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Using a summary measure for multiple quality indicators in primary care: the Summary QUality InDex (SQUID)

机译:在初级保健中对多个质量指标使用汇总度量:汇总质量指数(SQUID)

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Background Assessing the quality of primary care is becoming a priority in national healthcare agendas. Audit and feedback on healthcare quality performance indicators can help improve the quality of care provided. In some instances, fewer numbers of more comprehensive indicators may be preferable. This paper describes the use of the Summary Quality Index (SQUID) in tracking quality of care among patients and primary care practices that use an electronic medical record (EMR). All practices are part of the Practice Partner Research Network, representing over 100 ambulatory care practices throughout the United States. Methods The SQUID is comprised of 36 process and outcome measures, all of which are obtained from the EMR. This paper describes algorithms for the SQUID calculations, various statistical properties, and use of the SQUID within the context of a multi-practice quality improvement (QI) project. Results At any given time point, the patient-level SQUID reflects the proportion of recommended care received, while the practice-level SQUID reflects the average proportion of recommended care received by that practice's patients. Using quarterly reports, practice- and patient-level SQUIDs are provided routinely to practices within the network. The SQUID is responsive, exhibiting highly significant (p < 0.0001) increases during a major QI initiative, and its internal consistency is excellent (Cronbach's alpha = 0.93). Feedback from physicians has been extremely positive, providing a high degree of face validity. Conclusion The SQUID algorithm is feasible and straightforward, and provides a useful QI tool. Its statistical properties and clear interpretation make it appealing to providers, health plans, and researchers.
机译:背景技术评估初级保健的质量已成为国家医疗保健议程中的优先事项。对医疗质量绩效指标的审核和反馈可以帮助改善所提供的护理质量。在某些情况下,更少量的更全面的指标可能是可取的。本文介绍了摘要质量指数(SQUID)在跟踪患者和使用电子病历(EMR)的初级护理实践中的护理质量时的使用。所有实践都是“实践合作伙伴研究网络”的一部分,代表整个美国的100多种门诊护理实践。方法SQUID包括36个过程和结果度量,所有这些均从EMR中获得。本文介绍了SQUID计算算法,各种统计属性以及在多实践质量改进(QI)项目的背景下使用SQUID的算法。结果在任何给定的时间点,患者级别的SQUID反映了所接受的推荐治疗的比例,而实践水平的SQUID反映了该实践的患者所接受的推荐治疗的平均比例。使用季度报告,可以将常规和患者级别的SQUID定期提供给网络中的常规。 SQUID具有响应能力,在主要的QI计划中表现出非常显着的提高(p <0.0001),并且其内部一致性非常好(Cronbach's alpha = 0.93)。医生的反馈非常积极,可提供高度的面部有效性。结论SQUID算法是可行和直接的,并且提供了一个有用的QI工具。它的统计特性和清晰的解释使其吸引提供者,健康计划和研究人员。

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