Data journey map: a process for co-creating data requirements for health care artificial intelligence.

IF 2 4区 医学 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Revista Panamericana De Salud Publica-pan American Journal of Public Health Pub Date : 2024-12-16 eCollection Date: 2024-01-01 DOI:10.26633/RPSP.2024.107
Curtis Charles, Cherie Tulloch, Maurice McNaughton, Patrick Hosein, Ian R Hambleton
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Abstract

The Caribbean small island developing states have limited resources for comprehensive health care provision and are facing an increasing burden of noncommunicable diseases which is driven by an aging regional population. Artificial intelligence (AI) and other digital technologies offer promise for contributing to health care efficiencies, but themselves are dependent on the availability and accessibility of accurate health care data. A regional shortfall in data professionals continues to hamper legislative recognition and promotion of increased data production in Caribbean countries. Tackling the data shortfall will take time and will require a sustainably wider pool of data producers. The data journey map is one approach that can contribute to overcoming such challenges. A data journey map is a process for organizing the collection of health data that focuses on interactions between patient and health care provider. It introduces the idea that data collection is an integral part of the patient journey and that interactions between patient and provider can be enhanced by building data collection into daily health care. A carefully developed and enacted data journey map highlights key points in the care pathway for data collection. These so-called data hotspots can be used to plan - then eventually implement - appropriate AI health care solutions. In this article we introduce the idea of journey mapping, offer an example using cervical cancer prevention and treatment, and discuss the benefits and challenges to implementing such an approach.

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数据旅程图:共同创建医疗人工智能数据需求的流程。
加勒比小岛屿发展中国家提供全面卫生保健的资源有限,而且正面临区域人口老龄化造成的日益沉重的非传染性疾病负担。人工智能(AI)和其他数字技术为提高医疗效率提供了希望,但它们本身依赖于准确医疗数据的可用性和可访问性。区域数据专业人员的短缺继续阻碍加勒比国家立法承认和促进增加数据生产。解决数据短缺问题需要时间,并且需要持续扩大数据生产者的数量。数据旅程图是一种有助于克服此类挑战的方法。数据旅程图是一个用于组织健康数据收集的过程,其重点是患者和医疗保健提供者之间的相互作用。它引入了这样一种理念,即数据收集是患者旅程中不可或缺的一部分,通过将数据收集纳入日常医疗保健,可以增强患者和提供者之间的互动。精心开发和制定的数据旅程图突出了数据收集的护理途径中的关键点。这些所谓的数据热点可用于规划——然后最终实施——适当的人工智能医疗保健解决方案。在本文中,我们介绍了旅程映射的思想,提供了一个使用宫颈癌预防和治疗的例子,并讨论了实施这种方法的好处和挑战。
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来源期刊
CiteScore
4.10
自引率
3.80%
发文量
222
审稿时长
20 weeks
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