From Population Databases to Research and Informed Health Decisions and Policy - Machluf, Yossy; Tal, Orna; Navon, Amir; Chaiter, Yoram (Frontiers in Public Health, 2017)
Background: 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. The model: 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 inter-operative 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 multi-dimensional set of criteria to illuminate insights, and estimate the risk for future morbidity based on current medical conditions. Conclusions: 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.