Health Data Science: Data Types & Applications in Fitness, Sleep, and More

Health Data Science utilizes a wide array of data sources to gain insights and improve healthcare outcomes. Some key data types include:

• 'Fitness and Sleep Tracker Data': Provides valuable information on activity levels, sleep patterns, and overall health metrics.
• 'Electronic Health Records (EHRs)': Comprehensive records containing patient medical history, diagnoses, medications, and other vital data.
• 'Claims and Billing Data': Offers insights into healthcare utilization patterns, costs, and treatment trends.
• 'Medical Imaging Data': Includes X-rays, MRIs, CT scans, and other images used for diagnosis and treatment planning.
• 'Genomic Data': Provides insights into individual genetic makeup and its impact on health and disease risk.
• 'Public Health Data': Covers population-level health statistics, disease outbreaks, and environmental factors.
• 'Social Determinants of Health Data': Examines factors like socioeconomic status, education, and access to healthcare that influence health outcomes.
• 'Environmental Data': Includes air quality, water quality, and other environmental factors that can affect health.