Staying Ahead of the Curve

When it comes to NHS data processing – turning raw patient data into intelligence – Sollis has always been ahead of the curve.

A few years ago we built machine learning algorithms into our Sollis grouper, to make HRG and Specialised Commissioning grouping much more efficient at a time when we were being asked to push more and more data through the NHS HRG grouper within the same time period. (Despite more recent step changes to the NHS grouper, the Sollis grouper is still almost 2.5 times quicker with some data sets.¹)

Our solution uses machine learning techniques to avoid duplication of effort. Once it has been trained on a particular NHS grouper, it can apply the rules it has discovered to incoming data streams and group them blisteringly fast. Our CSU partners have benefited from the efficiency gains when importing Accident and Emergency and Outpatient data extracts in particular. Those our grouper has learnt do not need to be processed by the NHS grouper again. If a pattern is presented it hasn’t learnt, it reverts to the NHS grouper to learn how to handle the new situation. Results match the equivalent NHS grouper outputs exactly.

OLAP stands for ‘Online Analytical Processing’ – a term coined in 1993 to describe a class of multi-dimensional tools (particularly OLAP Cubes and viewers) to support data exploration and business intelligence systems. Cubes are multi-dimensional data structures that enable complex data queries to run quickly, using indexes and aggregation to optimise data for ad hoc querying.

Back in 1986 our founder, Dave Sollis, started building and delivering OLAP-based business intelligence systems to NHS users – well before the terminology itself was developed. By the early 1990s over 250,000 separate OLAP cubes were being built and used each year by NHS users, using this technology.   Our modern day OLAP application, the Sollis Cube Viewer, is the ideal tool for analysing large amounts of data to provide answers to specific data queries.

Recently, one of our CCG customers used the Cube Viewer to help identify potential opportunities to pool resources with local authorities, in order to provide more integrated care for elderly patients, delivered through the Better Care Fund.

The NHS doesn’t stand still and neither do we. The way health and care organisations, working in collaboration, use patient data to improve population health continues to change. Sollis, likewise, continues to innovate. It is our purpose to help enable the current and future NHS to gain insights from their data to inform service provision and improve population health.

¹ Tested on 306,000 outpatient records.