Create a simple-to-use, highly configurable, clinically focused end-user application to replace paper medical records. Find a more efficient way to index and extract precise clinical data needed on a daily basis, and provide it in a mobile environment so it can be accessed at the patients’ bedsides. Finally, migrate millions of records without disrupting employees’ activities.
The UK Government set a target for the National Health Service (NHS) to go paperless by 2018 in a move that aims to save billions of pounds, improve services, and help meet the challenges of an ageing population.
A core element of going paperless is the digitization of patient records, thereby making crucial information available to health and social care practitioners at the touch of a button. At the forefront of this drive is the leader of the UK Electronic Medical Records (EMR) market, Kainos Evolve, which has offices in the UK, Ireland, Poland, the Netherlands, and the United States. Its flagship EMR product, Evolve, is now used by over 100 acute hospitals in the NHS.
“Evolve started as a paper digitization project for The Ipswich Hospital NHS Trust almost seven years ago,” explains Nigel Hutchinson, Head of Kainos Evolve. “They were looking for an Electronic Document Management (EDM) solution for their paper patient records and wanted something that was more clinically focused, dealing with patients, wards and hospital processes.
“They were very keen to partner with an organization that could help them develop this vision because they couldn’t find anything in the market that met their requirements. At one end of the system there are large, monolithic Electronic Patient Record (EPR) solutions that deliver a ‘hospital-in-a-box’ and at the other end of the scale there are generic Enterprise Content Management (ECM) solutions that are not designed for the clinical environment. Ipswich saw an opportunity to work with Kainos Evolve to build a next generation EMR solution.”
Kainos Evolve was looking for a technology that could not only optically read (OCR) and index complex legacy paper-based information but could also extract document types and identify domain-specific concepts such as clinical disciplines.
Ideally, the technology would extract details of people, mapped to clinical disciplines, such as the mapping of a particular doctor to a specialty (Dr. Biggerstaff mapped to Cardiology, for example). In addition, Kainos Evolve needed powerful visualization tools to allow visual clustering of concepts and search results, and to facilitate intuitive ways for clinicians to handle returned information. The technology would also need to connect to and index information held in other systems, without requiring the ingestion of that information.