I had a truck similar to this. The first couple of winters I had my horse at home, I completely errored in calculating the amount of hay the darn thing would eat during the winter months. I'd use the old truck to have a local farmer drop a huge bale of hay in the truck bed. Every time I got in that truck, I had to crank open the window to adjust the mirror and then slide over to the passenger side and repeat. The truck was a bit stubborn and I had to pump the gas pedal a bit... and the keyhole was a tad finicky and required just the right touch to actually be able to turn the key to start the truck. Since it was a stick shift, I had to remember to use the clutch to start the thing. Then, when driving, I had to pay attention to the sound of the engine to shift at the appropriate time. It wasn't difficult to listen to the engine because there was no sound insulation whatsoever. The truck didn't have 4-wheel drive capability, so I had to know the weather to ensure the day I was picking up hay was a day without loads of snow.
In the 1970s and 1980's there were no outcomes measurement systems. We were beginning to see outcomes measurement tools in that time period. The options were like the 1970's truck. Clinicians were required to choose the outcomes measurement tool. Then, someone had to go print it out. The outcome measures back then were all paper and pen tools. The tools were static: what I mean by this, the patient was required to respond to the full sheet(s) of questions. Clinicians had to manually score the tool. (This meant clinicians needed to know the scoring formula, had to have a pen and calculator nearby AND had to know what to do in the event a patient skipped a question.) The measurement tools were designed to be interpreted only for the individual patient who completed the tool. Since the tools were so new back then, the design didn't recognize the concepts of ceiling and floor effects. These design flaws led to less accuracy and less responsiveness in capturing change. The measurement tools were not designed to be used to compare the results of services provided to multiple patients. In other words, putting the scores into a database and analyzing groups of scores were outside the scope of the tool design. As a heads up, the original, archaic measurement tools are still in existence and used today. Although the tools are the same, the delivery model feels high tech and intelligent because a web based platform is used for collecting the data and reporting results. The design flaws have not been addressed and, sadly, the science behind the measurement tools is ignored. Aggregated data for archaic measurement tools is worthless for determining effectiveness or efficiency of care.
Fast forward to now. Think of today's trucks.
Outcome measurement systems now exist that are almost as automated as today's trucks. The better systems will have full integration capability with other software systems to streamline your workflow and reduce waste. The systems are smart systems and intuitive enough to reduce your patient's burden when it comes to answering questions. Real systems are built with sophisticated technology that addresses the original flaws when outcomes measurement tools were first designed. Computer adaptive testing is not a regurgitated, archaic outcomes measurement tool. Computer adaptive testing does four things: individualizes the test for each patient, reduces the time to complete the test, substantially reduces ceiling and floor effects, and improves responsiveness to more accurately capture change. Because comparing patients and results was not accurately possible with the archaic tools, the new systems are scientifically designed to overcome that hurdle to address the need for fair comparison. This is accomplished by thorough research to identify patient factors that impact outcomes. The better systems can define those factors and indicate how much of the difference between patients can be explained. These factors are used to risk adjust patients. Once patients are risk adjusted, the next step is predictive analytics. The individual patient dashboard will indicate both an expected outcome and how well the patient is doing compared to other similar patients in the system. This is based on predictive analytics. The clinician or clinic dashboard will indicate how well the clinic or clinician is doing in achieving predicted outcomes. Because outcomes measurement tools have evolved over the last four decades, you now have an option that addresses not only the shortfalls of the 1970's, but also a nearly automated system that allows for fair and accurate quality assurance.
This week FOTO Team will be excited to see many of you at the American Physical Therapy Association's Combined Sections Meeting in Anaheim, California. Stop by Booth #259 to better understand why FOTO is the standard in outcomes measurement. In the event you are really curious, no worries, I can share a bit here for you. Just click and learn more.
What differences do you see between measuring and managing outcomes in the 70's compared to now?
Until next time,