Amidst all the discussion about 'big data' and 'learning health systems', I’d like to take this opportunity to introduce a concept – that of 'devolved analytics'. I believe this has a part to play in achieving a better quality healthcare system through the use of large-scale healthcare data.
To help put this into context, first a brief bit of history. The illustration below shows the evolution of healthcare analytics to date. The first steps are recognisable to most businesses: organisations start with simple spreadsheets and then move on to produce simple management reports with some graphical visualisation of key outputs. Some organisations are firmly at the second stage, successfully managing data via simple reports and data visualisation. However, many still have a long way to go and are not even at this stage yet.
The third stage is where the analytics becomes more complex. Many healthcare institutions have established data marts or enterprise data warehouses, which contain data drawn from multiple sources within the organisation and a range of different types of data, such as clinical data, financial data, etc.