Tag: big data in healthcare

Top Tech Skills to Land a Job in Healthcare

By Artur Meyster, CTO, Career Karma.

Even though the inclusion of technology is apparent in many aspects of our lives, the healthcare industry was hesitant about incorporating some forms of technology until recently. But things have changed, and the utilization of tech in the medical sector today is more extensive. More doctors today use apps to consult with patients. And that’s where you come in.

The tech skills we list in this guide will help you land a job in the healthcare industry and allow you to make a tangible impact on this fairly new tech sector. Plus, you will have the opportunity to make a difference that will possibly save lives in the future.

These new developments in the healthcare industry are known as telemedicine, which is a series of apps, wearable devices, and software that improve the consultation experience for patients and health professionals. These innovations open many opportunities for tech workers and allow people in the sector to learn certain tech skills.

The Internet of Medical Things  

The internet of medical things (IoMT) refers to all of the devices, software, and applications that help to monitor, detect, and manage diseases or treatments. These can be connected to other devices, servers, systems, and the internet. The IoMT also collects data and stores it in a cloud or server for doctors or physicians to visualize later. It allows a direct connection between patients and health professionals.

For example, there is a mobile app that can detect when a patient collapses. When it happens, the app will allow your phone to send a stress signal to a healthcare provider or other emergency contacts. Also, there are wearable devices like smartwatches that allow people to monitor their health, this is especially helpful for patients with heart problems.

Other companies are developing smart pills that will monitor the patient’s health from the inside the body. The potential for these technologies are endless and are just in the beginning stage. This market is projected to reach $254,233.6 million in 2026, so if you learn to be a software developer or app developer, you will find a job in no time.

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Healthcare Big Data a Catalyst More So than Electronic Health Records Ever Will Be

Healthcare big data is a big story, and it’s only going to continue being one. It’s a story I like and am intrigued by, but it’s not very sexy. Because of this, the only pieces of information about it seems to be very technical.

Until we actually see how big data changes lives, there’s just not going to be warm and fuzzy stories about it. So, cold and technical it is; nonetheless, I’m still fascinated.

In searching information about the subject, because I too want to know more from a ground floor level, it was nice to come across a nice piece about big data on the Cleveland Clinic’s website.

So, getting right into it, here’s an interesting piece of trivia about healthcare big data directly from the Clinic: “The amount of data collected each day dwarfs human comprehension and even brings most computing programs to a quick standstill. It is estimated that 2.5 quintillion bytes of data are created daily, so much that 90 percent of the data in the world has been created in the last two years.”

Healthcare big data is essentially large amounts of data that’s difficult to manipulate using standard, typical databases. Essentially, big data is very large pieces of information that ultimately, when captured can analyzed, dissected and used to monitor segments within a given sect.

Healthcare big data, it is thought, is what will drive change in care outcomes. What’s interesting, though, is that even though there’s a tremendous amount of data available for use, it’s just not being collected in a structured manner.

Collecting structured data is a must if we are going to begin putting some muscle to the bone of the new healthcare ecosphere we’re putting in place. You don’t have to take my word for it; IDC Health Insights research director Judy Hanover spoke of the same subject recently here.

But, to prove my position, I’ll let Cleveland Clinic make the point: “Unfortunately, not enough of this deluge of big data sets has been systematically collected and stored, and therefore this valuable information has not been aggregated, analyzed or made available in a format to be readily accessed to improve healthcare.”

Also according to the Clinic, if all of the data currently available were used and analyzed, it would be worth about $300 billion a year, reducing “healthcare expenditures by almost 8 percent.”

At the heart of healthcare big data is the hope that it can eventually help providers become predictors. Essentially, big data is like a big crystal ball, or so it’s been said.

According to Cleveland Clinic: “In this way, analytics can be applied to better hospital operations, track outcomes for clinical and surgical procedures, including length of stay, re-admission rates, infection rates, mortality, and co-morbidity prevention. It can also be used to benchmark effectiveness-to-cost models.”

Predictive analytics: That’s what it’s all about.

With all of the attention being given big data and warnings about being prepared for big data so it doesn’t sneak up on you – like meaningful use and ICD-10 – are valid and should be taken seriously.

Efforts are currently underway and available for big data processing and by managing data, “This dynamic data management technology makes data analysis more efficient and useful. Access to these data can also significantly shorten the time needed to track patterns of care and outcomes, and generate new knowledge. By leveraging this knowledge, leaders can dramatically improve safety, research, quality, and cost efficiency, all of which are critical factors necessary to facilitate healthcare reform,” writes Cleveland Clinic.

Big data is a catalyst for change, and without sounding caustic, will be a bigger deal than electronic health records currently are. Without a commitment to it, practices and healthcare systems will be left behind.