FOTO Rehab Outcomes

Oct 08, 2017 | Selena Horner

Physitrack or FOTO for Your Rehabilitation Outcomes

The world of rehabilitation outcomes and all it entails: measuring, managing, marketing, negotiating and engaging now has value to clinicians and leaders within the walls in which rehabilitation services are provided.  Products are being created to jump into the outcomes world. Products that were originally created to serve a specified purpose are now being designed with add-ons to increase diversity.

Earlier this summer, I read something in MedCity News that had me contemplating why Physitrack would be compared with FOTO.

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Oct 01, 2017 | Selena Horner

Musculoskeletal Service Delivery in Primary Care

Typically when I voice my thoughts on working with physicians, the immediate response is negative in nature. The responder's immediate thought is physician self-referral and that conflict of interest. This sadly limits the conversation and also limits the ability to think of possibilities. The physician shortage is real and affecting patients. In my little town, patients may wait 3-6 weeks before being seen by their primary care physician for an acute condition. A patient scheduling for a preventative care physical typically waits about 6 months for that particular appointment. I have worked on educating my patients about patient self-referral (direct access). The physicians have been supportive. I continue to wonder "what if?" What if physical therapists were in primary care physician offices to be part of the team to help improve access to care so care is delivered in a more timely manner? Now that times have changed, the idea of physician self-referral is not really an issue in that setting because most physicians have sold out to hospital organizations.

The study I am sharing digs into the "what if" I've been wondering about for years.

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Sep 24, 2017 | Selena Horner

What Makes a Good Clinical Prediction?

When it comes to predicting outcomes, one of the most important questions you can ask is, "how much variance is explained?" The savvy person focuses on this question because the accuracy of the prediction depends on the response to this question.  If a prediction is used for future decisions, like quality payment programs, then you want the most accurate prediction possible.

To have 100% variance explained is quite improbable.  Teams creating prediction models are focused on as high amount of variance explained as possible.

How much information should patients be providing to help explain variance?

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