Health Services and Delivery Research (Oct 2018)
A framework to address key issues of neonatal service configuration in England: the NeoNet multimethods study
Abstract
Background: There is an inherent tension in neonatal services between the efficiency and specialised care that comes with centralisation and the provision of local services with associated ease of access and community benefits. This study builds on previous work in South West England to address these issues at a national scale. Objectives: (1) To develop an analytical framework to address key issues of neonatal service configuration in England, (2) to investigate visualisation tools to facilitate the communication of findings to stakeholder groups and (3) to assess parental preferences in relation to service configuration alternatives. Main outcome measures: The ability to meet nurse staffing guidelines, volumes of units, costs, mortality, number and distance of transfers, travel distances and travel times for parents. Design: Descriptive statistics, location analysis, mathematical modelling, discrete event simulation and economic analysis were used. Qualitative methods were used to interview policy-makers and parents. A parent advisory group supported the study. Setting: NHS neonatal services across England. Data: Neonatal care data were sourced from the National Neonatal Research Database. Information on neonatal units was drawn from the National Neonatal Audit Programme. Geographic and demographic data were sourced from the Office for National Statistics. Travel time data were retrieved via a geographic information system. Birth data were sourced from Hospital Episode Statistics. Parental cost data were collected via a survey. Results: Location analysis shows that to achieve 100% of births in units with ≥ 6000 births per year, the number of birth centres would need to be reduced from 161 to approximately 72, with more parents travelling > 30 minutes. The maximum number of neonatal intensive care units (NICUs) needed to achieve 100% of very low-birthweight infants attending high-volume units is 36 with existing NICUs, or 48 if NICUs are located wherever there is currently a neonatal unit of any level. Simulation modelling further demonstrated the workforce implications of different configurations. Mortality modelling shows that the birth of very preterm infants in high-volume hospitals reduces mortality (a conservative estimate of a 1.2-percentage-point lower risk) relative to these births in other hospitals. It is currently not possible to estimate the impact of mortality for infants transferred into NICUs. Cost modelling shows that the mean length of stay following a birth in a high-volume hospital is 9 days longer and the mean cost is £5715 more than for a birth in another neonatal unit. In addition, the incremental cost per neonatal life saved is £460,887, which is comparable to other similar life-saving interventions. The analysis of parent costs identified unpaid leave entitlement, food, travel, accommodation, baby care and parking as key factors. The qualitative study suggested that central concerns were the health of the baby and mother, communication by medical teams and support for families. Limitations: The following factors could not be modelled because of a paucity of data – morbidity outcomes, the impact of transfers and the maternity/neonatal service interface. Conclusions: An evidence-based framework was developed to inform the configuration of neonatal services and model system performance from the perspectives of both service providers and parents. Future work: To extend the modelling to encompass the interface between maternity and neonatal services. Funding: The National Institute for Health Research Health Services and Delivery Research programme.
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