Menlo College, 1000 El Camino Real, Atherton, CA 94027, USA.
Faculty of Law, Tarbiat Modares University, Tehran, Iran.
Health Policy. 2024 Sep;147:105134. doi: 10.1016/j.healthpol.2024.105134. Epub 2024 Jul 17.
National strategies are essential driving forces behind governments taking responsibility for setting the direction of digital health on a national level. This study employed a novel mixed-methods approach, integrating topic modeling, co-occurrence analysis, and qualitative content analysis, to comprehensively examine 22 national digital health strategies through the lens of Donabedian's structure-process-outcome model. The quantitative analysis identified 14 prevalent topics, while the qualitative analysis provided nuanced insights into the contexts underlying these topics. Leveraging Donabedian's framework, the topics were categorized into structure (training and digital health professionals, governance frameworks, computing infrastructure, public-private partnerships, regulatory frameworks), process (AI and big data, decision-support systems, shared digital health records, disease surveillance, information system interoperability), and outcome dimensions (improved health and social care, privacy and security, quality and efficiency of health services, universal coverage, sustainable development goals). This hybrid methodology offers a unique contribution by mapping the identified themes onto a widely accepted quality of care model, bridging the gap between policy analysis and healthcare quality assessment. The study unveils underaddressed themes, highlights the interrelationships between policy components, and provides a comprehensive understanding of the global digital health policy landscape. The findings inform future strategies, academic research directions, and potential policy considerations for governments formulating digital health regulations.
国家战略是政府在国家层面承担数字卫生方向责任的重要推动因素。本研究采用一种新颖的混合方法，通过 Donabedian 的结构-过程-结果模型，综合主题建模、共现分析和定性内容分析，全面研究了 22 个国家数字卫生战略。定量分析确定了 14 个常见主题，而定性分析则深入了解了这些主题背后的背景。利用 Donabedian 的框架，将这些主题分为结构（培训和数字卫生专业人员、治理框架、计算基础设施、公私伙伴关系、监管框架）、过程（人工智能和大数据、决策支持系统、共享数字健康记录、疾病监测、信息系统互操作性）和结果维度（改善卫生和社会保健、隐私和安全、卫生服务的质量和效率、全民覆盖、可持续发展目标）。这种混合方法通过将确定的主题映射到广泛接受的护理质量模型上，为政策分析和医疗保健质量评估之间架起了桥梁，从而做出了独特的贡献。该研究揭示了未得到充分关注的主题，突出了政策组成部分之间的相互关系，并全面了解了全球数字卫生政策格局。研究结果为政府制定数字卫生法规提供了未来战略、学术研究方向和潜在政策考虑。
