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衡量重要指标 - 用于管理中低收入国家基层医疗保健环境中慢性病的信息系统:挑战与机遇。

Measuring what matters - information systems for management of chronic disease in primary healthcare settings in low and middle-income countries: challenges and opportunities.

机构信息

King's Global Health Institute, King's College London, Franklin Wilkins Building, Stamford Street, London, SE1 9NH, UK.

MindWave Ventures, 4a White Horse Mews, 37 Westminster Bridge Rd, London, SE1 7QD, UK.

出版信息

Epidemiol Psychiatr Sci. 2020 May 11;29:e127. doi: 10.1017/S204579602000030X.

Abstract

Effective health information systems are essential to the delivery of high-quality community-based care for chronic disease which will be needed to address the changing healthcare needs of populations in low and middle-income country settings. Health management information systems (health service data collected at facility level) and electronic health records (data organised by individual patients) may support the measurement-based, collaborative approach that is central to the chronic care model, which has been adopted as the basis for task-shared models of care for mental health and non-communicable disease. We used the performance of routine information systems management to guide our commentary on the evidence-base about information systems to support chronic care. We found that, despite an appetite for using the information to support decision-making around service planning, this rarely happens in practice, reasons include that data is not perceived to be of good quality or fit for purpose. There is often a mismatch between technology design and the availability of specialised knowledge and infrastructure. However, when data collection is designed in collaboration with local stakeholders, there is some evidence of success, demonstrated by completion and accuracy of data forms. Whilst there are global targets for the development of health information systems and progress on these is undoubtedly being made, indicators for chronic disease are seldom prioritised by national governments and there is insufficient decentralisation to facilitate local data-driven decision-making. Our recommendations for future research and development, therefore, focus upon the need to integrate context into the design of information systems: through building strong multisectoral partnerships, ensuring newly developed indicators are well aligned to service models and using technology that is a good fit with local infrastructure. This approach will be necessary if information systems are to deliver on their potential to drive improvements in care for chronic disease.

摘要

有效的健康信息系统对于提供高质量的基于社区的慢性病护理至关重要,这将需要满足中低收入国家人群不断变化的医疗保健需求。健康管理信息系统(在机构层面收集的卫生服务数据)和电子健康记录(按个体患者组织的数据)可以支持以测量为基础、协作的方法,这是慢性病护理模式的核心,该模式已被采纳为精神卫生和非传染性疾病共担护理模式的基础。我们利用常规信息系统管理的绩效来指导我们对支持慢性病护理的信息系统证据基础的评论。我们发现,尽管人们渴望利用这些信息来支持服务规划方面的决策,但在实践中很少发生这种情况,原因包括数据质量或适用性不佳。技术设计与专门知识和基础设施的可用性之间经常存在不匹配。然而,当数据收集与当地利益相关者合作设计时,就会有一些成功的证据,表现为数据表格的完整性和准确性。虽然有全球卫生信息系统发展目标,并且在这方面无疑正在取得进展,但国家政府很少将慢性病指标作为优先事项,也没有足够的权力下放来促进当地的数据驱动决策。因此,我们对未来研究和发展的建议侧重于将背景纳入信息系统设计的必要性:通过建立强大的多部门伙伴关系,确保新制定的指标与服务模式紧密一致,并使用与当地基础设施相匹配的技术。如果信息系统要发挥其潜力,推动慢性病护理的改善,就必须采取这种方法。

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