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首页> 外文期刊>BMC Pediatrics >Variation in and risk factors for paediatric inpatient all-cause mortality in a low income setting: data from an emerging clinical information network
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Variation in and risk factors for paediatric inpatient all-cause mortality in a low income setting: data from an emerging clinical information network

机译：低收入背景下小儿住院全因死亡率的变异和危险因素：来自新兴临床信息网络的数据

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Background Hospital mortality data can inform planning for health interventions and may help optimize resource allocation if they are reliable and appropriately interpreted. However such data are often not available in low income countries including Kenya. Methods Data from the Clinical Information Network covering 12 county hospitals’ paediatric admissions aged 2–59?months for the periods September 2013 to March 2015 were used to describe mortality across differing contexts and to explore whether simple clinical characteristics used to classify severity of illness in common treatment guidelines are consistently associated with inpatient mortality. Regression models accounting for hospital identity and malaria prevalence (low or high) were used. Multiple imputation for missing data was based on a missing at random assumption with sensitivity analyses based on pattern mixture missing not at random assumptions. Results The overall cluster adjusted crude mortality rate across hospitals was 6 · 2% with an almost 5 fold variation across sites (95% CI 4 · 9 to 7 · 8; range 2 · 1% - 11 · 0%). Hospital identity was significantly associated with mortality. Clinical features included in guidelines for common diseases to assess severity of illness were consistently associated with mortality in multivariable analyses (AROC =0 · 86). Conclusion All-cause mortality is highly variable across hospitals and associated with clinical risk factors identified in disease specific guidelines. A panel of these clinical features may provide a basic common data framework as part of improved health information systems to support evaluations of quality and outcomes of care at scale and inform health system strengthening efforts.
机译：背景医院死亡率数据可以为卫生干预计划提供信息，并且如果可靠且经过适当解释，可以帮助优化资源分配。但是，此类数据通常在包括肯尼亚在内的低收入国家中无法获得。方法利用临床信息网络中2013年9月至2015年3月期间12个月至59个月的12所县级医院儿科收治的数据，描述不同背景下的死亡率，并探讨是否通过简单的临床特征对疾病的严重程度进行分类常见的治疗指南一直与住院患者的死亡率相关。使用考虑医院身份和疟疾流行（低或高）的回归模型。缺失数据的多重估算是基于随机假设的缺失，而敏感性分析基于模式混合物的缺失而不是随机假设。结果整个医院群的总体调整后粗死亡率为6·2％，各地差异为5倍（95％CI 4·9至7·8;范围2·1％-11·0％）。医院身份与死亡率显着相关。在多变量分析中，用于评估疾病严重程度的常见疾病指南中包括的临床特征与死亡率始终相关（AROC = 0·86）。结论全因死亡率在各医院之间差异很大，并且与疾病特定指南中确定的临床危险因素有关。这些临床特征的面板可以提供基本的公共数据框架，作为改进的健康信息系统的一部分，以支持对质量和护理结果进行大规模评估，并为加强卫生系统提供信息。

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