One of the silver linings of the COVID pandemic was a new trust put into future technologies that people wouldn’t have otherwise needed to depend on. In the commerce world, the closures of storefronts caused a boom in ecommerce, a trend which is expected to continue long after the pandemic has finally ended. The food industry became a lot more dependent on delivery and take-out options, and this trend is also expected to hang around.
For healthcare, an industry completely flipped on its head by the virus, the remote work trend resonated a bit, with advancements in telehealth becoming necessity for consultations as many hospitals had to repurpose many of their wards to deal with COVID patients. Telehealth allows for both patients and providers to save time on travel, and save money on hospital space, reducing the cost of care for a patient. Here is a look at two other future technologies that are expected to shape the way we are taken care of at a hospital or similar site of care.
Wearables (Think Fitbits)
Wearable technologies are not only great resources of personal information that can be used by healthcare providers, but they are also becoming trendy simply as a fashion accessory, and there’s nothing wrong with a win-win! The fashion aspect tends to end with the watch-style fitness trackers like Fitbit, but many other wearable healthcare devices are becoming less invasive and more effective as monitors for different ailments.
Smart heart watches track the wearer’s heart rate and can provide crucial information to doctors to help prevent against heart-related issues, including cardiac arrest. Similar watch-style devices exist for patients who need to watch their blood pressure or blood sugar, great sources of information for those with concerns of high blood pressure or diabetes, respectively.
It is encouraged for anyone who is purchasing a wearable health tracker to take a deep look at the privacy agreements, as health data is some of the most sensitive in existence and should always be handled with the utmost care.
Machine learning is an aspect of artificial intelligence where machines are programmed to digest data, and make predictive analysis relative to data they received in the past regarding a similar situation. A simple daily example would be a website offering you “other products” based on your purchase. These machines have “learned” that someone who buys item X often buys item Y, and thus the machines have learned to market item Y to people who are interested in item X.
Machine learning advances in healthcare are aplenty, but some of the most promising uses include robot-assisted surgery and photo analysis, but even things like staffing nurses has been improved with this technology.
Robot-assisted surgeries scare a lot of people, but truth be told, they are more successful than their human-performed counterparts. With machine learning, these robot surgeons are able to notice any potential issues before they happen, based on a network of information shared by the entirety of machines performing the same procedures. When it comes to photo analysis, machines that do the analysis “learn” trends in the photos, not much different from the computers that learn the trends of what people buy online. Using this knowledge, swarths of photos (such as MRIs or x-rays) can be analyzed in a fraction of the time a human technician could do so, leading to faster responses, ultimately saving lives.
With no shortage of funding, and the primary motivation being saving human lives, healthcare technology advances as quickly as anything else in the world, and wearables and machine learning are still fairly new technologies, meaning their ability to grow is exciting and almost unlimited.