5,046 research outputs found

    Modelling and performance measure of a perinatal network centre in the United Kingdom

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    The main aim of this paper is to model the neonatal unit of a perinatal network centre using the general framework of a loss network model and to estimate some performance measures. A special case of the class of model has been applied for capacity planning to the perinatal network centre of a neonatal network in the United Kingdom. Using the data supplied from the perinatal network centre about admission process, length of stay (LoS) and discharge pattern of the babies, the loss network model is applied to estimate the admission refusal probability in the system under steady-state conditions. Results are derived for different arrival patterns and different combinations of cots at all levels of care of the neonatal unit. This approach can be useful to select the optimal combination of cots for any given acceptance rate of arrival to the neonatal unit

    A UK wide cohort study describing management and outcomes for infants with surgical Necrotising Enterocolitis

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    The Royal College of Surgeons have proposed using outcomes from necrotising enterocolitis (NEC) surgery for revalidation of neonatal surgeons. The aim of this study was therefore to calculate the number of infants in the UK/Ireland with surgical NEC and describe outcomes that could be used for national benchmarking and counselling of parents. A prospective nationwide cohort study of every infant requiring surgical intervention for NEC in the UK was conducted between 01/03/13 and 28/02/14. Primary outcome was mortality at 28-days. Secondary outcomes included discharge, post-operative complication, and TPN requirement. 236 infants were included, 43(18%) of whom died, and eight(3%) of whom were discharged prior to 28-days post decision to intervene surgically. Sixty infants who underwent laparotomy (27%) experienced a complication, and 67(35%) of those who were alive at 28 days were parenteral nutrition free. Following multi-variable modelling, presence of a non-cardiac congenital anomaly (aOR 5.17, 95% CI 1.9-14.1), abdominal wall erythema or discolouration at presentation (aOR 2.51, 95% CI 1.23-5.1), diagnosis of single intestinal perforation at laparotomy (aOR 3.1 95% CI 1.05-9.3), and necessity to perform a clip and drop procedure (aOR 30, 95% CI 3.9-237) were associated with increased 28-day mortality. These results can be used for national benchmarking and counselling of parents

    The role of health and social factors in education outcome: A record-linked electronic birth cohort analysis

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    Background and objectiveHealth status in childhood is correlated with educational outcomes. Emergency hospital admissions during childhood are common but it is not known how these unplanned breaks from schooling impact on education outcomes. We hypothesised that children who had emergency hospital admissions had an increased risk of lower educational attainment, in addition to the increased risks associated with other health, social and school factors.MethodsThis record-linked electronic birth cohort, included children born in Wales between 1 January 1998 and 31 August 2001. We fitted multilevel logistic regression models grouped by schools, to determine whether emergency hospital inpatient admission before age 7 years was associated with the educational outcome of not attaining the expected level in a teacher-based assessment at age 7 years (KS1). We adjusted for pregnancy, perinatal, socio-economic, neighbourhood, pupil mobility and school-level factors.ResultsThe cohort comprised 64 934 children. Overall, 4680 (7.2%) did not attain the expected educational level. Emergency admission to hospital was associated with poor educational attainment (OR 1.12 95% Credible Interval (CI) 1.05, 1.20 for all causes during childhood, OR 1.19 95%CI 1.07, 1.32 for injuries and external causes and OR 1.31 95%CI 1.04, 1.22 for admissions during infancy), after adjusting for known determinants of education outcomes such as extreme prematurity, being small for gestational age and socio-economic indicators, such as eligibility for free school meals.ConclusionEmergency inpatient hospital admission during childhood, particularly during infancy or for injuries and external causes was associated with an increased risk of lower education attainment at age 7 years, in addition to the effects of pregnancy factors (gestational age, birthweight) and social deprivation. These findings support the need for injury prevention measures and additional support in school for affected children to help them to achieve their potential

    Now we are 50: Key findings from the National Child Development Study

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    The economic case for better mental health

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    Comparison of three different methods for risk adjustment in neonatal medicine

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    Abstract Background Quality improvement in health care requires identification of areas in need of improvement by comparing processes and patient outcomes within and between health care providers. It is critical to adjust for different case-mix and outcome risks of patient populations but it is currently unclear which approach has higher validity and how limitations need to be dealt with. Our aim was to compare 3 approaches towards risk adjustment for 7 different major quality indicators in neonatal intensive care (21 models). Methods We compared an indirect standardization, logistic regression and multilevel approach. Parameters for risk adjustment were chosen according to literature and the condition that they may not depend on processes performed by treating clinics. Predictive validity was tested using the mean Brier Score and by comparing area under curve (AUC) using high quality population based data separated into training and validation sets. Changes in attributional validity were analysed by comparing the effect of the models on the observed-to-expected ratios of the clinics in standardized mortality/morbidity ratio charts. Results Risk adjustment based on indirect standardization revealed inferior c-statistics but superior Brier scores for 3 of 7 outcomes. Logistic regression and multilevel modelling were equivalent to one another. C-statistics revealed that predictive validity was high for 8 and acceptable for 11 of the 21 models. Yet, the effect of all forms of risk adjustment on any clinic’s comparison with the standard was small, even though there was clear risk heterogeneity between clinics. Conclusions All three approaches to risk adjustment revealed comparable results. The limited effect of risk adjustment on clinic comparisons indicates a small case-mix influence on observed outcomes, but also a limited ability to isolate quality improvement potential based on risk-adjustment models. Rather than relying on methodological approaches, we instead recommend that clinics build small collaboratives and compare their indicators both in risk-adjusted and unadjusted form together. This allows qualitatively investigating and discussing the residual risk-differences within networks. The predictive validity should be quantified and reported and stratification into risk groups should be more widely used to correct for confounding

    Analyst-driven development of an open-source simulation tool to address poor uptake of O.R. in healthcare

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    Computer simulation studies of health and care problems have been reported extensively in the academic literature, but the one-off research projects typically undertaken have failed to create an enduring legacy of widespread use by healthcare practitioners. Simulation and other modelling tools designed and developed to be used routinely have not fared much better either. Following a review of the literature and a survey of frontline analysts in the UK NHS, we found that one reason for this is because simulation tools have, to date, not been developed with the requirements of the end-user in the heart of the development process. Starting with a thorough needs assessment of NHS based healthcare analysts, this study outlines a set of practical design principles to guide development of simulation software tool for conducting patient flow simulation studies. The overall requirement is that patient flow be modelled over a number of inter-connected points of delivery while capturing the stochastic nature of patient arrivals and hospital length of stay, as well as the dynamic delays to patient discharge and transfer of care between different points of care delivery. In ensuring a cost-free solution that is both versatile and user-friendly, and coded in an increasingly popular language among the envisaged end users, the tool was implemented is the R programming language and software environment, with the user interface implemented in the interactive R-Shiny application. The talk will provide an overview of the project lifecycle including an illustrative example of an empirical simulation study concerning the centralisation of an acute stroke pathway

    SPARC 2016 Salford postgraduate annual research conference book of abstracts

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    Informing prevention of stillbirth and preterm birth in Malawi:development of a minimum dataset for health facilities participating in the DIPLOMATIC collaboration

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    OBJECTIVE: The global research group, DIPLOMATIC (Using eviDence, Implementation science, and a clinical trial PLatform to Optimise MATernal and newborn health in low Income Countries), aims to reduce stillbirths and preterm births and optimise outcomes for babies born preterm. Minimum datasets for routine data collection in healthcare facilities participating in DIPLOMATIC (initially in Malawi) were designed to assist understanding of baseline maternal and neonatal care processes and outcomes, and facilitate evaluation of improvement interventions and pragmatic clinical trials. DESIGN: Published and grey literature was reviewed alongside extensive in-country consultation to define relevant clinical best practice guidance, and the existing local data and reporting infrastructure, to identify requirements for the minimum datasets. Data elements were subjected to iterative rounds of consultation with topic experts in Malawi and Scotland, the relevant Malawian professional bodies and the Ministry of Health in Malawi to ensure relevance, validity and feasibility. SETTING: Antenatal, maternity and specialist neonatal care in Malawi. RESULTS: The resulting three minimum datasets cover the maternal and neonatal healthcare journey for antenatal, maternity and specialist neonatal care, with provision for effective linkage of records for mother/baby pairs. They can facilitate consistent, precise recording of relevant outcomes (stillbirths, preterm births, neonatal deaths), risk factors and key care processes. CONCLUSIONS: Poor quality routine data on care processes and outcomes constrain healthcare system improvement. The datasets developed for implementation in DIPLOMATIC partner facilities reflect, and hence support delivery of, internationally agreed best practice for maternal and newborn care in low-income settings. Informed by extensive consultation, they are designed to integrate with existing local data infrastructure and reporting as well as meeting research data needs. This work provides a transferable example of strengthening data infrastructure to underpin a learning healthcare system approach in low-income settings.DIPLOMATIC is funded by the UK National Institute for Health Research
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