The impact of frailty and geriatric syndromes on metrics of acute care performance: results of a national day of care survey.
The impact of frailty and geriatric syndromes on metrics of acute care performance: results of a national day of care survey.
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DOI：
10.1016/j.eclinm.2023.102278
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发表时间：
2023-12
影响因子：
15.1
通讯作者：
Lasserson, Daniel
中科院分区：
文献类型：
--
作者：
Knight, Thomas;Atkin, Catherine;Kamwa, Vicky;Cooksley, Tim;Subbe, Chris;Holland, Mark;Sapey, Elizabeth;Lasserson, Daniel
虚弱与急性医院环境中的一系列不良临床结局相关。我们试图确定虚弱和相关因素是否影响临床过程，如英国国家卫生服务（NHS）紧急入院期间的评估时间。急性医学基准审计协会（桑巴舞）是一项年度横断面护理调查。桑巴舞2022于二零二二年六月二十三日（星期四）进行。我们评估了临床虚弱量表（CFS）和老年综合征的存在是否影响了国家认可的临床质量指标的性能，这些指标基于初始评估时间和顾问审查时间。CFS被分为健全（CFS 1 -3），轻度（CFS 4-5），中度（CFS 6），重度（CFS 7 -8）和绝症（CFS 9）。使用多水平多重插补为缺失变量创建合理值。使用混合效应广义线性模型对初始国家预警评分2（NEWS 2）和到达时间进行调整来描述这种关联。共有152家医院提供了与7248例急诊入院相关的患者水平数据。轻度、中度和重度虚弱的患者不太可能在到达后4小时内接受评估（校正OR，轻度0.79，95% CI 0.68-0.96，中度0.67 95% CI 0.53-0.84，重度0.75 95% CI 0.58-0.96，终末期疾病0.59（95% CI 0.23-1.43），不太可能达到顾问审查的临床质量指标（校正OR，轻度0.69 95% CI 0.58-0.83，中度0.55 95% CI 0.44-0.70，重度0.54 95% CI 0.41-0.69，终末期疾病0.76 95% CI 0.42-1.5）。患有老年综合征的患者也不太可能在到达后4小时内（调整后OR 0.66 95% CI 0.56-0.76）或在推荐的时间范围内（调整后OR 0.45 95% CI 0.39-0.51）由顾问进行评估。差异部分解释了SDEC途径的差异使用。对SDEC区域外评估的5148例患者进行的亚组分析表明，患有老年综合征（校正OR 0.71，95% CI 0.60-0.83）但不属于CFS定义的虚弱的患者不太可能在抵达后4小时内进行评估。中度和重度虚弱以及老年综合征的存在与达到顾问审查标准的可能性降低相关（中度，校正OR 0.75，95% CI 0.59-0.94，重度校正OR 0.75，95% CI 0.58-0.96，老年综合征校正OR 0.59，95% CI 0.50-0.69）。虚弱与延迟临床评估相关。这种关联可能表明临床优先级的系统性问题，对急性护理政策具有重要意义。桑巴舞的数据库是由。
Frailty is associated with a range of adverse clinical outcomes in the acute hospital setting. We sought to determine whether frailty and related factors affected clinical processes such as time to assessment during emergency hospital admission within the National Health Service (NHS) in the UK. The Society for Acute Medicine Benchmarking Audit (SAMBA) is an annual cross-sectional day of care survey. SAMBA 2022 was conducted on Thursday 23rd June 2022. We assessed whether the Clinical Frailty Scale (CFS) and presence of a geriatric syndrome affected performance against nationally recognised clinical quality indicators based on time to initial assessment and time to consultant review. CFS was graded into robust (CFS1-3), mild (CFS 4-5), moderate (CFS 6), severe (CFS7-8) and terminal illness (CFS 9). Plausible values were created for missing variables using multi-level multiple imputation. The association was described using mixed effect generalised linear models adjusting for initial National Early Warning Score 2 (NEWS2) and time of arrival. A total of 152 hospitals provided patient level data relating to 7248 emergency medical admissions. Patients with mild, moderate and severe frailty were less likely to be assessed within 4 h of arrival (adjusted OR, mild 0.79, 95% CI 0.68–0.96, moderate 0.67 95% CI 0.53–0.84, severe, 0.75 95% CI 0.58–0.96, terminally ill 0.59 95% CI 0.23–1.43) and less likely to be achieve the clinical quality indicator for consultant review (adjusted OR, mild 0.69 95% CI 0.58–0.83, moderate 0.55 95% CI 0.44–0.70, severe 0.54 95% CI 0.41–0.69, terminally ill 0.76 95% CI 0.42–1.5). Patients with geriatric syndromes were also less likely to be assessed within 4 h of arrival (adjusted OR 0.66 95% CI 0.56–0.76) or by a consultant within the recommended time frame (adjusted OR 0.45 95% CI 0.39–0.51). The difference was partially explained by differential use of SDEC pathways. Sub-group analysis of 5148 patients assessed outside of SDEC areas demonstrated patients with geriatric syndromes (adjusted OR 0.71, 95% CI 0.60–0.83), but not frailty defined by CFS were less likely to be assessed within 4 h of arrival. Moderate and severe frailty and the presence of a geriatric syndrome were associated with a decreased likelihood of achieving the consultant review standard (moderate, adjusted OR 0.75, 95% CI 0.59–0.94, severe adjusted OR 0.75 95% CI 0.58–0.96, geriatric syndrome adjusted OR 0.59, 95% CI 0.50–0.69). Frailty is associated with delayed clinical assessment. This association may suggest a systemic issue with clinical prioritisation, with important implications for acute care policy. The database for SAMBA is funded by the .
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影响因子：
2.9
作者：
通讯作者：
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影响因子：
--
作者：
Atkin, C;Knight, T;Lasserson, D
通讯作者：
Lasserson, D
影响因子：
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通讯作者：
Turpin, Sarah
影响因子：
6.7
作者：
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通讯作者：
Rockwood, Kenneth
影响因子：
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作者：
Rockwood, K;Song, XW;Mitnitski, A
通讯作者：
Mitnitski, A