As the NHS reaches its 70th birthday, its senior leaders and the Government have called for a "technological revolution" to tackle the increasing challenges and pressure the service faces. In this context, artificial intelligence (AI) solutions have been receiving growing attention within the healthcare industry.
In particular, the large-scale digitisation of NHS electronic health records, provides opportunities for the use of advanced analytics and machine learning techniques to transform the analysis and interpretation of healthcare information.
“The PwC team have been great to work with, bringing 'out of the box' thinking that has helped us to implement, proactive and innovative ways of working, as well as to gain the buy-in of key clinical stakeholders. PwC have been able to combine their in-depth understanding of the healthcare industry with an expertise in AI and machine learning, which has enabled them to automate parts of our administrative practices, whilst improving overall coding data quality.”
Leveraging on electronic health records, we have used a range of AI techniques including machine learning to drive deep insight from large volumes of unstructured data in NHS Trusts. This has allowed hospitals to increase the accuracy with which they capture patient information, generate more detailed healthcare insights and improve clinical outcomes.
Specific benefits for hospitals include being able to predict length of stay more accurately for individual patients (allowing for more effective capacity planning), to gain a better understanding of local healthcare needs, and to receive funding that is more accurately matched to the treatments that are provided. Our work has allowed hospitals to free up administrative capacity and focus their time on more complex patient needs.
In particular, our readmissions modelling has supported actionable insights into 'at risk' patient groups. This allows for both immediate improvements in care management, as well as supporting the wider strategic design of aftercare and clinical pathways.