Automation software tech set to blast health care into the future
It is easy to see that technology is changing a number of different industries, including healthcare. The way health clinics provide care is changing faster than some might have predicted, and it is changing what people expect from them. Although there are a number of technologies that have been driving change in the modern healthcare industry, there is one that has the potential to fundamentally shift the way the industry conducts business – and it’s automated data collection and analysis technology. Here’s a look at how the technology is poised to disrupt the medical profession, and the effects it is going to have.
The Scale of the Challenge
The reason that this specific area of technology has the capacity to have such a large impact on the industry has to do with the sheer volume of data that healthcare providers collect. Industry analysts estimate that the global healthcare industry will have created 2 zettabytes of data by 2020, and that’s only considering the types of data currently collected. By comparison, the total annual traffic on the global internet was only 1.2 zettabytes in 2016.
A Variety of Data
One of the major challenges that the healthcare industry faces in making use of the mountain of data they’re collecting is that it is coming from multiple disparate sources. Those sources include electronic medical records (EMR) systems, Internet of Things (IoT) devices, and things like patient surveys and insurance information. The data produced isn’t standardized, and the quality of the data differs from source to source. That makes sorting through the information to derive meaningful insights difficult and time-consuming, and simply beyond the capabilities of healthcare staff alone.
A Change Over the Horizon
For the healthcare industry to make efficient use of the data they’ve been collecting, it must be filtered and synthesized into a usable form. That’s where the latest in machine learning technology comes into play. The technology has reached a level of sophistication that makes it a perfect match for the task of dealing with large volumes of both structured and unstructured data. The software can be built to find specific types of information within a variety of data sources and can apply judgment to determine the value and utility of what is located. Best of all, the software will continually learn from the data it reviews, and even request human intervention when necessary.
Healthcare Staff Unleashed
Machine learning software is going to reduce the amount of time medical professionals spend inputting data or matching symptoms to causes. By leaving the task of data collection and analysis to computerized systems, healthcare professionals will find the answers they need exactly when they need them, with far fewer misdiagnoses. While manual research can miss a possible cause, a learning computer will not. In essence, this kind of software is going to streamline medical treatment to patients and make it more effective, taking care to the next level.
One issue that many hospitals deal with on a regular basis is medical errors. Some of these errors happen because there is a mix up with paperwork, which usually starts with a mistake when reading a patient’s medical history. Collecting unstructured data through automation should help ensure that these types of errors are reduced or even avoided as the technology advances. This may also reduce the chances of incorrect prescriptions due to overlooked information in the patient’s medical history.
Care without Borders
Another aspect of the medical industry that is probably going to change is the way patients are transferred to a general health care provider to a specialist. This task takes a while because the doctor needs to make sure insurance coverage extends to the specialist. Any treatment options need to be covered as well. The automation technology software being introduced should be able to peruse through some of this information and find matches in a manner of seconds, making the patient experience much easier.
Of course, this just represents some of the changes the industry could expect, and some hospitals are already taking advantage of these new technologies. There is no telling what other changes could take place as technology continues to advance, but the current outlook is bright. Modern machine learning and data analysis systems point the way towards a future of efficient, effective medical care, which is an outcome that providers and patients alike have reason to cheer.
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