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Illustration showing key data entered by neonatal nurses in different NICUs travelling to a shared internet-based neonatal database for pooled analysis
Collecting, analysing and comparing data from multiple neonatal units is more informative

Tracking ROP data within the NICU

Each admission of a preterm baby to the neonatal unit generates vast amounts of clinical and demographic data. In this article we highlight why collecting these data is so important, how to record and keep the data safe and who should collect it and analyse the data.

Why is collection, tracking and analysis of neonatal data important?

Neonatal data are needed to:

  • Inform service planning and implementation
  • Develop high quality, evidence-based clinical care
  • Support teaching and training, and
  • Provide opportunities for research.

In any health service, planners and policymakers need accurate, relevant and up-to-date data to make informed decisions and allocate finite resources effectively. As the rate of preterm birth can vary from region to region within a country, country-wide data are required to identify where the most vulnerable infants are born, allocate sufficient resources to these areas, and ensure that the needs for neonatal care are met.

Development of neonatal intensive care units (NICUs) in geographical areas of greater need will, in time, lead to these NICUs accumulating the clinical skills, knowledge and expertise to provide high-quality care, and train doctors and nurses to a high standard. In addition, these large NICUs will generate large amounts of clinical data that can be used for research to drive improvements in neonatal care.

The quality of care given to preterm babies affects long-term outcomes. To understand the relationship between the two requires collection of neonatal data. These data can then be used to drive improvements in the quality of care, and hence outcomes, without the need for significant resources. One way to do this is to share and pool clinical data from several neonatal units, analyse the data and develop quality improvement programmes based on the insights gained. Using this method, a large healthcare provider in the United States achieved a 50% reduction in the incidence of severe retinopathy of prematurity (ROP) in its neonatal facilities (Ellsbury & Ursprung 2010).

What data should be collected?

There are two main types of data that should be collected for each baby:

  • Episodic data does not change and includes variables such as parental demographics, mode of delivery, Apgar score (an estimate of the baby’s general condition at birth), gestational age at birth and birthweight.

  • Daily data can change from day to day and includes respiratory support, use of antibiotics or inotropes, and nutritional intake.

There should be national agreement on which data should be collected and a neonatal minimum dataset developed. The complexity of the dataset will depend on local circumstances and resources but at the very least it should contain maternal and neonatal variables relevant to neonatal care and outcomes. With the support of professional organisations and the government, all neonatal units in a country can be encouraged to collect the variables in this dataset.

How should the data be collected and stored?

The simplest way to collect and record data is to use a paper form that contains fields for the variables of the minimum dataset. Whatever method is used, the data must be stored securely and not destroyed. To analyse the data easily, these variables can be entered into an electronic database that is backed-up regularly. The format of the database will depend on local circumstances and the complexity of the data collected. Software such as Microsoft Excel or Access can be used to develop simple databases. If this route is taken to collect and record data, it is important that all participating neonatal units use the same form and electronic database so that the data can be pooled and analysed easily.

Complex, internet-based databases designed specifically for neonatal data are available commercially or can be developed locally. The advantages of this way of collecting and recording neonatal data include easy access, uniformity of data collection across units, secure storage, and electronic back-up to ensure no loss of data.

Who should collect the data?

Each neonatal unit should have a policy in place that states clearly who is responsible for data collection. Doctors and nurses have the knowledge to perform this task well but the designated data collection person (or persons) can be a non-clinical member of the team, depending on local circumstances. It is important to collect contemporaneous, accurate and complete data. A programme should be implemented alongside to regularly check data accuracy and completeness.

Nurse and doctor checking data on paper forms in the NICU Data recording by NICU team, Mexico © Universidad de Guadalajara CC BY-NC-SA 4.0

Who should analyse the data?

Individual neonatal units are sometimes reluctant to share their data. There can be many reasons for this including the fear that one unit’s outcome data, for example mortality rate, might be worse than another’s. Individual units should have easy access to their own data to assess activity, examine time trends in outcomes, and produce reports.

The data from individual units depend on patient volume and case mix which can fluctuate from year to year. For these reasons, collecting and analysing data from multiple neonatal units is far more informative for planners, policymakers and researchers. In an ideal situation, data from all neonatal units within a country should be made available for analysis preferably by an independent central body.

Badgernet: An example of a national neonatal data tracking system

In the United Kingdom (UK), almost all neonatal units enter episodic and daily data on every single neonatal admission into a specialised, commercial database called Badgernet.

Badgernet is hosted on a secure platform accessed through the internet. Individual units have access to their own data and the data from other units in their locality. National data from Badgernet are collated by an independent body, the Neonatal Data Analysis Unit. It is commissioned by the professional organisation representing paediatricians and neonatologists in the UK, the Royal College of Pediatrics and Child Health (RCPCH), to analyse the Badgernet data and produce an annual report. These reports are made publicly available through the RCPCH website. Individual units are not anonymised in these reports which means that they can compare their performance with other units throughout the country. The publication of this unit-level data can be a strong driver to bring about change and improve function in under-performing units.

How should data be shared in your setting to promote quality improvements within the NICU? Share your views in the Comments.

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This article is from the free online course:

Retinopathy of Prematurity: Practical Approaches to Prevent Blindness

London School of Hygiene & Tropical Medicine