Alsallakh Mohammad, Tan Laura, Pugh Richard, Akbari Ashley, Bailey Rowena, Griffiths Rowena, Lyons Ronan A, Szakmany Tamas
Population Data Science, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea SA2 8PP, UK.
Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff CF14 4XN, UK.
J Clin Med. 2023 Jan 21;12(3):872. doi: 10.3390/jcm12030872.
In this retrospective cohort study, we used the Secure Anonymised Information Linkage (SAIL) Databank to characterise and identify predictors of the one-year post-discharge healthcare resource utilisation (HRU) of adults who were admitted to critical care units in Wales between 1 April 2006 and 31 December 2017. We modelled one-year post-critical-care HRU using negative binomial models and used linear models for the difference from one-year pre-critical-care HRU. We estimated the association between critical illness and post-hospitalisation HRU using multilevel negative binomial models among people hospitalised in 2015. We studied 55,151 patients. Post-critical-care HRU was 11-87% greater than pre-critical-care levels, whereas emergency department (ED) attendances decreased by 30%. Age ≥50 years was generally associated with greater post-critical-care HRU; those over 80 had three times longer hospital readmissions than those younger than 50 (incidence rate ratio (IRR): 2.96, 95% CI: 2.84, 3.09). However, ED attendances were higher in those younger than 50. High comorbidity was associated with 22-62% greater post-critical-care HRU than no or low comorbidity. The most socioeconomically deprived quintile was associated with 24% more ED attendances (IRR: 1.24 [1.16, 1.32]) and 13% longer hospital stays (IRR: 1.13 [1.09, 1.17]) than the least deprived quintile. Critical care survivors had greater 1-year post-discharge HRU than non-critical inpatients, including 68% longer hospital stays (IRR: 1.68 [1.63, 1.74]). Critical care survivors, particularly those with older ages, high comorbidity, and socioeconomic deprivation, used significantly more primary and secondary care resources after discharge compared with their baseline and non-critical inpatients. Interventions are needed to ensure that key subgroups are identified and adequately supported.
在这项回顾性队列研究中,我们使用安全匿名信息链接(SAIL)数据库,对2006年4月1日至2017年12月31日期间入住威尔士重症监护病房的成年人出院后一年的医疗资源利用(HRU)情况进行特征描述并确定预测因素。我们使用负二项模型对重症监护后一年的HRU进行建模,并使用线性模型分析与重症监护前一年HRU的差异。我们在2015年住院的人群中,使用多级负二项模型估计危重病与住院后HRU之间的关联。我们研究了55151名患者。重症监护后的HRU比重症监护前的水平高11 - 87%,而急诊就诊次数减少了30%。年龄≥50岁通常与重症监护后较高的HRU相关;80岁以上患者的再次住院时间是50岁以下患者的三倍(发病率比(IRR):2.96,95%置信区间:2.84,3.09)。然而,50岁以下患者的急诊就诊次数更多。高合并症与重症监护后HRU比无合并症或低合并症患者高22 - 62%相关。社会经济最贫困五分位数人群的急诊就诊次数比最不贫困五分位数人群多24%(IRR:1.24 [1.16,1.32]),住院时间长13%(IRR:1.13 [1.09,1.17])。重症监护幸存者出院后一年的HRU比非重症住院患者更高,包括住院时间长68%(IRR:1.68 [1.63,1.74])。重症监护幸存者,特别是年龄较大、合并症高和社会经济贫困的患者,出院后使用的初级和二级医疗资源明显多于其基线水平和非重症住院患者。需要采取干预措施,以确保识别关键亚组并给予充分支持。