Editorial Article: Fragmented Data is Hindering Healthcare Sectors’ Access to Big Data but Content Intelligence Provides a Solution

31 Oct 2014

Written by Jeremy Bentley, Chief Executive of Smartlogic

Along with its many benefits, the digital age has placed the healthcare sector under unprecedented information pressures. On the one hand, there is more medical research information available than ever before to help those on the frontline to provide better patient care. Yet on the other, the fact that there is so much information out there, from so many disparate sources and in so many formats, means that accessing what is needed on demand – if at all – can be a major challenge.

In this era of Big Data – which has seen more than 90% of the world’s data produced since 2010 according to Science Daily – a study from MindMetre Research that surveyed senior information management professionals in the US and Europe reveals that it is not in fact the information overload that’s the problem but the degree to which it is fragmented and disorganised.

There is no doubt that the Big Content that sits within the Big Data being generated in the medical world – the information held by organizations on symptomology, treatments, patient cases, medications, lab trials and more – can be of vital use to healthcare institutions and businesses, but much of it is unstructured and badly tagged. Yet for organisations of all sizes, harnessing this unstructured element of Big Data is becoming ever more critical in terms of gaining an edge in healthcare management and providing better patient care.

Information professionals in the healthcare field are becoming only too aware of the issue: the MindMetre research shows that 83% of the respondents in the medical industry believe large organizations are creating more unstructured data than ever, but that they are also beginning to understand the power and potential of unstructured data. The vast majority of those questioned – 89% – believe that being able to move more quickly and accurately tap into their Big Content would afford them tremendous advantages both in commercial terms and in their ability to better address healthcare needs.

In many cases, this is information that could be used to great advantage by those in the frontline of healthcare if it were not for the fact that much of it is held on a number of databases across several locations or by different business units, or partner organizations – with no practical or consistent system for categorizing documents in a way that makes them readily searchable.

Close to 80% of the health and medical industry professionals surveyed point to information fragmentation as a major hurdle when it comes to using Big Content effectively – making it the challenge most cited by respondents – while close to half see ineffective or non-existent tagging as a major barrier to locating the right unstructured data, the next most common issue named.

An additional challenge in healthcare is the complexity of its terminology, which is not only intricate and varied but is constantly evolving with the development of new research studies, diagnoses, drugs, treatments and illnesses. What’s more, in many cases factoring in layman’s terms is crucial both in extracting information from patients and enabling them to access information directly through health service portals.

There is growing momentum in the healthcare community to find ways of overcoming obstacles that prevent rapid and accurate access to this vital information, as the MindMetre research shows. The question is: how do the IT professionals in the medical and health sciences sector provide the necessary access to this vital unstructured information? Imbuing their information management platforms with Content Intelligence – enabling users to exploit Big Content by transforming their unstructured data into actionable information – would be a major step toward achieving this.

The trouble is most existing enterprise information applications – which include Microsoft SharePoint, Apache Lucene and Solr, Oracle, Google Search Appliance – do not have sufficient Content Intelligence capability. These broad platforms and tools lack the capacity to drill down and unearth very specific and technical unstructured information – despite expectations, searchers cannot simply Google a term and find the exact documents that suits their needs without combing through page after page.

The answer for many healthcare and medical organisations is the adoption of bolt-on tools that enhance existing information management platforms – applications that enable them to apply consistent metadata across disparate and far-flung information sources, search functions that facilitate more precise findability, and tools for managing very specific and unique vocabulary.

In a sector renowned for its complicated language, it is vital that organzations enable these capabilities and work together to foster a common Content Intelligence approach. The United Kingdom’s National Health Service is already leading the way in this area, developing Content Intelligence capability in its NHS Choices website. The patient information portal processes a search term, even a layman’s expression, in a specific context and generates results that address the searcher’s intended meaning, while screening out irrelevant content. For example, a search for ‘labour’ – one of last year’s most popular health searches on Google – would bring up information on childbirth rather than worker turmoil in the medical profession or healthcare policies of the UK political party.

Achieving more precise information access requires organizations involved in all parts of the medical sector – from primary care to laboratory research – to adopt Content Intelligence solutions and to encourage partner companies and institutions to do the same. It is a best practice model that everyone involved in healthcare should be working towards. Content Intelligence solutions radically improve medical and healthcare organisations’ ability to filter unstructured data and make quick use of the information. The end result is better efficiency, better competitiveness, quicker advances, better care and improved patient experiences.

Read NHS Choices Case Study

View Smartlogic's Content Intelligence Solution: Semaphore

About Jeremy Bentley

Jeremy Bentley is founder and chief executive of Smartlogic. An engineer by training, he has spent his entire career in enterprise software, specifically information management systems, including business process workflow, documents and records management, search, and now content intelligence. Bentley founded Smartlogic in 2006 on the belief that organizations can outperform others if they fully utilize the huge business value contained in content. Since then, the company’s content intelligence platform, Semaphore – which adds advanced classification and semantic search capabilities to existing information systems – has been implemented at more than 300 organizations worldwide, including the UK’s National Health Service, Sentara Medical Group, Massachussetts General Hospital, Alberta Health Services, Pfizer, Merck, AstraZenica and Amgen.