Peter Ford, public sector industry principal at Pegasystems, writes about the need to improve the quality of care in the NHS, but in order to do so we must use the country’s resources intelligently, drawing on the right tech at the appropriate time.
The last month has seen multiple announcements relating to the future of the country’s healthcare. On the Department of Health and Social Care’s 100th Birthday, UK health chief Chris Wormald both lauded the organisation’s achievements and also highlighted its limitations. His speech pointed to the importance of balancing ‘quality’ rather than ‘length’ of life as an organisational target.
Secondly, Boris Johnson announced an additional £1.8 billion grant to shore up service provision in the NHS on some twenty hospitals that need renovation and improvement. This was met with the usual derision from the press that this falls far short of what is needed.
Finally, there was an announcement from Matt Hancock regarding plans to establish an Artificial Intelligence Hub in the NHS. However, sceptics have voiced that this move might be ‘tech for tech’s sake’ rather than an effective use of the NHS limited resources (perhaps better directed to the aforementioned basic hospital improvements).
Yet other research stresses the importance of technology. The Deliotte Government Trends 2020 report highlights that the citizen experience in government is paramount and this will be supported by technologies and techniques such as Artificial Intelligence (AI), proactive government and nudge (behavioural science) amongst others. Citizen centricity is important but how can this be achieved in a way that avoids the risks associated with transformational change with the available funding envelopes?
What the above illustrates is a desperate need to improve the quality of care, but in order to do so we must use the country’s resources intelligently, drawing on the right tech at the appropriate time. So, with the need for ‘smart’ investment, what are the key health and social welfare issues that prevail that need attention first to provide the best service for UK citizens? And where should investment in new technologies be directed?
Use information assets and automate end-to-end processes.
With higher patient expectations and increases in life expectancy, a growing number of citizens require pre-emptive advice to promote better health. Leveraging the insight trapped in the UK population’s medical data can make the difference. But with more data and complexity than ever, unlocking this insight is increasingly difficult. Consequently, opportunities for preventive measures and the most efficient corrective care are not always taken.
To succeed, the NHS needs an easy, accurate and reliable way to create and incorporate predictive analytics and decisions into every process and interaction. Coupled with other technologies such as interactive business process management, robotic automation and context sensitive, transparent, guidance and decisioning, AI should bring both improvements in patient care at the same time as similar enhancements in operational efficiency. AI alone will not result in the desired outcomes. It needs to be part of wider scheme for data use, end-to-end digital process automation and citizen engagement to ensure this investment delivers desired outcomes.
Use the hospital assets for the purpose they were intended.
Make sure people are in the right beds. Move people from acute hospital beds at high cost and supported by highly medically trained staff to lower cost, high quality rehabilitation beds. The use of AI and analytics to inform trends on overtime and temporary staff plus identification of likely increases in demand would help set the right levels of staffing and other infrastructure provision. Integration of data from different sources within the NHS and agencies outside of it could also inform where different supply options for beds provides the best value for money.
Use the private sector.
With sufficient online information to inform on likely shortfalls in public sector rehabilitation beds, the private sector could be used. Analysing the particular needs of a patient based on case history, clinical guidance and rules, and AI to inform what the best options might be could improve the care a patient receives and create space in public sector hospitals.
Joined up agencies.
Healthcare and social welfare are inextricably linked. What happened in one domain often gives rise to demands on the other. Using data from all agencies to inform policy at a macro and local level as well as inform operational considerations around capacity should be the ambition. The delivery of social welfare by local government versus centralised provision of healthcare has caused issues and orchestration of inter-agency sharing of information is imperative.
With increasing use of analytics, AI, remote consultations based on data generated by wearable devices and various other we must not forget that clinicians and other staff require the training to adequately exploit this technology to its fullest. This extends to the use of information – data scientists in the NHS!
To truly improve the quality of patient care leaders must not throw money at the NHS without understanding whether the baseline service delivery is operating at its optimal efficiency otherwise the ingrained issues will persist. It is crucial they use assets, particularly data, human resources, beds etc. in the most efficient fashion. They must also remember to train staff to use the technology to give insight on demand and supply so the best choices can be made in options available. Although these ideas might not be the panacea, following these steps would certainly act as a well-needed catalyst for change.