Artificial intelligence is a term that is as vague as it is powerful. The decision-making processes of today’s business leaders have moved heavily towards information technology and away from intuition, but the word that is driving this change sounds like it was ripped from a science fiction story.
Over the course of its history, AI has evolved from descriptive, to predictive, and finally to prescriptive analytics and each of these steps represents a different way that the computer is able to recreate human thought. Let’s take a look at how AI has evolved over the years. (more…)
Isn’t it curious when two intelligent people examine the same information and draw opposite conclusions? That is the dynamic I thought was at work recently, when The New York Times ran an opinion piece called “Are Hospitals Becoming Obsolete?” one day before The Wall Street Journal published an in-depth report titled “What the Hospitals of the Future Look Like.” Based on the headlines, I expected one article to focus on hospitals’ pending doom and another on their rebirth.
But it turns out only the headline writers were betting on obsolescence versus evolution. The articles’ authors agree that hospitals are undergoing radical changes and they cover much common ground about current trends and where the sector is headed. What do they think hospitals of the future will look like? Here’s a rundown. (more…)
Predictive analytics is increasingly key to powering hospital initiatives that maximize efficiency, realize cost savings, and help deliver superior care. Predictive analytics is not new to healthcare, but it is more powerful than ever, due to today’s abundance of data and tools to understand it.
How – and why – are hospitals putting predictive analytics to work? The goal is often to improve operational efficiency or to proactively provide services that prevent greater problems and spending. Many hospitals have started with applications aimed at reducing readmissions and predicting which patients are at risk of developing sepsis. Other common use cases focus on optimizing staffing and resources. Here are three other examples of hospitals successfully putting predictive analytics into action. (more…)
Predictive analytics is a topic generating great hype and great hope in healthcare and other industries. As this area of data science matures, it is important to remember that predictive analytics is not defined by one technology or technique, although it can be roughly divided into two approaches: pattern recognition and simulation.
Pattern recognition is the most common approach, the foundation of much-hyped machine learning and artificial intelligence. Simulation is another, more human alternative to understanding business problems, predicting future trends, and recommending optimum decisions. In this blog, I explain the essentials of simulation and highlight three of its advantages. (more…)
Predictive analytics is a technology whose time has come. In healthcare, hospitals are beginning to use advanced analytical techniques to improve patient outcomes and optimize operations with some impressive results.
Predictive analytics is the process of learning from past data to make predictions about future outcomes. Several factors have set the stage for the emergence of healthcare predictive analytics in 2018 and beyond. In this blog, we will consider three reasons why the time is right. (more…)
2017 was quite an eventful year in the healthcare industry. There was a lot of discussion about technological innovation, such as artificial intelligence and blockchain, and the impact this technology could have on healthcare. In addition, this year was marked by attempts to repeal the Affordable Care Act, as well as discussion around and implementation of new forms of payment in healthcare such as value-based care models.
What will 2018 bring in healthcare? Will providers be able to take advantage of predictive analytics? How will data and analytics impact healthcare’s ability to measure population health? How will providers gain more trust in their data? Here are some of my thoughts on the future role of data and analytics in healthcare. (more…)
Healthcare is inarguably facing some of the most daunting challenges today, with the potential repeal of the Affordable Care Act (ACA), the uncertainty of the American Health Care Act (AHCA), numerous other regulations with which providers must comply, new payment models, and much more.
At our recent Dimensional Insight Users Conference (DIUC17), Julie Beard from KLAS Research spoke at a couple of our breakout sessions about some of the biggest healthcare challenges providers indicate they are facing today and where the industry is headed. (more…)
Dimensional Insight’s powerful Diver Platform puts extensive data visualization options at your fingertips. It provides quick access to large volumes of data and dashboards that help you transform insights into measurable information. So, wouldn’t it be great if Diver could integrate statistics into dashboards? Well, it can!
In this blog post, we will show you how to leverage the muscle of R, the data scientist’s go-to statistical computing and graphics language, with Diver. With R, you can have interactive forecasts and predictive functionality right in your DivePort dashboards. (more…)