About the author Orlando Agrippa has over 10 years' experience as an Information Systems Leader and Director in the UK NHS, with an impeccable focus on clinical systems delivery, business intelligence and analytics. Orlando has spent time understanding the US healthcare system and has worked in Australia as a director of analytics transformation. With a track record of enhancing executive success in public and private sector organizations of varying scale and complexity. It is widely accepted that artificial intelligence is about to revolutionize many industries, despite the fact that there are still valuable practical examples of its success. So how can this promising technology live up to this hype? It is clear to me that to deliver on this promise, it must be used to make a real and positive difference in ways that transform lives and fundamentally benefit society. Some industries are more advanced in applying this technology: retail and manufacturing, for example, have taken the lead, using AI to improve the customer experience or trusting the man with the most thankless tasks to optimize their efficiency. However, this new approach is likely to address some of the most persistent societal problems in other sectors, particularly in the healthcare and pharmaceutical space, where the focus of patient care and assessment needs to change. The perception is that industries, at all levels and in many sectors of activity, are about to completely review their mode of operation and will soon be structured in a completely different way. Currently, 40% of companies believe that their business models will simply not exist in the next five years. The transfer of this sentiment to the healthcare sector and the potential benefits are not only exciting, but truly transformative. Think about hospital readmissions: the ongoing challenge for healthcare professionals, and often the result of balancing efficiency and customer service.
(Image: © Image Credit: Rawpixel / Pixabay)
The challenge of readmission.
This might be considered controversial, but hospitals in their most basic form are very similar to hotels or factories. They need to work effectively to get people into the system, focus on providing the most profitable processes, and be closely tied to that, providing the best customer experience. Getting out of the hospital as quickly as possible is not only an advantage for the hospital, it is what most patients really want. But there is a good balance. Releasing people too soon has devastating effects on the patient and the hospital. Patients discharged too soon will be readmitted, some with more severe complications than before, adding to the burden. But healthcare professionals are under tremendous pressure to keep up the flow of patients in order to reduce the number of blocked beds or blocked patients, people who stay in hospitals longer than they should. When this pressure causes a patient to be released early, the impact on trust is enormous and the hospital's experience is questionable. Consider again the metaphor of the hotel and the factory. What is the cost of losing confidence when a large number of cars are recalled due to a process problem at a factory? Also, what is the impact on the customer experience if someone rushes to check in at the end of a dream vacation?How can AI help?
Using artificial intelligence technology as an assistant in these circumstances can make all the difference. By leveraging the vast amount of patient data available, hospitals have the ability to implement advanced algorithms to predict the impact of different circumstances in which healthcare professionals become more adept at managing. In this way, AI and machine learning turn out to be an indispensable tool to maintain the flow of patients. It has the ability to predict the impact of patient demographics on the speed with which they will evolve in the system, allowing hospitals to have the right resources and avoid even spikes in demand or potential problems. to react to circumstances. . Of course, it is difficult to overcome the years of clinical experience and the experience used by health professionals to assess the physical condition of patients: to make strategic decisions about bed allocation and future healing. That being said, using machine learning to process the same data and assist clinicians at all levels provides a better understanding of the patient journey. It allows professionals to focus on providing the best treatment and make strategic decisions, based on data they would never have access to before. Some pioneering hospitals are already developing strategic partnerships with AI-capable companies and vendors. However, in discussion with my NHS colleagues, it is clear that a lack of understanding of what this actually entails and how to implement it with ever thinner budgets is a reluctance. With approximately 1 million patients passing through the NHS each day and 4,3 million people awaiting treatment, running this plant well is a task that needs to be done on a large scale. The pressure for people to enter the system is growing rapidly, and readmissions are becoming more frequent as a result. This not only makes the patient experience negative, but also puts more pressure on the system. Helping to solve this problem will literally transform lives and benefit society.
Image Credit: Shutterstock (Image: © Image Credit: All Possible / Shutterstock)