD).

PATIENTS

Babies with a diagnosis of CDH admitted to a neonatal unit in England and Wales between 2012 and 2020.

MAIN OUTCOME MEASURES

Clinical pathways defined by place of birth (with or without colocated neonatal and surgical facilities), transfers, clinical interventions, length of hospital stay and discharge outcome.

RESULTS

There were 1319 babies with a diagnosis of CDH cared for in four clinical pathways: born in maternity units with (1) colocated tertiary neonatal and surgical units ('neonatal surgical units'), 50% (660/1319); (2) designated tertiary neonatal unit and transfer to stand-alone surgical centre ('tertiary designated'), 25% (337/1319); (3) non-designated tertiary neonatal unit ('tertiary non-designated'), 7% (89/1319); or (4) non-tertiary unit ('non-tertiary'), 18% (233/1319)-the latter three needing postnatal transfers. Infant characteristics were similar for infants born in neonatal surgical and tertiary designated units. Excluding 149 infants with minimal data due to early transfer (median (IQR) 2.2 (0.4-4.5) days) to other settings, survival to neonatal discharge was 73% (851/1170), with a median (IQR) stay of 26 (16-44) days.

CONCLUSIONS

We found that half of the babies with CDH were born in hospitals that did not have on-site surgical services and required postnatal transfer. Similar characteristics between infants born in neonatal surgical units and tertiary designated units suggest that organisation rather than infant factors influence place of birth. Future work linking the NNRD to other datasets will enable comparisons between care pathways.

Preterm Formula, Fortified or Unfortified Human Milk for Very Preterm Infants, the PREMFOOD Study: A Parallel Randomised Feasibility Trial

OBJECTIVE

Uncertainty exists regarding optimal supplemental diet for very preterm infants if the mother's own milk (MM) is insufficient. We evaluated feasibility for a randomised controlled trial (RCT) powered to detect important differences in health outcomes.

METHODS

In this open, parallel, feasibility trial, we randomised infants 25+0-31+6 weeks of gestation by opt-out consent to one of three diets: unfortified human milk (UHM) (unfortified MM and/or unfortified pasteurised human donor milk (DM) supplement), fortified human milk (FHM) (fortified MM and/or fortified DM supplement), and unfortified MM and/or preterm formula (PTF) supplement from birth to 35+0 weeks post menstrual age. Feasibility outcomes included opt-outs, adherence rates, and slow growth safety criteria. We also obtained anthropometry, and magnetic resonance imaging body composition data at term and term plus 6 weeks (opt-in consent).

RESULTS

Of 35 infants randomised to UHM, 34 to FHM, and 34 to PTF groups, 21, 19, and 24 infants completed imaging at term, respectively. Study entry opt-out rate was 38%; 6% of parents subsequently withdrew from feeding intervention. Two infants met predefined slow weight gain thresholds. There were no significant between-group differences in term total adipose tissue volume (mean [SD]: UHM: 0.870 L [0.35 L]; FHM: 0.889 L [0.31 L]; PTF: 0.809 L [0.25 L], p = 0.66), nor in any other body composition measure or anthropometry at either timepoint.

CONCLUSIONS

Randomisation to UHM, FHM, and PTF diets by opt-out consent was acceptable to parents and clinical teams, associated with safe growth profiles and no significant differences in body composition. Our data provide justification to proceed to a larger RCT.

Study protocol: Generation Victoria (GenV) special care nursery registry

Introduction

Newborn babies who require admission for specialist care can experience immediate and sometimes lasting impacts. For babies admitted to special care nurseries (SCN), there is no dataset comparable to that of the Australian and New Zealand Neonatal Network (ANZNN), which has helped improve the quality and consistency of neonatal intensive care through standardised data collection.

Objectives

We aim to establish a proof-of-concept, Victoria-wide registry of babies admitted to SCN, embedded within the whole-of-Victoria Generation Victoria (GenV) cohort.

Methods

This prototype registry is a depth sub-cohort nested within GenV, targeting all babies born in Victoria from Oct-2021 to Oct-2023. Infants admitted to SCN are eligible. The minimum dataset will be harmonised with ANZNN for common constructs but also include SCN-only items, and will cover maternal, antenatal, newborn, respiratory/respiratory support, cardiac, infection, nutrition, feeding, cerebral and other items. As well as the dataset, this protocol outlines the anticipated cohort, timeline for this registry, and how this will serve as a resource for longitudinal research through its integration with the GenV longitudinal cohort and linked datasets.

Conclusion

The registry will provide the opportunity to better understand the health and future outcomes of the large and growing cohort of children that require specialist care after birth. The data would generate translatable evidence and could lay the groundwork for a stand-alone ongoing clinical quality registry post-GenV.

Pilot feasibility study of a digital technology approach to the systematic electronic capture of parent-reported data on cognitive and language development in children aged 2 years

BACKGROUND

The assessment of language and cognition in children at risk of impaired neurodevelopment following neonatal care is a UK standard of care but there is no national, systematic approach for obtaining these data. To overcome these challenges, we developed and evaluated a digital version of a validated parent questionnaire to assess cognitive and language development at age 2 years, the Parent Report of Children's Abilities-Revised (PARCA-R).

METHODS

We involved clinicians and parents of babies born very preterm who received care in north-west London neonatal units. We developed a digital version of the PARCA-R questionnaire using standard software. Following informed consent, parents received automated notifications and an invitation to complete the questionnaire on a mobile phone, tablet or computer when their child approached the appropriate age window. Parents could save and print a copy of the results. We evaluated ease of use, parent acceptability, consent for data sharing through integration into a research database and making results available to the clinical team.

RESULTS

Clinical staff approached the parents of 41 infants; 38 completed the e-registration form and 30 signed the e-consent. The digital version of the PARCA-R was completed by the parents of 21 of 23 children who reached the appropriate age window. Clinicians and parents found the system easy to use. Only one parent declined permission to integrate data into the National Neonatal Research Database for approved secondary purposes.

DISCUSSION

This electronic data collection system and associated automated processes enabled efficient systematic capture of data on language and cognitive development in high-risk children, suitable for national delivery at scale.

Nutrition for the micro preemie: Beyond milk

Nutritional support is a fundamental component of the care of the extremely preterm infant, including the "micro preemie" (here defined as a baby born weighing less than 500 g), but goes beyond considerations of milk as a food. This is because milk from an infant's own mother, unlike currently available substitutes, additionally provides invaluable non-nutritive benefits. Nutritional support requires suitable devices or techniques to administer nutrients enterally or intravenously, products shown to be safe in preterm populations, and efficacy demonstrated in respect of important functional outcomes. Sadly, preterm feeding remains characterised by a deficit of evidence. In this chapter, we will briefly describe the history of preterm nutrition, discuss current enteral and parenteral practice, important evidence gaps, a summary of approaches for evaluating nutritional practice, and key considerations for future endeavour. Our discussion refers to all extremely preterm infants and it not confined to the micro preemie.

Birthweight and patterns of postnatal weight gain in very and extremely preterm babies in England and Wales, 2008-19: a cohort study

BACKGROUND

Intrauterine and postnatal weight are widely regarded as biomarkers of fetal and neonatal wellbeing, but optimal weight gain following preterm birth is unknown. We aimed to describe changes over time in birthweight and postnatal weight gain in very and extremely preterm babies, in relation to major morbidity and healthy survival.

METHODS

In this cohort study, we used whole-population data from the UK National Neonatal Research Database for infants below 32 weeks gestation admitted to neonatal units in England and Wales between Jan 1, 2008, and Dec 31, 2019. We used non-linear Gaussian process to estimate monthly trends, and Bayesian multilevel regression to estimate unadjusted and adjusted coefficients. We evaluated birthweight; weight change from birth to 14 days; weight at 36 weeks postmenstrual age; associated Z scores; and longitudinal weights for babies surviving to 36 weeks postmenstrual age with and without major morbidities. We adjusted birthweight for antenatal, perinatal, and demographic variables. We additionally adjusted change in weight at 14 days and weight at 36 weeks postmenstrual age, and their Z scores, for postnatal variables.

FINDINGS

The cohort comprised 90 817 infants. Over the 12-year period, mean differences adjusted for antenatal, perinatal, demographic, and postnatal variables were 0 g (95% compatibility interval -7 to 7) for birthweight (-0·01 [-0·05 to 0·03] for change in associated Z score); 39 g (26 to 51) for change in weight from birth to 14 days (0·14 [0·08 to 0·19] for change in associated Z score); and 105 g (81 to 128) for weight at 36 weeks postmenstrual age (0·27 [0·21 to 0·33] for change in associated Z score). Greater weight at 36 weeks postmenstrual age was robust to additional adjustment for enteral nutritional intake. In babies surviving without major morbidity, weight velocity in all gestational age groups stabilised at around 34 weeks postmenstrual age at 16-25 g per day along parallel percentile lines.

INTERPRETATION

The birthweight of very and extremely preterm babies has remained stable over 12 years. Early postnatal weight loss has decreased, and subsequent weight gain has increased, but weight at 36 weeks postmenstrual age is consistently below birth percentile. In babies without major morbidity, weight velocity follows a consistent trajectory, offering opportunity to construct novel preterm growth curves despite lack of knowledge of optimal postnatal weight gain.

FUNDING

UK Medical Research Council.

Incorporating parent, former patient and clinician perspectives in the design of a national UK double-cluster, randomised controlled trial addressing uncertainties in preterm nutrition

Background

Comparative effectiveness randomised controlled trials are powerful tools to resolve uncertainties in existing treatments and care processes. We sought parent and patient perspectives on the design of a planned national, double-cluster randomised controlled trial (COLLABORATE) to resolve two longstanding uncertainties in preterm nutrition.

Methods

We used qualitative focus groups and interviews with parents, former patients and clinicians. We followed the Consolidated Criteria for Reporting Qualitative Research checklist and conducted framework analysis, a specific methodology within thematic analysis.

Results

We identified support for the trial's methodology and vision, and elicited themes illustrating parents' emotional needs in relation to clinical research. These were: relieving the pressure on mothers to breastfeed; opt-out consent as reducing parent stress; the desire for research to be a partnership between clinicians, parents and researchers; the value of presenting trial information in a collaborative tone; and in a format that allows assimilation by parents at their own pace. We identified anxiety and cognitive dissonance among some clinicians in which they recognised the uncertainties that justify the trial but felt unable to participate because of their strongly held views.

Conclusions

The early involvement of parents and former patients identified the centrality of parents' emotional needs in the design of comparative effectiveness research. These insights have been incorporated into trial enrolment processes and information provided to participants. Specific outputs were a two-sided leaflet providing very brief as well as more detailed information, and use of language that parents perceive as inclusive and participatory. Further work is warranted to support clinicians to address personal biases that inhibit trial participation.

Identification of variation in nutritional practice in neonatal units in England and association with clinical outcomes using agnostic machine learning

We used agnostic, unsupervised machine learning to cluster a large clinical database of information on infants admitted to neonatal units in England. Our aim was to obtain insights into nutritional practice, an area of central importance in newborn care, utilising the UK National Neonatal Research Database (NNRD). We performed clustering on time-series data of daily nutritional intakes for very preterm infants born at a gestational age less than 32 weeks (n = 45,679) over a six-year period. This revealed 46 nutritional clusters heterogeneous in size, showing common interpretable clinical practices alongside rarer approaches. Nutritional clusters with similar admission profiles revealed associations between nutritional practice, geographical location and outcomes. We show how nutritional subgroups may be regarded as distinct interventions and tested for associations with measurable outcomes. We illustrate the potential for identifying relationships between nutritional practice and outcomes with two examples, discharge weight and bronchopulmonary dysplasia (BPD). We identify the well-known effect of formula milk on greater discharge weight as well as support for the plausible, but insufficiently evidenced view that human milk is protective against BPD. Our framework highlights the potential of agnostic machine learning approaches to deliver clinical practice insights and generate hypotheses using routine data.

Facilitating quality improvement through routinely recorded clinical information

In this chapter, I discuss how quality improvement activities can be facilitated using routinely available clinical data. I begin by providing a definition of quality improvement and quality healthcare, and identifying what I consider key components and their information requirements. I suggest that quality improvement can be made simpler, more efficient and less labour and resource intensive by focussing on outcomes. Finally, I provide pointers for developing resources of routinely available clinical information.

Adult outcomes after preterm birth

Extremely preterm birth reflects global disruption of the third trimester environment. Young adults born preterm have an adverse cardiovascular and metabolic health profile, together with molecular evidence of accelerated ageing and a reduced life expectancy. The underlying mechanism for these observations is unknown. This review summarises recent evidence of the lifetime effects of preterm birth and highlights the risks survivors face.

Improving the Efficiency and Impact of Clinical Research: A Game Changer for 21st Century Neonatology

Every clinician is aware of the many uncertainties that exist in everyday clinical care. These contribute to variation and inequity in outcomes and pose dangers to patient wellbeing and safety. Evidence generation is still too slow, too expensive, too much left to chance, too ad hoc, and wholly inadequate. Modern technologies can drive faster, more efficient evidence generation and implementation of findings. However, professional and public buy-in are also needed for success; in short, a new conceptual framework aimed at reducing uncertainties effectively, efficiently, and incrementally in clinical practice is required. Currently, much-needed research to reduce practice uncertainties is often never done, or conducted in ways that are inefficient or lack impact. The consequence is poor patient care and abrogation of the cardinal duty of doctors to "first, do no harm." Research is efficient if high quality, conducted rapidly, at reasonable cost, with minimal burden on investigators and participants. Research has impact if outcomes are incorporated into evidence syntheses, and robust conclusions are implemented into practice without delay. Here, I will discuss ways that build upon modern thinking and new technologies to improve the efficiency and impact of clinical research.