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

Abstract

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.

Introduction

In Australia, around 18% [1] of newborn babies are cared for in neonatal intensive care units (NICU) or in special care nurseries (SCN) that cater to lower-intensity conditions, including post-NICU care. The main, but not sole, reason for admission is preterm birth (>37 weeks), which affects one in 10 babies worldwide (15 million babies per year). The number of preterm births continues to rise [2], and is the leading cause of morbidity and mortality in children under five years of age worldwide [3].

Care for babies in SCNs is guided by a weaker evidence base than is the case for NICUs. Most research has focused on best care practices and outcomes for very preterm babies (<32 weeks, 2,500 babies/year in Australia) and specific groups such as those requiring surgery. However, collectively these babies comprise less than 10% of newborn admissions for specialist care [1, 4, 5]. The evidence base is much smaller regarding the care and outcomes of moderate-late preterm (32 to 36 weeks) or term (>37 weeks) babies that receive specialist care in SCNs, who comprise 80–90% of neonatal admissions in Australia [6, 7]. Problems experienced by these babies include respiratory distress, hypoglycaemia, jaundice, seizures, temperature instability and feeding issues [4]. Their ongoing care also incurs significant health (including rehospitalisation) and societal costs [8].

Registry-based research can improve outcomes for high-risk groups. Clinical quality registries can monitor and benchmark outcomes through systematic and ongoing standardised data collection [9]. They enable identification of clinical practice variation and its effect on patient outcomes [9, 10]. Well-constructed registries drive continuous improvements in patient outcomes and reduce variation through better adherence to guideline-recommended care [10, 11]. They provide a platform to implement new treatments and pragmatic trials [9]. Thus, the highest-risk babies cared for in the state’s five NICUs share largely harmonised care pathways and, through the well-established Australia and New Zealand Neonatal Network (ANZNN) registry, data collection [12]. Additionally, due to their large size, registries provide a valuable resource for researchers to study rare events and small effect sizes that may incrementally improve care over time.

However, there is no coordinated data collection for the less-sick NICU babies who do not meet ANZNN criteria, or for any babies admitted to public and private SCNs across each state. This is not unique to Australia; to our knowledge, the UK national neonatal research database (NNRD) is the only such platform internationally. To date, NNRD contains information on approximately one million infants with approximately 25,000 new patients added each quarter [13]. Moreover, access to post-discharge health and developmental surveillance data (essential to understanding impacts of healthcare beyond the admission itself) is limited in Victoria and throughout Australia. This hampers translatable evidence (prediction, prevention, treatments, services) to improve the care and future wellbeing and health of this much larger group of babies. Therefore, a registry for SCN babies will provide much-needed evidence to develop better models of care and state-wide and nation-wide guidelines for sick newborns.

Creating a new clinical quality registry involving 40 SCNs across Victoria without funding is challenging. Here, we have an opportunity to develop and test a registry with Generation Victoria (GenV) [14, 15], a population whole-of-state cohort targeting all Victorian babies born from October 2021 to October 2023 and their parents. GenV thus offers unique infrastructure to support population-based data collection for newborns requiring SCN admission. While a depth sub-cohort of GenV, GenV’s state wide nature would effectively create an SCN registry within GenV. GenV’s 2-year recruitment period provides a window within which to set up the methods and outcomes for a registry and consider whether it could transition to a stand-alone ongoing registry in subsequent years. This protocol outlines the anticipated cohort, dataset, and timeline and how this registry will also serve as a resource for longitudinal research through its integration with the GenV cohort and linked datasets.

Methods and analysis

Study design

This study is nested within GenV, which aims to create parallel whole-of-state birth and parent cohorts for discovery and interventional research [15]. GenV is open to all newborns and their parents from all 58 birthing hospitals in the state of Victoria from October 2021 for a period of two full years; thus, the sampling frame is all ~150,000 births amongst the full state population ~6.5 million), of whom we would expect 12,500 to be admitted in each year to an SCN [1, 16]. The GenV cohort design comprises four elements: 1) Consent soon after birth to follow the child and parent/s indefinitely until study end or withdrawal, 2) Retrospective and prospective linkage to clinical and administrative datasets, 3) Universal and clinical biosamples, and 4) GenV-collected demographic, risk, geographic and outcomes data that are not available in linked datasets or existing biosamples.

One goal of GenV is to include more detailed clinical data for higher risk newborns within the cohort. Therefore, GenV is establishing a depth sub-cohort within GenV (GenV SCN registry) comprising babies admitted to all 40 SCNs across Victoria (Figure 1). This will complement the existing ANZNN registry, which already collects data for most babies admitted to NICUs.

Figure 1: How SCN sub-cohort integrates with the GenV and the potential state-wide SCN registry. SCN = special care nursery; GenV = Generation Victoria.

Participant recruitment

The Victorian Infant Hearing Screen Program (VIHSP) creates a daily census of all births in Victoria. Drawing on this census, GenV recruiters visit the parent(s)/guardian and infant soon after birth (or once the child is >34 weeks gestational age and not ventilated) and invite them to participate in GenV. The parent(s) choose(s) whether or not to participate voluntarily and free from coercion. If willing, an electronic consent (eConsent) process takes place for their own and their child’s overall participation in GenV, including both bundled and item-by-item components of the consent. Those who are missed or initially decline can join later via virtual or self-guided recruitment.

Participant selection

Inclusion criteria

This registry aims to include all babies admitted to Victoria’s 40 SCNs and recruited to GenV. Exclusion criteria: This registry will not include data for the 2,500 NICU babies per year eligible for ANZNN registry inclusion, i.e. babies who are <32 weeks’ gestation, <1500 g birthweight, ventilated for >4 hrs or those that received therapeutic hypothermia or major surgery. Estimated number: This will depend on the uptake into GenV, which is not yet known; we estimate the sampling frame to be around 23,000 children ((14,000–2,500) x2). As this is an opt-in process with informed consent (due to collection of biosamples and extended data linkage) uptake is likely to be lower than for the opt-out UK national neonatal research database (uptake rate around 96%). This in itself will provide important knowledge for future registries.

Minimum dataset and data extraction form

A GenV Newborns Working Group was established in 2019 to advise on opportunities and directions relating to newborn research in the GenV cohort, which has to date included this protocol and minimum dataset. The group comprises experts from multiple disciplines involved in newborn care, policy, research, and data collection and the neonatal/paediatric leads at hospitals with NICUs and SCNs. As GenV moves from recruitment to data management and release, composition of this group will evolve to potentially include all the principal investigators of studies that include participants from both GenV and the study itself (where a data sharing agreement is in place), representatives from the Australia and New Zealand Neonatal Network, and health care service providers. The composition of the working group will be reviewed annually, and with input from consumers and other end-users. The group meets 4 times/year to discuss progress of the project, any challenges or barriers to timely completion, and delivery of key performance indicators.

The minimum dataset was defined in the following steps:

1) In order to harmonise with the ANZNN dataset, our starting point was ANZNN data items that are relevant to babies in SCNs and not already collected by GenV directly or through data linkage with Victorian Perinatal Data Collection (VPDC).

2) The items unique to the ANZNN dataset were reviewed for relevance with neonatologist Professor Jeanie Cheong (Chair, GenV Newborns Working Group) and additional items relevant to SCN care added.

3) The items were circulated to the GenV Newborns Working Group for feedback and additional suggestions.

4) The expert feedback led to the final proposed SCN registry minimum dataset in Table 1, from which we developed the SCN Registry Data Extraction Form (Appendix 1).

Table 1: Proposed SCN registry minimum data set.

Maternal

Previous preterm birth

Antenatal

Maternal antibiotics in labour

Antenatal corticosteroids

Baby and birth

Date and time of birth

1st SCN admission (date, time and admitted from)

Intubated at resuscitation

Temperature at admission

Base excess after birth

Cord lactate and first lactate

Hypoxic-ischaemic encephalopathy

Seizures

Respiratory

Main indication for respiratory support

Surfactant

Method of administration of first dose of surfactant

Date and time of surfactant first given

Numbers of doses of surfactant

Air leak requiring drainage

Date and time of first drainage of pulmonary air leak

Respiratory support

IPPV (intermittent positive pressure ventilation)

Date and time intubated for ongoing ventilation

Date and time of final extubation from mechanical ventilation

Remain ventilated/ongoing ventilation at final discharge

Nasal CPAP (continuous positive airway pressure)

Date and time of initiation of nasal CPAP

Date and time of final cessation of nasal CPAP

Remain nasal CPAP at final discharge

Nasal high flow

Date and time of initiation of nasal high flow

Date and time of final cessation of nasal high flow

Remain nasal high flow at final discharge

Cardiac

Patent ductus arteriosus

Pharmacological treatment for patent ductus arteriosus

Infection

Probiotics

Infection (type and date of specimen)

Antibiotics/antiviral (name, date and time)

Nutrition

Parenteral nutrition

Date and time of initiation

Date and time of cessation

Remain parenteral nutrition at final discharge

Feeding

Breast milk feeding at onset of enteral feeds

Donor breast milk in any quantity

Breast milk (any) at discharge to home

IVH and cranial ultrasound

Left and right IVH

Cerebellar haemorrhage

6-week head ultrasound

Other suggested items

Hypoglycaemia

Lowest blood glucose + date and time

Treatment

Signs

Neonatal abstinence syndrome

Maternal medication/substance use

Treatment

Jaundice

Highest total bilirubin (level + test date and time)

Treatment

Vitamin K given

Final destination from this hospital

Transferred to another hospital

Death

Discharge to home

How many admissions altogether to this special care nursery (SCN)?

Date of 2nd SCN admission and discharge

Date of 3rd SCN admission and discharge

Proposed data collection process and tools

The proposed data collection process comprises the following steps:

1) GenV-hospital authorisation and agreement with each site (see Ethics and Governance, below).

2) GenV data scientist creates a modified Australian Statistical Linkage Key (SLK-581) in GenV dataset and shares the keys with a hospital using GenV Owncloud account.

3) Designated hospital staff (in departments such as Health Information Services, Performance Units, Medical Records on a hospital-by-hospital basis) creates SLK-581 in hospital’s dataset, undertakes matching and returns to GenV the linkage outcome (linked or not linked). Our pilot study drew on a one-year (births from 5 December 2020–31 December 2021) cohort for a single Australian birthing hospital selected as GenV’s Vanguard on the basis of its large size and ethnically and socioeconomically diverse patient base. For 1819 consented mother-baby pairs and 58 additional babies (whose mothers were not themselves participating), approximately 93% of participants were linked using SLK-581 [17].

4) GenV data scientist prepares and transfers minimum personally identifiable information (PII) of unlinked GenV participants in step (3) to the clinical sites to enable another attempt of matching. The participants’ UR numbers will be used to assist with matching where this is available to GenV.

5) Hospital data staff undertakes the matching of unlinked participants and then returns to GenV the original PII of unlinked GenV participants and linkage outcome (linked or not linked). According to our pilot study at one hospital, approximately 3–4% of participants could be further linked [18].

6) GenV data scientist returns a final list of linked participants to the hospital.

7) Automated extraction of SCN variables into an Excel spreadsheet by designated authorised hospital staff from a combination of (a) hospital administrative datasets prepared for the Victorian Admitted Episodes Dataset (VAED) and Victorian Emergency Minimum Dataset (VEMD), (b) the Birthing Outcomes System (BOS), in which all Victorian birthing hospitals record standardised maternity and newborn data, and (c) the site’s Electronic Medical Record (EMR) if used.

8) For any remaining data not retrieved via these automated routes, GenV staff with an honorary site appointment to undertake manual EMR and/or paper extraction into REDCap.

9) The hospital to transfer the retrieved SCN data to GenV via a secured architecture solution provided by GenV.

Engagement with SCNs

This work is advised by the GenV Newborns Working Group. Clinical site engagement is essential to success, including authorisation from Heads/Directors of the clinical sites for data extraction from neonatal unit records. Therefore, we will send an introductory letter to the Heads/Directors of SCNs to introduce the concept of GenV SCN registry and request general support of the intended data collection. Each site will complete a site assessment survey regarding number and flow of admissions, feasibility of extracting the proposed dataset and the form (paper/electronic) of its medical records. Their feedback will enable potential issues to be raised and processes to be fine-tuned. The following will be vital to mitigate the potential risk of non-support from key stakeholders at SCNs: early engagement, a strong value proposition, identifying a key contact person at each site, and regular communication between the project team and service teams. Between-site process variations in data extraction could reduce data consistency and thus value; to mitigate this risk, we will develop a clear overarching data architecture and flows that are consistent yet flexible across all sites.

Timeline

Figure 2 provides an overview of the protocol timeline. The first stage of this protocol, including the generation of the SCN minimum dataset, preliminary clinical site engagement and a pilot study of participant matching and data extraction, has already taken place as of October 2022. Formal engagement and agreements with clinical sites to refine the dataset and enable future data collection are projected to occur in late 2022/early 2023. The later activities of the protocol (from early 2023 through 2024) include participant matching, data extraction and storage and subsequent utilisation of the generated registry data for quality initiatives, primary publications, future research and guidelines. We will be applying for funding in parallel with these activities which will be material to the outcomes of this work.

Figure 2: Timelines for SCN registry within GenV. SCN = special care nursery; GenV = Generation Victoria.

Data management

The GenV data management team will be responsible for the quality checks of the SCN data before loading the data for end users. These will span completeness, usability (ensuring formatting of variables is suitable for researchers), validity (confirming no impossible values) and accessibility (excluding or changing variables that are not suitable for researchers).

Data analysis plan

This dataset will support multiple questions for a range of risks and conditions including circumstances of rare events and small effect sizes. The primary description will include the incidence estimation of key high-risk conditions and their co-occurrence for the full cohort, by level of care, by sector, and according to recorded perinatal risk factors. Once integrated with the ongoing GenV datasets and supported by high-quality data and strong research design, this registry will enable exploration of potential causal relationships of neonatal conditions and risk/protective factors with children’s long-term outcomes. It will also support examination of variations in care, explore relationships between different care pathways (from the first point of antenatal contact up to 2 years) and child outcomes. Last, as GenV’s recruitment period overlapped with the COVID-19 pandemic, it could support research into the effects of the SARS-CoV-2 virus and of the pandemic more broadly on these vulnerable babies.

The proposed dataset has several novel axes. It is Australia’s first SCN registry that includes all birthing hospitals. As it spans every service in all areas, it can summarise whole-of-state neonatal care and its variations on multiple parameters such as metro/regional/rural, public/private and disadvantage. Its comprehensive clinical data (see Table 1) are not well captured in any current collated administrative or clinical database. Lastly, partnering with GenV to access its linked administrative and clinical data, biosamples and long-term child outcomes expands the scope and time horizon of research questions that can be addressed.

Ethics and governance

Ethical approval is in place for the GenV cohort (Royal Children’s Hospital Human Research Ethics Committee (HREC)-2019/11), including consent to access clinical data. During recruitment, one primary parent/guardian is asked to provide consent for themselves and their child (index participant), and any additional parents/guardians are asked to consent for themselves only. At consent, parents provide broad consent for GenV to access (1) current and future clinical and service records, from primary sources (such as general practitioners (e.g., Medical Director) and hospitals (e.g., electronic medical records) and from secondary collated sources (e.g., My Health Record, National Disability Insurance Scheme (NDIS), Maternal and Child Health); and (2) administrative data (e.g., health (Medicare), education (National Assessment Program – Literacy and Numeracy (NAPLAN)) and social (Centrelink). This includes all electronic health record and service data available, including demographics, visits, assessments, diagnoses, procedures, vital signs, medications, laboratory and notes. Before clinical data extraction commences at each location, GenV will work with the hospital to obtain governance authorisation, including site-specific assessment (SSA) to augment GenV’s overarching ethical approval and material transfer agreement (MTA).

Dissemination of the findings

We anticipate that members of the GenV Newborns Working Group will be instrumental in a range of formal and informal dissemination activities to their peers throughout the state.

In order to foster the conditions for a successful long-term Clinical Quality Registry (CQR) beyond the GenV birth window, the SCN Registry will work towards achieving all Operating Principles for CQRs (Appendix 2), as outlined in the Framework for Australian Clinical Quality Registries developed by the Australian Commission on Safety and Quality in Healthcare [19]. All data will be stored and accessed via GenV’s already-built data repository operating under FAIR [20] and Five Safes [21] principles.

GenV is committed to an Open Science philosophy to the greatest extent possible within ethical and legal requirements, with completed waves of GenV datasets (once cleaned and prepared) made available to end-user researchers and analysts. We do not anticipate any periods of exclusive individual use for the GenV SCN registry data. Ultimately, released completed waves of GenV datasets and biosamples will be available to end-user researchers and analysts.

GenV will maintain on its website a summary of publications and outputs to the best of its knowledge. It will disseminate this via media releases, printed brochures and online summaries, social media, blogs, working papers, forums for diverse audiences (public, policy, clinical, academic etc) and featured posts on the GenV website. Reports may also be posted on Figshare, a publicly accessible online repository where researchers share their research outputs. GenV will provide participants with periodic overviews of findings, and direct them to the other forms of dissemination above.

Conclusion

Many of the significant health problems Australians increasingly face have their roots in early life. By embedding the features of a Clinical Quality Registry, the GenV SCN registry will be able to systematically address multiple questions relating to causal and care pathways for high-risk babies, enhancing translation into standardised healthcare that is accessible to everyone. Should it demonstrate a high level of acceptability and value, there may be the opportunity to transition this GenV-dependent registry into a formal ongoing clinical registry after GenV recruitment ends, supporting quality improvement activities for years to come.

Acknowledgements

Members of the Working Group (in alphabetical order):

1. Prof Peter Anderson, Professor of Paediatric Neuropsychology, Monash University

2. Assoc Prof Rose Boland, Postdoctoral Neonatal Nurse Researcher, Paediatric Infant Perinatal Emergency Retrieval (PIPER)

3. Prof Peter Davis, Consultant Neonatologist, Royal Women’s Hospital

4. Prof Lex Doyle, Associate Director of Research, Royal Women’s Hospital

5. Assoc Prof Wei Qi Fan, Consultant Paediatrician and Neonatologist, Northern Health

6. Dr Dan Garrick, Consultant Paediatrician, Goulburn Valley Health

7. Prof Rod Hunt, Chair in Neonatal Paediatrics, Monash Health

8. Prof Brett Manley, Consultant Neonatologist, Royal Women’s Hospital

9. Dr Trisha Prentice, Consultant Neonatologist, Royal Children’s Hospital

10. Dr Calum Roberts, Consultant Paediatrician, Monash Health

11. Dr Arun Sasi, Consultant Neonatologist, Mercy Hospital for Women

12. Prof Alicia Spittle, Paediatric Physiotherapy, University of Melbourne

13. Dr Niranjan Thomas, Consultant Neonatologist, Western Health

14. Dr Dave Tickell, Consultant Paediatrician, St John of God Ballarat Hospital

15. Dr Anna Tottman, Consultant Neonatologist, Royal Women’s Hospital

16. Dr David Tran, Consultant Paediatrician, Northern Health

Funding statement

No specific funding was secured for the development of this protocol. JW is supported by a Melbourne Children’s LifeCourse postdoctoral fellowship, funded by Royal Children’s Hospital Foundation grant [2018-984] and the Jack Brockhoff Foundation Early Career Medical Research Grant. MW is supported by the Australian National Health and Medical Research Council Principal Research Fellowship 1160906. Generation Victoria (GenV) is supported by grants from the Victorian government, the Paul Ramsay Foundation, and the Royal Children’s Hospital Foundation. Research at the Murdoch Children’s Research Institute is supported by the Victorian Government’s Operational Infrastructure Program. JC is supported by the Medical Research Future Fund Career Development Fellowship 1141354.

Conflicts of interest

The authors have no potential conflicts of interest to disclose.

Ethics statement

The Royal Children’s Hospital Human Research Ethics Committee approved the GenV cohort ((HREC)-2019/11), including consent to access clinical data.

Abbreviations

ANZNN	Australia and New Zealand Neonatal Network
BOS	Birthing Outcomes System
CQR	Clinical Quality Registry
EMR	Electronic Medical Record
GenV	Generation Victoria
HREC	Human Research Ethics Committee
MTA	Material Transfer Agreement
NAPLAN	National Assessment Program – Literacy and Numeracy
NDIS	National Disability Insurance Scheme
NICU	Neonatal Intensive Care Unit
PII	Personal Identifiable Information
REDCap	Research Electronic Data Capture
SCN	Special Care Nursery
SLK-581	Statistical Linkage Key
SSA	Site-specific assessment
VAED	Victorian Admitted Episodes Dataset
VEMD	Victorian Emergency Minimum Dataset
VIHSP	Victorian Infant Hearing Screen Program
VPDC	Victorian Perinatal Data Collection

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