The Potential and Enablers of Human Data Science
Human Data Science can help improve scientific research, facilitate better clinical decision-making and enhance health system performance.
The impact on different stakeholders varies, but Human Data Science helps all of them interact more meaningfully together in the interconnected health eco-system.
Researchers are already applying the discipline to their work, but they often lack access to fully integrated tools across data science and human science to harness the full potential.
For physicians, Human Data Science can provide access to real-time dashboards to improve clinical decisions and patient care - the combined knowledge derived from millions of patient cases and in-depth disease data to make better clinical decisions for an individual patient.
For a patient, it creates the opportunity for access to better coordinated, high-value affordable care, and incentivizes taking control of personal health and wellness.
For a life science company, Human Data Science represents a structured approach to integrating human science with data science to advance R&D, innovation and commercial success. It enables the ability to harness the power of technology to accelerate the speed of innovation and clinical development.
Payers can utilize this integrated approach to get better access to real world data, linked datasets, and validate outcomes-based risk-sharing arrangements. It can also help improve wellness and preventative activities among beneficiaries and insured members.
Human Data Science can help policymakers make better, evidence-based decisions and advance policies to improve the performance of health systems. It can provide comparative datasets and benchmarks across various health systems.
Achieving the benefits of Human Data Science does not happen overnight.
We need significant commitment from all stakeholders to drive change.
We have identified the six areas that have the most potential to impact Human Data Science.
The first is human expertise. Promoting better health by focusing on the whole person – rather than just the disease.
Second is supportive policy. Encouraging stakeholders to develop policies that ensure and encourage the availability and sharing of data.
The third is investment in basic research and translational science. This means investing in policies that support the funding of basic, translational and behavioral sciences.
The fourth is investing in technology that enables AI and machine learning. This encompasses data management, IT infrastructure, education, and IP protection.
The fifth is patient privacy and data security. The protection of patient and data privacy as well as data integrity is vital to Human Data Science.
Finally, the sixth element is big data availability and data science methodologies. This involves the standardization and sharing of methodologies as well as identifying and reducing data bias to avoid applications that violate human rights.
Ultimately, Human Data Science, with its integration of data, expertise and technology, does more than just address the needs of individual stakeholders in healthcare.
It builds a proactive and collaborative health ecosystem.