ABSTRACT
ObjectiveTo examine infants in Scotland aged 0-27 days with confirmed SARS-CoV-2 infection; the risk of neonatal infection by factors including maternal infection status and gestation at birth; and the need for hospital admission among infected neonates. DesignPopulation-based cohort study. Setting and populationAll live births in Scotland, 1 March 2020 to 31 January 2022. ResultsThere were 141 neonates with confirmed SARS-CoV-2 infection over the study period, giving an overall infection rate of 153 per 100,000 live births (141/92,009). Among infants born to women with confirmed infection around the time of birth, the infection rate was 1,811 per 100,000 live births (15/828). Nearly two-thirds (92/141, 65.2%) of babies with confirmed neonatal infection had an associated admission to neonatal or (more commonly) paediatric care. Of those admitted to hospital, 6/92 (6.5%) infants were admitted to neonatal or paediatric intensive care, however none of these six had COVID-19 recorded as the main diagnosis underlying their admission. There were no neonatal deaths among babies with confirmed infection. Implications and relevanceConfirmed neonatal SARS-CoV-2 infection is uncommon. Secular trends in the neonatal infection rate broadly follow those seen in the general population, albeit at a lower level. Maternal infection at birth increases the risk of neonatal infection, but most babies with neonatal infection are born to women without confirmed infection. A high proportion of neonates with confirmed infection are admitted to hospital, with resulting implications for the baby, family, and services, although their outcomes are generally good. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIThe incidence of SARS-CoV-2 infection in neonates is low, but some studies have suggested that age under 1 month is a risk factor for severe infection requiring admission to intensive care. C_LIO_LIAlmost all the studies of neonatal SARS-CoV-2 have focused on the transmission risk from SARS-CoV-2 positive women to their offspring and data are lacking on the level of neonatal SARS-CoV-2 infection in the whole population. C_LI What this study addsO_LIThis study includes all babies with confirmed SARS-CoV-2 in the neonatal period in Scotland during the first 22 months of the COVID-19 pandemic. C_LIO_LIConfirmed neonatal SARS-CoV-2 infection is uncommon, but a high proportion of neonates with confirmed infection are admitted to hospital. C_LIO_LIConfirmed maternal SARS-CoV-2 infection around the time of birth substantially increases the risk of neonatal infection, although the absolute risk of neonatal infection remains low (<2%) and most babies with neonatal infection are born to women without confirmed infection. C_LIO_LIOutcomes for neonates with confirmed SARS-CoV-2 infection are good; only 6.5% (6/92) of admitted neonates required intensive care, and COVID-19 was not the primary diagnosis recorded for these babies. There were no neonatal deaths among babies with confirmed infection. C_LI
ABSTRACT
BackgroundInduction of labour (IOL) is one of the most commonly performed interventions in maternity care, with outpatient cervical ripening increasingly offered as an option for women undergoing IOL. The COVID-19 pandemic has changed the context of practice and the option of returning home for cervical ripening may now assume greater significance. This work aimed to examine whether and how the COVID-19 pandemic has changed practice around IOL in the UK. MethodWe used an online questionnaire to survey senior obstetricians and midwives at all 156 UK NHS Trusts and Boards that currently offer maternity services. Responses were analysed to produce descriptive statistics, with free text responses analysed using a conventional content analysis approach. FindingsResponses were received from 92 of 156 UK Trusts and Boards, a 59% response rate. Many Trusts and Boards reported no change to their IOL practice, however 23% reported change in methods used for cervical ripening; 28% a change in criteria for home cervical ripening; 28% stated that more women were returning home during cervical ripening; and 24% noted changes to womens response to recommendations for IOL. Much of the change was reported as happening in response to attempts to minimise hospital attendance and restrictions on birth partners accompanying women. ConclusionsThe pandemic has changed practice around induction of labour, although this varied significantly between NHS Trusts and Boards. There is a lack of formal evidence to support decision-making around outpatient cervical ripening: the basis on which changes were implemented and what evidence was used to inform decisions is not clear.
ABSTRACT
Over the past several decades healthcare delivery systems have received increased pressure to become more efficient from both a managerial and patient perspective. Many researchers have turned to simulation to analyze the complex systems that exist within hospitals, but surprisingly few have published guidelines on how to analyze models with multiple performance measures. Moreover, the published literature has failed to address ways of analyzing performance along more than one dimension, such as performance by day of the week, patient type, facility, time period, or some combination of these attributes. Despite this void in the literature, understanding performance along these dimensions is critical to understanding the root of operational problems in almost any daily clinic operation. This paper addresses the problem of multiple responses in simulation experiments of outpatient clinics by developing a stratification framework and an evaluation construct by which managers can compare several operationally different outpatient systems across multiple performance measure dimensions. This approach is applied to a discrete-event simulation model of a real-life, large-scale oncology center to evaluate its operational performance as improvement initiatives affecting scheduling practices, process flow, and resource levels are changed. Our results show a reduction in patient wait time and resource overtime across multiple patient classes, facilities, and days of the week. This research has already proven to be successful as certain recommendations have been implemented and have improved the system-wide performance at the oncology center.
