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Role of visual analytics in supporting mental healthcare systems research and policy: A systematic scoping review

机译:视觉分析在支持精神保健系统研究和政策中的作用:系统的范围界定审查

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摘要

The availability of healthcare data has exponentially grown, both in quantity and complexity. The speed of this evolution has generated new challenges for translating complex data into effective evidence-informed policy. Visual analytics offers new capacity to analyze healthcare systems and support better decision-making. We conducted a systematic scoping review to look for evidence of visual analytics approaches being applied to mental healthcare systems and their use in driving policy. We found 79 relevant studies and categorized them in two ways: by study purpose and by type of visualization. The majority (67.1%) of the studies used geographical maps, and 11% conducted highly complex studies requiring novel visualizations. Significantly, only 15% of the studies provided information indicating high levels of usability for policy and planning. Our findings suggest that while visual analytics continues to evolve rapidly, there is a need to ensure this evolution reflects the practical needs of policy makers.
机译:医疗数据的可用性在数量和复杂性上均呈指数增长。这种发展的速度为将复杂数据转换为有效的循证政策提出了新的挑战。可视化分析提供了分析医疗保健系统并支持更好的决策制定的新能力。我们进行了系统的范围界定审查,以寻找视觉分析方法应用于精神保健系统及其在驾驶政策中的使用的证据。我们找到79项相关研究,并通过两种方式对它们进行分类:按研究目的和按可视化类型分类。大多数研究(67.1%)使用地理地图,而11%进行的高度复杂的研究需要新颖的可视化效果。值得注意的是,只有15%的研究提供了表明政策和计划的高可用性的信息。我们的发现表明,尽管视觉分析继续快速发展,但有必要确保这种发展能够反映决策者的实际需求。

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