The universe of healthcare data continues to expand exponentially. The need to process and make sense of this data has led to a proliferation of companies and vendors offering technology solutions to harness and extract value from these data. Within this growing ecosystem, the unstructured textual data remains a black hole to many organizations – and yet is appreciated as a potential source of so much added value, that companies are now seeking ways accessing these unstructured data siloes. As companies in the healthcare space continue to grow and prove value from the structured data – the pressure is now on to extend capabilities by turning to the free text – but how?
Nothing is as simple as black and white – but for ease of explanation – there are two options when considering how to tackle the unstructured data using natural language processing (NLP) – build something yourself or partner with someone who is already proven at doing it well. In this blog – I will break down these options to a little more detail.
Option one – partner with an established healthcare NLP player
To get to value as fast as possible – logic dictates that you partner with established technologies to bootstrap their offering with NLP: this has been the approach of many companies over the past couple of years. The benefits are obvious – by partnering with an established player in the space – you gain the knowledge, experience, and expertise of that organization, without the need to invest heavily in development. However, what is becoming clear is that most existing NLP solutions on the market are built and targeted at niche areas and therefore limit the scope of what is possible in terms of extracting information from the unstructured text. Furthermore, these solutions are usually “black box” – i.e. lack the transparency to show what is happening beneath the hood. This lack of flexibility and freedom to adjust or customize has led to companies exploring the “build it yourself” option.
Option two – build the NLP capability yourself
Under build it yourself, organizations can either start from scratch – hire staff with expertise in linguistics and natural language processing – and attempt to create something new that will extract from the unstructured data the value that will make a difference to their customers. In reality – NLP is such a mature area, that this is unlikely to be the chosen approach. Much more likely is that organizations will use open source software as a starting point. The benefits here are that users have the freedom to customize and manipulate pipelines to ensure an NLP solution that is tailored to their needs. The downside is that whilst these open source tools do offer flexibility – they are often not reliable or do not scale easily. –You need to ensure that the pipeline you implement are highly fault tolerant and are not going to leave you red faced by unexpectantly breaking, with no support available.
There is a better way – NLP that combines transparency, flexibility and reliability at scale
In the past, these were the choices facing innovative healthcare IT companies who acknowledge that their offering could be significantly enhanced by unlocking unstructured data. However, there is now a third choice that combines the best of the above – flexibility and transparency with reliability and robustness – the NLP Data Factory.
Flexibility: the NLP Data Factory is built on our core NLP platform – which enables users to interactively develop queries and rules to extract the maximum value from their unstructured data. With its extensive catalogue of ontologies, pre- and post-processors and queries – Linguamatics NLP is a platform which can be truly multi-mission in its approach to tackling unstructured data. It’s open NLP pipeline affords users the flexibility that you would expect is only possible from open-source platforms, and enables users to incorporate their own components, such as trained BERT models, to obtain results that are well aligned with needs.
Transparency: Queries can be visualized and edited in an easy to use graphical user interface – and results are displayed with links back to the evidence and reason for them – meaning users have the comfort of being able to understand why the software produces the output it does. This trust is hugely important when adding functionality to existing offerings
Reliability: Linguamatics has been delivering customer success through NLP for 20 years - there are multiple publications and awards that our team and our customers have received that are testament to the reliability of this NLP capability. Quarterly updates to the software as well as ongoing maintenance and management of its wide range of ontologies ensures that the NLP transformations remain at the cutting edge
Robustness: With is scalable architecture, orchestration engine and support for Docker and Kubernetes, the NLP Data Factory provides a pipeline that is fault tolerant and able to handle huge volumes of data. This is essential given the sheer amount of data that exists in unstructured format. This capability enables the needles to be found in the ever-growing haystacks.
The NLP Data Factory changes the paradigm in how organizations like yours can think about harnessing unstructured data. To find out more, watch our upcoming webinar.