Related Experiment Video
Updated: Oct 6, 2025
06:16
Involving Individuals with Developmental Language Disorder and Their Parents/Carers in Research Priority Setting
Published on: June 6, 2020
3.9K
A Modelling Framework for Evidence-Based Public Health Policy Making
IEEE Journal of Biomedical and Health Informatics
|January 13, 2022
Summary
This study introduces a novel ontology and integrated platform for evidence-based public health policy making. The model-driven solution utilizes big data analytics to improve decision-making for managing health conditions like hearing loss.
Area of Science:
- Public Health
- Health Informatics
- Data Science
Background:
- Public health policy making requires evidence-based approaches supported by data analytics.
- Heterogeneous data sources (e.g., device usage, lifestyle, environmental) are crucial for effective health management.
- Existing decision-making tools lack tailored analytics for comprehensive public health policy development.
Purpose of the Study:
- To present a novel ontology and integrated platform for evidence-based public health policy making.
- To demonstrate a model-driven approach utilizing big data analytics for policy development.
- To support the EVOTION research program focused on hearing loss management.
Main Methods:
- Development of a model-driven ontology for public health policy decision making (PHPDM).
- Implementation of an integrated web-based platform using Hadoop, Spark, and HBASE.
- Utilizing big data analytics to process heterogeneous health-related data.
Main Results:
- The PHPDM models define data collection, analysis, and evidence generation for policy interventions.
- The platform integrates diverse data types to support informed public health policy decisions.
- The approach facilitates the analysis of evidence to support or contradict policy actions.
Conclusions:
- The novel ontology and platform offer a robust framework for evidence-based public health policy making.
- Big data analytics and model-driven approaches enhance the management of health conditions at a policy level.
- The EVOTION project demonstrates a practical application for hearing loss policy development.
Related Concept Videos
01:25Models of Health Promotion and Illness Prevention I
2.3K
A model is a theoretical way to understand a concept or an idea. Models can overcome barriers to health regardless of diverse economic and cultural backgrounds. In addition, models make the task easier by providing different ways to approach complex issues. There are two major health promotion models: the health belief model and the health promotion model.
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
2.3K
01:18Models of Health Promotion and Illness Prevention II
1.8K
The person's health status fluctuates continually, varying from being in good health to becoming ill and returning to being healthy. To understand the concept of illness prevention, there are two models. First, the health-illness continuum model is a graphic representation of an individual's wellness. It states that a person is considered healthy in the absence of physical disease and the presence of good emotional health.
The agent-host-environment model states that disease results...
The agent-host-environment model states that disease results...
1.8K
01:16Models, Theories, and Laws
7.5K
Scientists frequently use models to help them comprehend a specific collection of phenomena. In physics, a model is a condensed version of a physical system that is too complex to study thoroughly. One such example is the light wave model; unlike water waves, light waves are typically invisible to us. Nonetheless, it is helpful to think of light as being composed of waves, since investigations show that light behaves like water waves. Since it is impossible to visually see what is genuinely...
7.5K
01:25Statistical Methods for Analyzing Epidemiological Data
592
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
592
01:20Study Designs in Epidemiology
482
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
482
01:26Principles of Disease Surveillance
211
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
211