虚弱学习医疗系统原型:和谐模式

IF 2.6 Q2 HEALTH POLICY & SERVICES
Kirsten J. Parker, Louise D. Hickman, Julee McDonagh, Richard I. Lindley, Caleb Ferguson
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引用次数: 0

摘要

通过创新将研究成果迅速转化为临床实践,对于改善医疗系统和患者疗效至关重要。获得以实时数据为基础的高效学习系统是医疗保健的未来。这种医疗系统将减少不必要的临床差异,加快证据的快速转化,并提高整体医疗质量。本文旨在介绍 HARMONY 模型(使用学习型医疗系统实现动态质量改进以提高虚弱结果),这是一种实施科学和实践改进的新型虚弱学习型医疗系统模型。HARMONY 模型为医疗保健领域的临床质量登记基础设施和合作关系提供了一个原型。该模型将纵向虚弱数据转化为易于访问和使用的学习格式。该原型为老年护理和康复医院的住院患者提供了一个登记数据反馈和质量改进流程模型,以帮助减少临床差异、提高研究转化能力和改善护理质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The prototype of a frailty learning health system: The HARMONY Model

The prototype of a frailty learning health system: The HARMONY Model

Introduction

Rapid translation of research findings into clinical practice through innovation is critical to improve health systems and patient outcomes. Access to efficient systems of learning underpinned with real-time data are the future of healthcare. This type of health system will decrease unwarranted clinical variation, accelerate rapid evidence translation, and improve overall healthcare quality.

Methods

This paper aims to describe The HARMONY model (acHieving dAta-dRiven quality iMprovement to enhance frailty Outcomes using a learNing health sYstem), a new frailty learning health system model of implementation science and practice improvement. The HARMONY model provides a prototype for clinical quality registry infrastructure and partnership within health care.

Results

The HARMONY model was applied to the Western Sydney Clinical Frailty Registry as the prototype exemplar. The model networks longitudinal frailty data into an accessible and useable format for learning. Creating local capability that networks current data infrastructures to translate and improve quality of care in real-time.

Conclusion

This prototype provides a model of registry data feedback and quality improvement processes in an inpatient aged care and rehabilitation hospital setting to help reduce clinical variation, enhance research translation capacity, and improve care quality.

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来源期刊
Learning Health Systems
Learning Health Systems HEALTH POLICY & SERVICES-
CiteScore
5.60
自引率
22.60%
发文量
55
审稿时长
20 weeks
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