Future-proofing the healthcare industry
Technology is advancing at a rate of knots. And given that it’s hard enough for an individual to keep up with it, it’s no surprise business are struggling. To add to this, the healthcare industry is commonly known as being one of the slowest adopters of new technology. However, with increasingly fickle customers, rising costs and fierce competition, industry players can no longer afford to sit back and wait.
In order to future-proof itself, the industry needs to adopt a bold strategy and a new approach. To do this, it needs to move away from being a “disease-care system to a healthcare system”.1 This is where technology can play a crucial role, specifically through advancements in content and data storage, retrieval and analytics as well as automation through the use of machine learning and robotics process automation (RPA).
Using cloud as a safe and secure data storage technology and ensuring the data is quickly organized, managed and easily and readily accessible through Pragmatic Content Building and Data Encoding and Extraction platforms, the industry can help streamline and future-proof its processes to keep up with today’s technologically-evolving times.
Unlike current and traditional Optical Character Recognition (OCR) methods, these platforms can enable players to automatically capture structured and unstructured data from a number of sources and formats - both textual and non-textual. They can also analyze the data to provide valuable insights, leading to actionable intelligence. In fact, such tools improve performance, reduce manual input times and errors. Further, the speed and efficiency of being able to manipulate of all of this data can lead to reduced costs and can be implemented through both machine learning and RPA.
Machine learning can be used to leverage the healthcare industry to a higher level. It can help provide faster diagnostics through ‘deep learning’, which “contextualizes the imaging data by comparing it to large datasets of past images, and by analyzing ancillary clinical data, including clinical reports and laboratory studies.” 2
In addition to this, players can apply RPA to “rules-based, labor intensive and error prone processes in the healthcare revenue cycle…everything from patient registration to coding to claims to audit.” 3
Thus, it is apparent that the benefits of the industry looking further into certain technological adoptions are manifold. Players must be inclined to drop their traditional thinking methods and adapt to today’s changing times. In the long-run any investment in some of these new tools, platforms and methods will not only assist individual players but uplift the healthcare industry as a whole.