Accurate identification of hospital admissions from care homes; development and validation of an automated algorithm.
Accurate identification of hospital admissions from care homes; development and validation of an automated algorithm.
复制标题
DOI：
10.1093/ageing/afx182
复制
发表时间：
2018-05-01
期刊：
影响因子：
6.7
通讯作者：
Shaw DE
中科院分区：
文献类型：
--
作者：
Housley G;Lewis S;Usman A;Gordon AL;Shaw DE
衡量疗养院居民的复杂需求对于资源分配至关重要。医院患者管理系统 (PAS) 可能无法准确识别疗养院的入院情况。使用常规收集的 PAS 数据开发和验证一种准确、实用的方法来识别护理院住院患者的入院情况。对急性信托基金 2011 年至 2012 年 (n = 103,105) 的入院数据进行建模，开发出一种自动化工具，将医院 PAS 地址详细信息与护理质量委员会 (CQC) 的数据库进行比较，从而得出护理院居住的可能性。该工具和 Nuffield 方法（仅 CQC 邮政编码匹配）根据随机入院样本 (n = 2,000) 的手动检查进行了验证。对来自单独信托基金的数据集进行了分析，以评估普遍性。医院 PAS 不准确；人工检查中发现的护理院入院人员均未在 PAS 上记录护理院入院来源。两种方法都表现良好；自动化工具比纳菲尔德方法具有更高的阳性预测值（100% 95% 置信区间 (CI) 98.23–100% 与 87.10% 95% CI 82.28–91.00%），这意味着那些被编码为疗养院居民的人更有可能实际上来自疗养院。我们的自动化工具与第二个 Trust 的数据具有 99.2% 的高度一致性（Kappa 0.86 P < 0.001）。护理院的状态无法定期或准确地获取。自动匹配提供了一种准确、可重复、可扩展的方法来识别疗养院居住情况，并可用作衡量疗养院居民如何使用整个国家卫生服务中心急症医院资源的基准工具。
measuring the complex needs of care home residents is crucial for resource allocation. Hospital patient administration systems (PAS) may not accurately identify admissions from care homes. to develop and validate an accurate, practical method of identifying care home resident hospital admission using routinely collected PAS data. admissions data between 2011 and 2012 (n = 103,105) to an acute Trust were modelled to develop an automated tool which compared the hospital PAS address details with the Care Quality Commission’s (CQC) database, producing a likelihood of care home residency. This tool and the Nuffield method (CQC postcode match only) were validated against a manual check of a random sample of admissions (n = 2,000). A dataset from a separate Trust was analysed to assess generalisability. the hospital PAS was inaccurate; none of the admissions from a care home identified on manual check had a care home source of admission recorded on the PAS. Both methods performed well; the automated tool had a higher positive predictive value than the Nuffield method (100% 95% confidence interval (CI) 98.23–100% versus 87.10% 95%CI 82.28–91.00%), meaning those coded as care home residents were more likely to actually be from a care home. Our automated tool had a high level of agreement 99.2% with the second Trust’s data (Kappa 0.86 P < 0.001). care home status is not routinely or accurately captured. Automated matching offers an accurate, repeatable, scalable method to identify care home residency and could be used as a tool to benchmark how care home residents use acute hospital resources across the National Health Service.
影响因子：
2.4
作者：
Godden, S;Pollock, AM
通讯作者：
Pollock, AM
影响因子：
6.7
作者：
Sherlaw-Johnson, Chris;Smith, Paul;Bardsley, Martin
通讯作者：
Bardsley, Martin
影响因子：
6.7
作者：
Gordon, Adam Lee;Franklin, Matthew;Gladman, John R. F.
通讯作者：
Gladman, John R. F.