The NHS needs to ensure its data is accurate, clean and well prepared for data analytics
By Adam Wilson, CEO Trifacta
The Healthcare industry in the UK faces greater challenges than many other industries when it comes to adopting the latest technologies and innovations. The NHS in particular has large, fragmented IT infrastructure which contains legacy systems marked by remarkable complexity. This hinders the efficient use of information across the NHS and slows down digital transformation.
The recent ‘Future of Healthcare’ strategy which was released by the UK Government in October is looking to address these challenges. It introduces a plan for creating national open standards for data to enable more efficient healthcare and better use of resources. In addition, the Government is planning to launch five new centres of excellence, leveraging artificial intelligence to help improve early diagnosis of disease, including cancer by detecting data abnormalities.
To be able to make the most of all this information, the NHS needs to ensure its data is accurate, clean and well prepared for data analytics. Without preparing the data sufficiently, the NHS will suffer the garbage-in, garbage-out syndrome of data analytics. Only with high-quality, clean data to feed AI algorithms, can meaningful insights be extracted.
Here are a few examples of the key data challenges facing modern healthcare providers and how data preparation can help address them.
The complexity and volume of NHS data makes preparing data very laborious and time consuming
There is no lack of data in the NHS but the volume and complexity of the data means it can be difficult to wrangle into a format usable for analysis in a timely manner. For instance, healthcare data comes in multiple formats and from hundreds of data sources, including connected e-health devices, patient records and diagnostics tools. There are even multiple different applications for the same purpose between Clinical Commission Groups (CCGs).
What’s more, the siloed nature of the data—as it is often scattered in different parts of the organisation—can make it difficult to access. Many NHS analysts are preparing this data using different data preparation tools, creating even further fragmentation. As a result, data preparation requires a huge amount of time and resources to sift through the fragmented data and standardise it in a format that’s meaningful for analysis.
The fragmentation of data preparation tools increases the risk of data errors
Consolidation of NHS IT is not easy and past efforts have achieved mixed results. As a result, there is a lot of IT fragmentation in the NHS, not only of data sources but also in terms of IT systems and data preparation tools. This creates problems of standardisation, anomaly and error checking across the different departments of the organisation and makes it difficult to centrally manage and govern the data preparation process.
One way to address this challenge is by automating and standardising the data preparation process into one intelligent data preparation platform. This approach allows healthcare providers to standardise the data preparation process to ensure they can cross-reference data across multiple systems and extract insights from unstructured clinical data. This reduces the risk of manual errors and significantly improves the efficiency of data analysis, the process which follows the data preparation stage, to deliver more accurate data insights.
Streamlining the data preparation process can help the NHS provide better healthcare services
Intelligent data preparation helps improve the quality of the data used for data analysis which helps deliver more accurate data insights. Due to this it can play a key role in improving diagnostics, treatment and prevention of diseases. Accurate data insights can help enhance the understanding of patient problems and enable healthcare providers to identify trends which will help them with healthcare research, improving patient services and aiding decision making.
For instance, Trifacta is working with the healthcare tech start-up SymphonyRM, to accelerate the data preparation process and enable healthcare providers to get faster access to data insights in order to deliver better patient care. This has enabled SymphonyRM to speed up data preparation by 90%, allowing its customers to rapidly analyse multiple sets of clinical and consumer data and deliver better services to patients.
As data and analytics are becoming more important to the transformation of the national healthcare system, embracing an intelligent approach to data preparation will be key for improving patient care.
