September 22, 2021 | Net Health

4 min read

3 Challenges for Implementing Predictive Analytics in Wound Care, with Guidance

It’s pretty safe to say that predictive analytics is the future of wound care at all levels. No matter if we’re talking about a single wound care facility or a comprehensive national network, the possibilities to capitalize on this rapidly growing technology are immense. What’s even more exciting is that even down to the most granular level, implementation can be quite feasible and achievable. That being said, there are some challenges that lie ahead.

In this article, we want to take a look at three potential speed bumps you may encounter when looking to implement predictive analytics in wound care.

Let’s Set the Stage

Before we dive into these challenges, we want to make sure that we’re on the same page about what we mean when we say predictive analytics in wound care and how expansive that horizon really is. Many people are aware that wound care software and solutions are being created to do things like predict patient outcomes and suggest treatment regimens, which is incredibly impactful.

It goes much further, though. Healthcare analytics software utilizing predictive analytics, machine learning, and artificial intelligence (AI) can do things like:

  • Alert schedulers of patients who are more likely to miss appointments or self-discharge
  • Automate certain aspects of clinical documentation, like wound measurements
  • Predict patient healing times and wound-level risks

Understanding the expansiveness of predictive analytics for wound care better frames our discussion of the potential roadblocks and why they matter. With that understanding, let’s talk challenges.

1. Resistance

The biggest hurdle with any change is resistance. There’s a reason there are a million and one cliché phrases alluding to people’s natural resistance to change. And when you start talking about changing the way providers meet, greet, and treat patients—expect to get a lot of resistance.

Is this resistance bad? Absolutely not. What you’re really seeing is your team’s tangible display of their care for your business and the patients.

Thankfully, what this provides is an opportunity for a champion of change to take the reins. By doing things like clearly explaining the benefits of the technology, allowing key decision-makers to have a voice in the process, and showing your support without a “my way or the highway” mentality—the necessary buy-in can be secured to implement these groundbreaking wound care solutions.

Additional Tip: Some providers may feel that predictive analytics are being brought in to replace them. It’s imperative to fully demonstrate that the solutions are meant to be complementary and are designed to augment the quality of care, not to take away anyone’s job or decision-making capabilities. 

2. Trust

The biggest reason for the resistance to change is the need for trust. Providers want to know that the tools and software they’re using to treat patients are reliable, effective, and safe. Where this becomes troublesome with predictive analytics is that you can’t always show the calculations or logic behind the software’s decisions.

If you have wound care software suggesting a treatment regimen and it’s analyzing numerous data points and has been trained on millions of past cases, there’s no time or feasible way to show that to the provider. Instead, the trust needs to be built in other ways.

Think about flying on an airplane as an example. Most of us don’t understand all the complex systems, calculations, and science that go into what makes an airplane safe to fly in. However, we see examples of safe flights every day, we’ve been able to test flying ourselves, and we’ve seen the experts and bright minds behind the technology that gets us safely off the ground and to our destination.

The same process can work for these healthcare analytics solutions. By showing providers as much transparency as possible and allowing them to do real-world testing side-by-side with their classic methods, the trust can be built.

3. Efficiency

The entire point of using predictive analytics in wound care is to provide better care more efficiently. However, if the solution requires brand new systems across the board, extensive amounts of retraining, and a total upending of existing processes, that efficiency goes out the window. And even if the solution is good at what it does, the lost resources of time and money might be a net negative or could spell the end of the practice altogether.

Thankfully, there are wound care technology providers that understand this. We’re seeing many solutions that can be fully integrated into existing systems and come with the customizable flexibility needed to work without fully flipping the script.

In fairness, yes, any new technology will require some retraining and some changes to existing processes—and that’s okay. However, the takeaway here is that if a predictive analytics solution requires too much of an overhaul, you’ll lose efficiency, struggle to build trust, and run into a wall of resistance.   

How Can I Learn More?

It should be quite evident now that not only are predictive analytics for wound care exciting, but they’re going to be something required to stay competitive moving forward. If you’re interested in learning more about the current status and the future of these solutions specifically for the wound care market, we’d highly encourage you to read our free e-book, The Future of Wound Care: Predictive Analytics.

The Future of Wound Care: Predictive Analytics

Changing the way wound care clinics operate and treat patients

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