Wisdom of patients: predicting the quality of care using aggregated patient feedback.
Wisdom of patients: predicting the quality of care using aggregated patient feedback.
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DOI：
10.1136/bmjqs-2017-006847
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发表时间：
2018-03
影响因子：
5.4
通讯作者：
Leaver MP
中科院分区：
文献类型：
--
作者：
Griffiths A;Leaver MP
护理质量委员会（CQC）负责确保英格兰的医疗质量。为此，CQC开发了统计监督工具，定期汇总大量定量绩效指标，以识别护理质量风险，并优先考虑其有限的检查资源。然而，这些工具未能成功地查明质量差的供应商。面对持续的预算削减，CQC现在进一步依赖于“情报驱动”，基于风险的方法来确定检查的优先顺序，需要一种新的有效工具。确定近实时、自动收集和汇总多个来源的患者反馈是否可以提供集体判断，有效识别护理质量风险，从而有助于确定检查的优先级。我们的患者语音跟踪系统结合了来自NHS选择，患者意见，Facebook和Twitter的患者反馈，在任何给定日期为急性医院和信任形成近乎实时的集体判断评分。集体判断分数的预测能力进行评估，通过逻辑回归分析的456家医院和信托级检查的开始日期的集体判断分数之间的关系，以及随后的检查结果。汇总患者反馈可以增加以患者为中心的护理质量见解的数量和多样性。由此产生的集体判断分数与随后的检查结果之间存在正相关关系（与“需要改善”相比，被评定为“不充分”的OR为0.35（95% CI 0.16 - 0.76），需要改善/良好OR为0.23（95% CI 0.12至0.44），良好/显著OR 0.13（95% CI 0.02至0.84），所有p<0.05）。集体判断分数可以成功地识别出一组高风险的组织进行检查，可以在接近真实的时间内获得，并且可以在比大多数现有数据集更细的粒度级别上获得。因此，集体判断分数可用于帮助确定检查的优先次序。
The Care Quality Commission (CQC) is responsible for ensuring the quality of healthcare in England. To that end, CQC has developed statistical surveillance tools that periodically aggregate large numbers of quantitative performance measures to identify risks to the quality of care and prioritise its limited inspection resource. These tools have, however, failed to successfully identify poor-quality providers. Facing continued budget cuts, CQC is now further reliant on an ‘intelligence-driven’, risk-based approach to prioritising inspections and a new effective tool is required. To determine whether the near real-time, automated collection and aggregation of multiple sources of patient feedback can provide a collective judgement that effectively identifies risks to the quality of care, and hence can be used to help prioritise inspections. Our Patient Voice Tracking System combines patient feedback from NHS Choices, Patient Opinion, Facebook and Twitter to form a near real-time collective judgement score for acute hospitals and trusts on any given date. The predictive ability of the collective judgement score is evaluated through a logistic regression analysis of the relationship between the collective judgement score on the start date of 456 hospital and trust-level inspections, and the subsequent inspection outcomes. Aggregating patient feedback increases the volume and diversity of patient-centred insights into the quality of care. There is a positive association between the resulting collective judgement score and subsequent inspection outcomes (OR for being rated ‘Inadequate’ compared with ‘Requires improvement’ 0.35 (95% CI 0.16 to 0.76), Requires improvement/Good OR 0.23 (95% CI 0.12 to 0.44), and Good/Outstanding OR 0.13 (95% CI 0.02 to 0.84), with p<0.05 for all). The collective judgement score can successfully identify a high-risk group of organisations for inspection, is available in near real time and is available at a more granular level than the majority of existing data sets. The collective judgement score could therefore be used to help prioritise inspections.
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影响因子：
5.4
作者：
Griffiths, Alex;Beaussier, Anne-Laure;Rothstein, Henry
通讯作者：
Rothstein, Henry
影响因子：
--
作者：
Bardsley, M.;Spiegelhalter, D. J.;Bharania, S.
通讯作者：
Bharania, S.
影响因子：
5.4
作者：
Bardach NS;Asteria-Peñaloza R;Boscardin WJ;Dudley RA
通讯作者：
Dudley RA
影响因子：
120.7
作者：
DONABEDIAN, A
通讯作者：
DONABEDIAN, A
影响因子：
5.4
作者：
Greaves F;Laverty AA;Cano DR;Moilanen K;Pulman S;Darzi A;Millett C
通讯作者：
Millett C