Human data science is a practice that combines life sciences with advances in data science to improve scientists' understanding of human health. By joining human health science, data on social and environmental conditions people go through, and people’s experience with the healthcare system, it adds a great deal of value to healthcare.
There are three components of human data science: human science, human data, and data science. All three are required in order to get a full perspective on the many factors that influence human health. Many times, healthcare systems fail to use one component and end up impeding valuable data. Human data science views human health in a different way by applying people and the entirety of the human experience instead of just thinking of them as patients and sets of data. Many missing components can include psychological state, personal beliefs, and other social facts such as their environment and housing security. If people are treated only from a medical standpoint and not from a complete one, they can go through multiple hospital visits and increased costs.
Why is Human Data Science important?
Human data is useful in providing information about people and their health, both of them relating to their cooperations with the health system. It gathers data derived from patients and converts it into a standardized format, which is very useful in comparisons between populations and healthcare systems. This data can help create models to lead major healthcare choices and influence research that is performed to make contributions to the current knowledge of diseases.
What are the components and factors of Human Data Science?
Human Data:
The many interactions of people with the healthcare system
Social, behavioral, and environmental factors affecting a person's wellness
Human Science:
The history of diseases
Mapping, structure, evolution of genes (genomics)
Disease prevention methods
Drug therapies and their guidelines
Data Science:
Artificial intelligence (AI) and machine learning (ML)
More access to data, and better decision making
Insight into data analysis
Automation of data processing
Real-world data includes information on social factors, which can greatly influence a person’s health. They have a large effect on one’s overall health, wellness, and disease responses. These types of data can bring important contributions to the world of human data science.
The social factors of human health can fall under four main categories:
Biological health:
Genetic make up
Risk of disease
Aging
Access to quality healthcare
Cultural influences:
Religious beliefs
Socio-economic status
Heritage
Education
Psychological factors:
Experiences/trauma
Stress
Depression
Insomnia
Social behavior:
Work environment
Personal habits
Technology interactions
What exactly is the Human Data Science Cloud?
The human data science cloud, made by the health information technology company, IQVIA, allows researchers and companies, to access, integrate, and transform very large amounts of data for advanced analytics, machine learning, and artificial intelligence applications. It first takes raw data from data networks and information factories. Second, it then goes through a process of data integration and transformation, which finally brings it into the final stage of data interface with AI / ML applications.
With 60x faster data extraction, 2x faster data management, 72x faster data processing, and 10x faster data delivery, the Human Data Science Cloud can play a major role in how health data is interpreted and analyzed. The IQVIA Human Data Science Cloud is a giant step forward in the world of healthcare data.
Sources
“Introducing the Human Data Scientist.” IQVIA, 2018, www.iqvia.com/blogs/2018/10/introducing-the-human-data-scientist.
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