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How AI and Data Visualization Work Together to Make Healthcare Healthier

Artificial intelligence (AI) is on everyone’s mind lately. In fact, a recent episode on CBS’s 60 Minutes was devoted to this topic. “The Oracle of AI,” Kai-Fu Lee, said that he believes, “…it's going to change the world more than anything in the history of mankind. More than electricity.”

When it comes to the healthcare arena, the effects made available through AI—and the resulting data visualization (so people can recognize data in the form of charts, diagrams, graphs, pictures, and the like)—are equally (if not even more) profound. Together these advancements are moving healthcare forward in leaps and bounds. As healthcare providers see, understand, organize and use these revolutionary tools they are able to deliver better, more informed, cost-effective patient treatment decisions.

Is AI revolutionizing healthcare…or is it all hype?

The answer to that question is that AI is doing a lot of BOTH (and the innovative tool is constantly changing and evolving).

“For decades, artificial intelligence has held science fiction-like promise,” according to MedCityNews. Today, “…one of AI’s biggest promises lies in the healthcare field…to help improve healthcare, starting from early stage drug discovery all the way to patient care.” It can be a game changer, but it’s too soon to tell.

At its simplest, artificial intelligence is allowing patients to check on their appointments, get reminders for their medications, and have answers to questions such as “can I get a nurse,” “when do I take my medicines?” Plus AI holds immense promise in helping healthcare professionals interact with their patients, extract insights and value from massive quantities of patient data, and make diagnosis quicker and easier.

Perhaps that’s the reason Healthcare Informatics states that, “Three out of four healthcare executive leaders (77 percent) report that the pace of investment in big data and artificial intelligence (AI) is accelerating at their organizations.”

2019 is an amazingly critical year for the advancement of AI in healthcare. The formation of the Alliance for Artificial Intelligence in Healthcare (AAIH) is a positive development and recognition that establishing standards and best practices will be crucial for companies to hone their AI tools. AAIH believes that, “Patients’ lives will be improved through investment, innovation and the thoughtful and responsible application of AI in the discovery and development of new therapies. 

Healthcare Analytics says AI is becoming a major transformational force in healthcare.

AI makes medicine smarter these 7 ways.

AI is a powerful technology that can play a major role in improving individual and population health when implemented judiciously, especially when you are able to take the resulting data and make it easier to understand and use through data visualization approaches.

For example, Healthcare-Informatics reports that:

  1. AI can be used to generate insights based on data and analytics that may have been otherwise missed.
  2. AI has the potential to improve the quality of care and reduce costs by preventing unnecessary tests and procedures.
  3. AI can accelerate diagnoses and improve access by better utilizing resources.
  4. AI adds value while improving patient outcomes and access
  5. AI is not only a stated goal but also an imperative for survival of health systems in the emerging value-based integrated care environment
  6. AI thrives, based on data-centric architecture, but data but needs to be aggregated, cleansed and organized, and turned into visual media (like charts and graphs) to support AI projects.
  7. AI assists physicians to make smarter decisions in the point of care, the taking off hassle and uncertainty from the viewing patient scans and diminishing physician burnout.

 

In healthcare, there’s an AI and data talent shortage.

Modern Healthcare tells us that, “One of the main issues with artificial intelligence is that it requires a lot of data. That, in turn, requires data scientists who know how to work with all of that data and make it visually useful. The problem is that data scientists are in very high demand, and there's an incredible amount of competition for their skills (and not just within healthcare).”

It's going to take some time to train people from within or outside. One of the interesting things is that you can find very smart, talented, capable people outside your organization, but when you bring them in, they'll still have to learn your tech stack, processes, policies, maybe even industry. That can be a long learning curve, too. 

Additionally, you have to train your medical staff (physicians, nurses, technicians, etc.) and administration personnel to tap into AI and data visualization advances. That takes substantial time and expertise, as well.

What can you do to make AI work for you?

You can turn to outside consultants to educate healthcare staff on the myriad uses for AI and deliver valuable knowledge and expertise, on how to make the resulting data easy to visualize and understand. Plus, consultants can step up and help you meet temporary or ongoing staffing needs.

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