Digital health companies need to explore and consider the emerging risks related to ‘Big Data’ within their organisations, according to broker Willis Towers Watson (WTW).
According to the broker’s white paper, ‘Big Data in Healthcare’ it defines Big Data as data whose scale and complexity require new architecture, techniques, algorithms, and analytics to manage it and extract value and hidden knowledge from it.
In a healthcare context, it adds, the term often has a multidimensional meaning that incorporates:
- the volume and diversity of data available from disparate sources with
- the efficient real-time linking and analysis of those data in order to
- provide actionable insights and enable informed decision making.
Consequently, the broker suggests, ‘Big Data’ in healthcare is not wholly focused on the flood of data; rather, the emphasis is on the analysis, parsing and synthesis of the data into knowledge and understanding.
The white paper proposes that many healthcare systems, though often data rich, do not properly utilise existing datasets to generate a better understanding of how to improve access to better quality care and to reduce waste:
“Such missed opportunities result in unnecessary patient harm and serve to increase the gap between the cost of healthcare and the outcomes achieved.”
“These system limitations could be overcome by the development of a continuous learning healthcare system that harnesses Big Data to ‘fuel’ a virtuous cycle, in which research informs and influences clinical practice and clinical practice informs and influences research.”
In such a system, WTW suggests, Big Data can help facilitate a more empirically driven healthcare system, ideally free from bias, to drive lowered costs, improved quality of care and patient safety and ultimately better outcomes.
To access the full paper click here.