Modelling the neonatal system: A joint analysis of length of stay and patient pathways.

Shola Adeyemi, E. Demir
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Abstract

In the United Kingdom, one in seven babies require specialist neonatal care after birth, with a noticeable increase in demand. Coupled with budgeting constraints and lack of investment means that neonatal units are struggling. This will inevitably have an impact on baby's length of stay (LoS) and the performance of the service. Models have previously been developed to capture individual babies' pathways to investigate the longitudinal cycle of care. However, no models have been developed to examine the joint analysis of LoS and babies' pathways. LoS at each stage of care is a critical driver of both the clinical outcomes and economic performance of the neonatal system. Using the generalized linear mixed modelling approach, extended to accommodate multiple outcomes, the association between neonate's pathway to discharge and LoS is examined. Using the data about 1002 neonates, we noticed that there is a high positive association between baby's pathway and total LoS, suggesting that discharge policies needs to be looked at more carefully. A novel statistical approach that examined the association of key outcomes and how it evolved over time is developed. Its applicability can be extended to other types of long-term care or diseases, such as heart failure and stroke.
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新生儿系统建模:住院时间和患者路径的联合分析。
在英国,七分之一的婴儿在出生后需要专门的新生儿护理,需求明显增加。再加上预算限制和缺乏投资意味着新生儿病房正在苦苦挣扎。这将不可避免地对婴儿的停留时间(LoS)和服务的表现产生影响。以前已经开发了一些模型来捕捉单个婴儿的路径,以研究护理的纵向循环。然而,目前还没有模型来检验LoS和婴儿通路的联合分析。每个护理阶段的LoS是新生儿系统临床结果和经济绩效的关键驱动因素。使用广义线性混合建模方法,扩展到适应多种结果,新生儿的路径到出院和LoS之间的关系进行了检查。使用1002名新生儿的数据,我们注意到婴儿路径与总LoS之间存在高度正相关,这表明出院政策需要更仔细地考虑。一种新的统计方法,研究了关键结果的关联及其如何随着时间的推移而演变。它的适用性可以扩展到其他类型的长期护理或疾病,如心力衰竭和中风。
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