The healthcare industry produces and gathers a huge amount of data and this data has the potential to be used in predictive analytics modelling to help improve and forecast the demand on healthcare services. There are many ways in which predictive analytics could be used. Some companies are looking at forecasting hospital readmissions and others looking at predicting specific patient illnesses before they become serious.
Inpatient Waiting Times
In Northern Ireland inpatient waiting times are increasing and becoming longer compared with other parts of the UK.
Providers in the healthcare industry must take every precaution to ensure the data they are handling is protected with levels of data security and privacy.
Healthcare systems generate huge amounts of data and this opens the opportunity for data discovery, artificial intelligence and machine learning to provide insight, synchronise data between silos, optimise innovation, enhance decision making and increase efficiency of research.
Artificial Intelligence In Healthcare
There are few (if any) industries that can be transformed by artificial intelligence to the degree that healthcare can. As initiatives around the world seek to digitize healthcare data, there are huge opportunities for game-changing tools and platforms. However, with potentially a yottabyte (1024 gigabytes) of healthcare data in the United States alone, we are no closer to this utopian, data-driven world of healthcare. Data in existence is not standardized, highly fragmented and is stored in incompatible legacy platforms. The technology exists, so why is healthcare so far behind other sectors in utilizing existing technology and what needs to be done to catch up?