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

Modi, Neena

doi:10.21037/tp.2019.07.08

Cited by 17 publications

(14 citation statements)

References 36 publications

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“…We used the National Neonatal Research Database (NNRD) 42 , a mature ongoing longitudinal registry that commenced in 2007 and that contains detailed clinical information extracted from the electronic patient records of all admissions to neonatal units in England, Wales and Scotland 43 . Out of nearly one million infants and 12 million daily records of care, we selected all very and extremely preterm infants, defined as born below a gestational age of 32 weeks.…”

Section: Methodsmentioning

confidence: 99%

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

Greenbury

Ougham

et al. 2021

Sci Rep

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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.

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Section: Methodsmentioning

confidence: 99%

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

Greenbury

Ougham

et al. 2021

Sci Rep

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“…COLLABORATE offers a pragmatic response to these uncertainties. COLLABO-RATE will use data from the National Neonatal Research Database to minimise clinical burden, [4][5][6] and evaluate 2 year language and cognitive outcomes with a parentcompleted questionnaire, the Parent Report of Children's Abilities-Revised. 7 These clinical uncertainties, which affect the care provided to babies as well as the information provided to families, present an opportunity to understand how parents of very preterm babies can improve the recruitment materials for the COLLABORATE trial and clarify the acceptability of consent methods, as well as compare their views and reactions with those of clinicians.…”

Section: What This Study Adds?mentioning

confidence: 99%

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

Lammons

Moss

Battersby

et al. 2021

bmjpo

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BackgroundComparative 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.MethodsWe 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.ResultsWe 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.ConclusionsThe 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.

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“…There are now well-established electronic databases that capture individual clinical data on every baby born preterm. For example, the National Neonatal Research Database in the UK 52 has complete population coverage of all very preterm and sick newborn infants. It was established in 2007 and, to date, contains clinical information on approximately one million infants, such as demographic and anthropometric details, daily interventions throughout the neonatal admission, diagnoses and outcomes and follow-up health status at the age of 2 years.…”

Section: Future Researchmentioning

confidence: 99%

Adult outcomes after preterm birth

Prior

Modi

2020

Postgraduate Medical Journal

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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.

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

Cited by 17 publications

References 36 publications

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

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

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

Adult outcomes after preterm birth

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