In the past few years, the healthcare industry has undergone an ample amount of changes. These changes are more in the ways how the healthcare industry stores data. Moving backward in our distant past, remind us of the old paper-based method to keep health records. It doesn't exist anymore in our present. Instead, we have new data-keeping methods, i.e., online digital records where storing & sharing information is easy.
Microsoft UK has reported an "encouraging increase" in the use of artificial intelligence (AI) technologies in healthcare. In a survey of the use of AI in UK industry, 46% of healthcare leaders reported their organisation used the technology in some capacity, reflecting an 8% increase compared to 2018. The biggest growth areas reported were research-level AI, which grew 13% in the past 12 months. Robot process automation (RPA) and general automation both increased by 10%, while the use of voice recognition technology increased by 9%. The study, conducted by YouGov, included the input of some 1,000 business leaders and 4,000 employees.
The Internet of Healthcare Things is coming -- and for all intents and purposes, it's already here. According to a new report by Aruba Networks, by next year, 87 percent of healthcare organizations will have adopted IoT. Moreover, more than three-quarters of these organizations believe the technology will completely transform the healthcare industry. As IoT is injected into everything from X-ray machines to patient monitors and hospital meters, networking demands will change and providers will need to revamp cybersecurity to address an increasingly connected threat landscape. But alongside these infrastructure needs will come several benefits and an increased return on investment for care organizations that choose to embrace a connected future.
The healthcare industry is currently suffering from a host of issues. Knowledge sharing between hospitals, determination of patient adherence to medications, and the efficient management of surgical procedures are just three topics in a long list of areas that need improvement. All of these issues have the same thing in common: the healthcare industry has a data problem.
Building off my last post, I want to use the same healthcare data to demonstrate the use of R packages. Packages in R are stored in libraries and often are pre-installed, but reaching the next level of skill requires being able to know when to use new packages and what they contain. With that let's get to our example. When working with vectors and strings, especially in cleaning up data, gsub makes cleaning data much simpler. In my healthcare data, I wanted to convert dollar values to integers (ie.