How AI and Healthcare Management Are Merging

Digital technology and healthcare services are easily integrated in the science-fiction world. In the real world however merging the two has been more challenging. Our understanding of digital technologies just doesn't match what sci-fi writers imagine. But we are getting closer. In fact, artificial intelligence (AI) and healthcare management are now beginning to merge.

AI offers a lot of promises for better healthcare delivery. From improved diagnostics to remote surgical procedures via robotics, AI will eventually be capable of doing things we never imagined. But what about the here and now? How is AI improving healthcare management as we embark on a new year?

A Brief Introduction to AI

Before discussing how AI and healthcare management are merging, it is important to understand the basics of the technology. AI is commonly misunderstood as a technology that makes machines independent of human thought. This is not what it is.

AI utilizes a combination of deep learning and neural networks to analyze data and reach conclusions. It is a particularly good tool for doing certain kinds of tasks, like predictive analysis for example. It is also useful for automating digital tasks. But AI is limited. Machines cannot know what they don't know. Moreover, they cannot figure out how to learn that they don't know.

The deep learning portion of AI relies on machine learning principles to give computers the ability to infer conclusions based on previously analyzed data. Neural networks take deep learning to the next level with algorithms that react to encountered data by comparing unimaginable amounts of information. The two work together to give machines the ability to 'learn' artificially.

Implications for Healthcare Management

With a basic understanding of AI, it becomes easier to see how it can be applied to healthcare management. We are already seeing its implementation in a number of ways.

1. Improving Workflow

Artificially intelligent computer systems improve workflow through automation and data analysis. This is very easily seen in the electronic health records arena. Data entry and record management are reduced to single-entry tasks that are then turned over to AI systems that handle everything else. It all adds up to comprehensive record-keeping that offers record access across the entire healthcare spectrum.

2. Better Diagnostics

AI's ability to crunch large volumes of data represents an unparalleled ability to analyze and compare information across unlimited data sets. This leads to better diagnostics among clinicians. How so? By comparing a patient's current data with reams of historical data involving past cases. The historical data provides a clearer picture of what a patient is currently dealing with. Better diagnostics is the end result.

3. Improved Risk Management

Insurance brokers and carriers will be happy to know that AI makes for better risk management. Again, it is all about data. Predictive analytics opens the door to assessing patient risks well in advance. It opens the door to advising patients about the best ways to take care of themselves to avoid future illness and injury. It all leads to improved risk management through better preventative medicine.

4. More Virtual Care

AI's emerging capabilities are quickly moving us in the direction of providing virtual care by way of automated apps, robotics, etc. We will be able to rely more frequently on virtual solutions for primary care, freeing up medical professionals to concentrate on more serious needs.

As healthcare becomes more technologically advanced, AI will play a greater role in management. AI and healthcare management are merging in ways that will completely transform how we view service delivery. Perhaps that means a healthier population and lower across-the-board costs