May 4, 2023 | Net Health

3 Minute Read

Enter a New Age of Wound Care with Predictive Analytics (Ebook)

Can you imagine a world in which clinicians could predict patient healing times based on the current size and shape of a wound, or the risk of amputation based on current oxygen levels?

You don’t need to imagine it. With predictive analytics, a new age of wound care is here. 

Predictive analytics is the latest configuration of healthcare analytics to be deployed across clinical, administrative, and back-office settings throughout the wound care market.

What Are Predictive Analytics in Wound Care? 

As the name might suggest, predictive analytics leverage machine learning functionality — or algorithms that identify patterns within historical data — and apply it to current data to predict outcomes. 

Within wound care, predictive analytics empower clinicians to make far more informed and data-driven decisions. One example of predictive analytics in patient care is the ability to accurately forecast wound trajectory to administer more effective treatment.

Predictive analytics utilizes various data points to improve the efficacy of clinical and operational wound care solutions, including wound characteristics, patient parameters, and vital signs.

Wound Characteristics and Composition 

Machine learning identifies care patterns among wound characteristics such as tissue composition (granulation, necrotic, subcutaneous, slough, and eschar), periwound descriptors (temperature, texture, and color), size (length, width, and depth), and location.

Patient Parameters and Demographics

Predictive analytics illuminates previously unrecognized connections in wound care between individual patient parameters, like the history of certain cancer or other diseases, as well as patient demographic information such as age and sex. 

Point of Care Vital Signs 

Machine learning associates vital signs at the point of care, such as blood pressure, heart rate, and weight, with congruent data points to assess the efficacy of wound care and better forecast the timeline to patient discharge. 

How Does Predictive Analytics Impact Wound Care?

While it’s obvious how predictive analytics allow for more data-driven wound care, it’s less clear how these data points can benefit patient outcomes or clinic efficiency.  

On the surface, predictive analytics provide insight into wound trajectory; however, clinically, they help to identify a plan of care with the highest propensity for healing based on current wound characteristics and patient parameters. 

Within wound care facilities, predictive analytics help clinicians identify patients at risk for self-discharge or missed visits, to eliminate empty treatment rooms and reduced revenue and instead create new avenues to engage patients in their care.

In other words, predictive analytics enable wound care facilities to remain one step ahead — of both patient wounds and patients themselves — to allow for the most productive, profitable care. 

Discover How to Leverage Predictive Analytics in Your Clinic 

Predictive analytics provides clinicians with data-driven insights that enhance treatment decisions, reduce patient healing time, and improve clinical outcomes. 

Right at this moment, clinicians are running predictive analytics scenarios to assess how the application of a procedure could affect the healing trajectory of a wound, or gauge the likelihood of a patient attending their next appointment. 

Discover how you can leverage predictive analytics to bring your clinic into the new age of wound care with our latest’s ebook, “The Future of Wound Care: Predictive Analytics.”

How Clinics are Leveraging Predictive Analytics to Improve Clinical Outcomes

Download this free ebook to reveal how predictive analytics is driving the future of wound care.

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