King's College London

Data and quantitative indicators are increasingly being used across the world to monitor, regulate and, ultimately, improve the quality of healthcare provided by hospitals. For instance, regulatory authorities in many countries have committed substantial resources towards exploiting healthcare performance data for many purposes such as assisting inspections, enhancing patient choice, and/or informing national and local level quality improvement initiatives.

However, the use of such large quantities of so-called ‘big data’ has been marked by a bewildering variety of international practice. While state and non-state organisations in some countries use only a few indicators (eg to inform national-level targets), comparable organisations in other countries have constructed hundreds of indicators (eg to inform nationwide quality initiatives or to assist hospital inspections).

Organisations seeking to exploit performance data also have encountered persistent difficulties in making their systems work. Cursory examination suggests that problems include: settling on agreed definitions of quality; constructing meaningful, robust and timely indicators; and the sometimes competing values and goals bound up with healthcare regulation. Such problems raise serious questions about the limits of using big data to improve healthcare quality regulation.