From Population Databases to Research and Informed Health Decisions and Policy
BackgroundIn 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 i...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2017-09-01
|
Series: | Frontiers in Public Health |
Subjects: | |
Online Access: | http://journal.frontiersin.org/article/10.3389/fpubh.2017.00230/full |
id |
doaj-bd679e46c7af4c56bb6716ccdc32638f |
---|---|
record_format |
Article |
spelling |
doaj-bd679e46c7af4c56bb6716ccdc32638f2020-11-24T23:13:07ZengFrontiers Media S.A.Frontiers in Public Health2296-25652017-09-01510.3389/fpubh.2017.00230286563From Population Databases to Research and Informed Health Decisions and PolicyYossy Machluf0Orna Tal1Orna Tal2Orna Tal3Amir Navon4Yoram Chaiter5Independent Researcher, Rehovot, IsraëlThe Israeli Center for Emerging Technologies (ICET) in Hospitals and Hospital-Based Health Technology Assessment (HB-HTA), Assaf Harofeh Medical Center, Zerifin, IsraelSackler Faculty of Medicine, Tel Aviv University, Tel Aviv, IsraelIsraeli Center for Technology Assessment in Health Care (ICTAHC), The Gertner Institute for Epidemiology and Health Policy, Tel Aviv, IsraelThe School of Social Sciences and Humanities, Kinneret College, Sea of Galilee, Jordan Valley, IsraelThe Israeli Center for Emerging Technologies (ICET) in Hospitals and Hospital-Based Health Technology Assessment (HB-HTA), Assaf Harofeh Medical Center, Zerifin, IsraelBackgroundIn 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 modelTo 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.ConclusionUsed 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.http://journal.frontiersin.org/article/10.3389/fpubh.2017.00230/fullmedical databasepopulation-based researchevidence-based decision-makingcomorbidity indexpublic health policy |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yossy Machluf Orna Tal Orna Tal Orna Tal Amir Navon Yoram Chaiter |
spellingShingle |
Yossy Machluf Orna Tal Orna Tal Orna Tal Amir Navon Yoram Chaiter From Population Databases to Research and Informed Health Decisions and Policy Frontiers in Public Health medical database population-based research evidence-based decision-making comorbidity index public health policy |
author_facet |
Yossy Machluf Orna Tal Orna Tal Orna Tal Amir Navon Yoram Chaiter |
author_sort |
Yossy Machluf |
title |
From Population Databases to Research and Informed Health Decisions and Policy |
title_short |
From Population Databases to Research and Informed Health Decisions and Policy |
title_full |
From Population Databases to Research and Informed Health Decisions and Policy |
title_fullStr |
From Population Databases to Research and Informed Health Decisions and Policy |
title_full_unstemmed |
From Population Databases to Research and Informed Health Decisions and Policy |
title_sort |
from population databases to research and informed health decisions and policy |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Public Health |
issn |
2296-2565 |
publishDate |
2017-09-01 |
description |
BackgroundIn 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 modelTo 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.ConclusionUsed 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. |
topic |
medical database population-based research evidence-based decision-making comorbidity index public health policy |
url |
http://journal.frontiersin.org/article/10.3389/fpubh.2017.00230/full |
work_keys_str_mv |
AT yossymachluf frompopulationdatabasestoresearchandinformedhealthdecisionsandpolicy AT ornatal frompopulationdatabasestoresearchandinformedhealthdecisionsandpolicy AT ornatal frompopulationdatabasestoresearchandinformedhealthdecisionsandpolicy AT ornatal frompopulationdatabasestoresearchandinformedhealthdecisionsandpolicy AT amirnavon frompopulationdatabasestoresearchandinformedhealthdecisionsandpolicy AT yoramchaiter frompopulationdatabasestoresearchandinformedhealthdecisionsandpolicy |
_version_ |
1725599249258774528 |