In today’s technological landscape, terms like “big data,” “artificial intelligence,” “machine learning,” and “predictive analytics,” are being thrown around more often than ever before, sometimes interchangeably. But it’s important to understand that all of these concepts are not synonymous. The term that we are going to focus on in this post is predictive analytics (one of our favorites!)
Some things we will cover:
- What does predictive analytics mean?
- How does it apply to the healthcare industry?
- What are the values and benefits?
- Has Covid-19 had an impact?
Predictive analytics: defined
There are many highly technical definitions of predictive analytics, but to put it simply, the phrase refers to the use of statistics and modeling techniques to make predictions about the future. Predictive analytics is a subset of Artificial Intelligence and can be use for nearly anything, but for business applications, the most common predictions are about performance outcomes.
In order for predictive analytics to benefit a company, the collected data have to be understood, and broken down into some sort of insight or metric that can be acted upon. Without any modeling techniques being applied, these pieces of data are what we know as “key performance indicators” or “key efficiency metrics.”
The concept of predictive analytics isn’t altogether new. Many industries and disciplines have been using it for years. Some examples include:
- Credit scoring: credit history and records of like borrowers are used to calculate and predict risk
- Marketing: shifts in demographics and the economy are looked at to understand what new target audiences will look like, and if the current product mix needs to be shifted as well
- Netflix: “Because you watched…” lists are highly curated based on data that have been collected about you and similar users
So, what do these functions look like for the healthcare industry?
Well, there are – not surprisingly – countless data points that can be collected from practice management systems, electronic health records, billing records, and patient portal interactions. These data are extremely dense, unique, nuanced, and – also not surprisingly – difficult to measure.
But the bottom line is, medical practices are still businesses. They have constantly changing demand just like any other company, and the use of predictive analytics makes quantifying and improving business operations that much easier.
The benefits and values of predictive analytics for the healthcare industry are no small thing, either.
Without even touching on the benefits for the medical professionals – like patient risk scoring, and other preventative care measures – there are so many benefits that can be found in the scheduling aspect of healthcare.
Some of the benefits include gaining a better understanding of patient behavior. For example, knowing which parts of the day are the busiest can help providers plan accordingly. Additionally, understanding the likelihood of certain reimbursements and the varying ranges of those reimbursements can help increase revenue for certain medical organizations.
Has Covid-19 had an impact?
So, the short answer is a resounding yes. Notably though, the Pandemic did a great job of highlighting where problem areas lie within our current healthcare landscape. Researchers, lawmakers, and medical providers alike are now understanding how predictive analytics models can help make decisions when it comes to allocating resources, predicting surgeries, and preventing physician burnout.
Additionally, the struggle around the spread of misinformation also gave a push into big data analysis. We are now better equipped with methods that allow for efficient consolidation of information and optimized communication to everyone.
To Sum it All Up…
The use of predictive analytics has been around for a while, but different industries are finding more and more ways to utilize the benefits to improve their business operations. Where healthcare scheduling is concerned, Opargo’s predictive analytics technology can improve the efficiency of the whole practice, simply by optimizing how patient visits get scheduled. But Opargo doesn’t just stop there. We use these analytics and additional data to drive the overall Artificial Intelligence engines ongoing to deliver long-term results.
To learn more about what we can do with predictive analytics and artificial intelligence, reach out to one of our healthcare scheduling optimization experts.