University Department of Anaesthesia, Critical Care, and Pain Medicine, School of Clinical Sciences, University of Edinburgh, Edinburgh, UK MRC Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK.
University Department of Anaesthesia, Critical Care, and Pain Medicine, School of Clinical Sciences, University of Edinburgh, Edinburgh, UK.
BMJ Open. 2016 Jun 28;6(6):e012590. doi: 10.1136/bmjopen-2016-012590.
Survivors of critical illness experience multidimensional disabilities that reduce quality of life, and 25-30% require unplanned hospital readmission within 3 months following index hospitalisation. We aim to understand factors associated with unplanned readmission; develop a risk model to identify intensive care unit (ICU) survivors at highest readmission risk; understand the modifiable and non-modifiable readmission drivers; and develop a risk assessment tool for identifying patients and areas for early intervention.
We will use mixed methods with concurrent data collection. Quantitative data will comprise linked healthcare records for adult Scottish residents requiring ICU admission (1 January 2000-31 December 2013) who survived to hospital discharge. The outcome will be unplanned emergency readmission within 90 days of index hospital discharge. Exposures will include pre-ICU demographic data, comorbidities and health status, and critical illness variables representing illness severity. Regression analyses will be used to identify factors associated with increased readmission risk, and to develop and validate a risk prediction model. Qualitative data will comprise recorded/transcribed interviews with up to 60 patients and carers recently experiencing unplanned readmissions in three health board regions. A deductive and inductive thematic analysis will be used to identify factors contributing to readmissions and how they may interact. Through iterative triangulation of quantitative and qualitative data, we will develop a construct/taxonomy that captures reasons and drivers for unplanned readmission. We will validate and further refine this in focus groups with patients/carers who experienced readmissions in six Scottish health board regions, and in consultation with an independent expert group. A tool will be developed to screen for ICU survivors at risk of readmission and inform anticipatory interventions.
Data linkage has approval but does not require ethical approval. The qualitative study has ethical approval. Dissemination with key healthcare stakeholders and policymakers is planned.
UKCRN18023.
危重病幸存者会经历多维残疾，从而降低生活质量，25-30%的患者在指数住院后 3 个月内需要计划外的医院再入院。我们旨在了解与计划外再入院相关的因素；制定一个风险模型来识别 ICU 幸存者中再入院风险最高的人群；了解可改变和不可改变的再入院驱动因素；并开发一种风险评估工具，以识别患者和需要早期干预的领域。
我们将使用混合方法进行同期数据收集。定量数据将包括需要 ICU 入院的苏格兰成年居民的链接医疗记录（2000 年 1 月 1 日至 2013 年 12 月 31 日），这些患者存活至出院。结果是指数出院后 90 天内计划外的紧急再入院。暴露因素将包括 ICU 前的人口统计学数据、合并症和健康状况，以及代表疾病严重程度的危重病变量。回归分析将用于确定与增加再入院风险相关的因素，并开发和验证风险预测模型。定性数据将包括在三个卫生委员会区域最近经历计划外再入院的最多 60 名患者和照顾者的记录/转录访谈。将使用演绎和归纳主题分析来确定导致再入院的因素以及它们如何相互作用。通过对定量和定性数据的迭代三角测量，我们将开发一个结构/分类法，以捕捉计划外再入院的原因和驱动因素。我们将在六个苏格兰卫生委员会区域经历过再入院的患者/照顾者焦点小组中对此进行验证和进一步改进，并与一个独立的专家组进行磋商。将开发一种工具，用于筛选有再入院风险的 ICU 幸存者，并提供预期干预措施。
数据链接已获得批准，但不需要伦理批准。定性研究已获得伦理批准。计划与主要医疗保健利益相关者和政策制定者进行传播。
UKCRN18023。
