Machluf Yossy, Tal Orna, Navon Amir, Chaiter Yoram
Independent Researcher, Rehovot, Israël.
The Israeli Center for Emerging Technologies (ICET) in Hospitals and Hospital-Based Health Technology Assessment (HB-HTA), Assaf Harofeh Medical Center, Zerifin, Israel.
Front Public Health. 2017 Sep 21;5:230. doi: 10.3389/fpubh.2017.00230. eCollection 2017.
In the era of big data, the medical community is inspired to maximize the utilization and processing of the rapidly expanding medical datasets for clinical-related and policy-driven research. This requires a medical database that can be aggregated, interpreted, and integrated at both the individual and population levels. Policymakers seek data as a lever for wise, evidence-based decision-making and information-driven policy. Yet, bridging the gap between data collection, research, and policymaking, is a major challenge.
To bridge this gap, we propose a four-step model: (A) creating a conjoined task force of all relevant parties to declare a national program to promote collaborations; (B) promoting a national digital records project, or at least a network of synchronized and integrated databases, in an accessible transparent manner; (C) creating an interoperative national research environment to enable the analysis of the organized and integrated data and to generate evidence; and (D) utilizing the evidence to improve decision-making, to support a wisely chosen national policy. For the latter purpose, we also developed a novel multidimensional set of criteria to illuminate insights and estimate the risk for future morbidity based on current medical conditions.
Used by policymakers, providers of health plans, caregivers, and health organizations, we presume this model will assist transforming evidence generation to support the design of health policy and programs, as well as improved decision-making about health and health care, at all levels: individual, communal, organizational, and national.
在大数据时代，医学界受到启发，要最大限度地利用和处理迅速增长的医疗数据集，以开展临床相关研究和政策驱动型研究。这需要一个能够在个体和群体层面进行汇总、解读和整合的医学数据库。政策制定者将数据视为明智的循证决策和信息驱动型政策的杠杆。然而，弥合数据收集、研究和政策制定之间的差距是一项重大挑战。
为弥合这一差距，我们提出了一个四步模型：（A）组建一个由所有相关方组成的联合特别工作组，宣布一项促进合作的国家计划；（B）以可访问且透明的方式推进国家数字记录项目，或至少推进一个同步且整合的数据库网络；（C）创建一个可互操作的国家研究环境，以便对经过整理和整合的数据进行分析并生成证据；（D）利用这些证据改进决策，以支持明智选择的国家政策。为实现后一目标，我们还开发了一套全新的多维标准，以基于当前医疗状况阐明见解并估计未来发病风险。
我们推测，政策制定者、健康计划提供者、护理人员和卫生组织使用该模型将有助于转变证据生成方式，以支持卫生政策和项目的设计，以及在各个层面（个体、社区、组织和国家）改进有关健康和医疗保健的决策。
