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质量改进故事板背后的量化故事:多州学习合作开展的质量改进项目的综合。

The quantitative story behind the quality improvement storyboards: a synthesis of quality improvement projects conducted by the multi-state learning collaborative.

机构信息

Center for Medicine and Public Health, Florida State University College of Medicine, Tallahassee, FL 32306, USA.

出版信息

J Public Health Manag Pract. 2013 Jul-Aug;19(4):330-40. doi: 10.1097/PHH.0b013e3182629054.

Abstract

CONTEXT

The Multi-State Learning Collaborative: Lead States in Public Health Quality Improvement (MLC) brought state and local health departments in 16 states together with public health system and national partners to prepare for national voluntary accreditation and to implement quality improvement (QI) practices.

OBJECTIVE

The MLC has collected the single largest repository of qualitative public health QI data to date. A preliminary study was conducted to explore the potential merits of further mining data sets of this size and scope and examining them quantitatively.

DESIGN

We addressed the following research question: What characteristics of QI projects/mini-collaboratives make them more or less likely to attain their stated objectives? Qualitative MLC data were modified and coded as quantifiable measures using categorical or Likert scale measures analyzable through quantitative methods. Descriptive and inferential statistics were calculated.

RESULTS

Of the 156 mini-collaboratives with complete data, chronic disease was the most commonly selected target area. Among the 4 dependent variables, results varied somewhat by outcome. There was support in 1 or more analytical models for a positive relationship between aim statements that included target objectives, time frames, measurable goals, and well-defined processes. The degree to which the intervention was logically aligned with the aim and the comprehensiveness of the QI project were also positively associated with 1 or more outcomes. The large number of statistical tests conducted may have led to type I errors for some comparisons.

CONCLUSIONS

Quantitative analysis and modeling of public health QI activities are feasible and desirable. It may provide critical information leading to incremental improvement in QI performance within public health practice. This work can inform the nascent national accreditation program and the developing QI in Public Health Practice Exchange.

摘要

背景

多州学习合作组织(MLC)将 16 个州的州和地方卫生部门与公共卫生系统和国家合作伙伴聚集在一起,为国家自愿认证做准备,并实施质量改进(QI)实践。

目的

MLC 收集了迄今为止公共卫生 QI 数据的最大单一存储库。进行了一项初步研究,以探讨进一步挖掘这种规模和范围的数据组并对其进行定量分析的潜在优点。

设计

我们解决了以下研究问题:QI 项目/小型合作的哪些特征使它们更有可能或更不可能实现其既定目标?使用可通过定量方法分析的分类或李克特量表措施,对 MLC 的定性数据进行了修改和编码,作为可量化的措施。计算了描述性和推断性统计数据。

结果

在具有完整数据的 156 个小型合作中,慢性病是最常选择的目标领域。在 4 个因变量中,结果因结果而异。在一个或多个分析模型中,支持包含目标、时间框架、可衡量目标和明确界定过程的目标陈述之间存在积极关系。干预与目标的逻辑一致性以及 QI 项目的全面性与一个或多个结果呈正相关。进行的大量统计检验可能导致某些比较的 I 型错误。

结论

对公共卫生 QI 活动进行定量分析和建模是可行且可取的。它可能为公共卫生实践中的 QI 绩效提供关键信息,从而实现增量改进。这项工作可以为新的国家认证计划和正在发展的公共卫生实践中的 QI 交流提供信息。

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