Predictive Analytics for Chronic Disease Management
Predictive Analytics for Chronic Disease Management
Description:
This collaboration involves healthcare providers and pharmaceutical companies to develop predictive models that help manage and prevent chronic diseases, such as diabetes and cardiovascular diseases.
Objectives:
• Enhance early detection and prevention of chronic diseases.
• Reduce healthcare costs associated with chronic disease treatment.
• Improve patient outcomes through data-driven interventions.
Socio-Economic Impact:
• Government: Reduced healthcare costs, improved public health outcomes, and lower chronic disease incidence.
• Private Sector: Access to valuable health statistics and insights for R&D, improved treatment efficacy, and enhanced patient engagement.
Potential Datasets:
• Pharmaceutical data on drug efficacy and treatment outcomes.
• Anonymized claims data and risk profiles.
• Trends in patient behavior, symptom tracking, and remote monitoring efficacy.
• Lifestyle and behavioral data, including diet and exercise habits.
• Data from devices like glucose monitors, blood pressure cuffs, etc.
Potential Stakeholders:
Pharmaceutical Companies, Health Insurance Companies, Healthcare Technology Companies, Biotechnology Firms, Telemedicine and Digital Health Companies, Health and Wellness Companies and Medical Device Manufacturers.
Code: Health
Sustainable Development Goals (SDG):
International Best Practices:
In the UK, the National Health Service collaborates with pharmaceutical companies to analyze chronic disease data, supporting early intervention and better patient outcomes.
How to get involved?
D4G Alliance initiative facilitates win-win collaboration between relevant stakeholders where privately held data are utilized to produce actionable insights for the public interest in the Emirates of Abu Dhabi.
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