Multidimensional Evidence Generation: A Paradigm Shift Post-Pandemic Enhancing Policy Implementation for India’s Health System

A. Mubayi, Anamika Mubayi
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Abstract

COVID-19 is having a profound impact on healthcare and society. The crisis has drastically shifted our focus and defined a new normal in terms of way of thinking and process of evidence gathering. Across the landscape of health, the response in future will see transformation on data, methodology, and experiences based on all stakeholders. The future of health care not merely will depend on convenience and less expensive technology but also will be multidimensional evidence-based while enhancing patients’ personal health and needs in real time. This will require integrated evidence-generation rather siloed functioning of departments, disciplines, markets, and geographies. There will be radical ways to operate that will smoothly connect evidence generating process from randomized clinical trials to patients’ medical and non-medical history, health economics and outcomes research, market access, and precision prevention strategies. That is, the paradigm shift incorporating partnership model will simultaneously enhance data engineering platforms, advanced analytics capabilities, modeling-based decision process, and cross-functional collaborations.
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多维证据生成:大流行后的范式转变,加强印度卫生系统的政策实施
COVID-19正在对医疗保健和社会产生深远影响。这场危机极大地转移了我们的关注点,并在思维方式和证据收集过程方面确立了一种新常态。在整个卫生领域,未来的应对措施将以所有利益攸关方为基础,在数据、方法和经验方面进行变革。医疗保健的未来不仅取决于便利性和更便宜的技术,而且还将以多维证据为基础,同时实时增强患者的个人健康和需求。这将需要综合的证据生成,而不是部门、学科、市场和地域的孤立运作。将会有激进的操作方式,将随机临床试验的证据生成过程与患者的病史和非病史、卫生经济学和结果研究、市场准入和精确预防策略顺利联系起来。也就是说,结合伙伴关系模型的范式转变将同时增强数据工程平台、高级分析能力、基于建模的决策过程和跨职能协作。
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