FOTO Rehab Outcomes Blog

3 Ways Predictive Analytics is Different than Fortune-telling

Written by Selena Horner | Sep 19, 2016 9:30:00 AM

Predictive analytics could help improve healthcare, right? Would patients appreciate knowing what might be the final results from rehabilitative services? Could clinicians improve care based on predictive analytics? Since predictive analytics has relevance, is it something to be trusted or is it comparable to fortune-telling?

 1. Fortune-telling does not have a rational basis. Predictive analytics uses statistical algorithms and a large database. The goal in rehabilitation is to predict the final outcome in services.

2. Fortune-telling uses many mediums depending on the fortune-teller: tea leaves, crystal balls, palms, the stars, black cats, cards... and the list goes on and on.  Predictive analytics uses data. 

3. Fortune-telling provides a final, unchangeable prediction.  Predictive analytics provides an opportunity to change the future. The predicted outcome allows for clinical reflection. Clinicians can use the provided information to drive conversations with their patients. Clinicians can use the predicted outcome to drive clinical decisions. There are times that the patient can surpass the predicted outcome, depending on the factors within the predictive algorithm that can be changed.

And... since I'm in a giving mood:

4. Fortune-telling is for fun. Predictive analytics is for hope, patient engagement, clinical decision-making, benchmark reporting and higher payments.

Typically with predictive analytics, a robust risk adjustment process is included in the algorithm to allow for a fair comparison of patients for a more accurate prediction. I've been thinking about predictive analytics because this isn't something commonly found in healthcare. I found a recent article about the growing need for predictive analytics quite interesting.

The likelihood of 100% accurate predictions is improbable for both fortune-tellers and predictive analytics. The accuracy of predictive analytics lies in how well all the factors that affect a patient's outcome can be identified and accounted for in the risk adjustment process. Science continues to grow in the area of risk adjustment. Although 100% accurate predictions is improbable for now, having somewhat of an idea of a patient's final outcome is helpful. The key is in tracking a patient's change during the course of services to ensure the change that is happening thoughout the course of the episode of care is heading toward the anticipated outcome.

FOTO is one of the few systems that includes predictive analytics as a key feature. If you are searching for a product that is based on predictive analytics, please talk to Judy Holder. FOTO can definitely be a solution for you.

Until next time,