Predictive analytics is the trending buzz word. Articles on LinkedIn talk about what predictive analytics can do for a company. Predict the number of orders, and adjust the warehouse to meet it. Save money but knowing just how much of a certain product to produce. It’s the latest and greatest, and will slice your egg, and straighten your hair. There is nothing Predictive analytics can’t do.
Working in Health Care, we had to keep data in silos. Patient data had to be maintained with certain standards. We had treasure troves of data, buried all over the Data Warehouse, and none of it linked.
Through-put in the clinic is call Turn-Around Time, or TAT. The clock begins when a patient is checked in, and ends when a patient is checked out. TAT was tracked, modeled. The question remained, how did the patient respond to time in the clinic? Ultimately, as a clinic, we wanted to get the patient thru quickly. Through-put matters. Each minute a patient is in the clinic means that the staff is busy taking care of that person. If we can move them through in a more efficient manner, we can get more people through the clinic and make more money. In the patient surveys, the number one thing that patients complained about was their time in the clinic. That was their favorite things to gripe about. Naturally, we set about figuring out how to speed up the process.
Since I’m a naturally curious person, I linked the Patient Satisfaction surveys with their actual time in the clinic and analyzed the results that way. I expected I would see that as clinic got faster, and got their patients out more quickly, they would see huge gains in patient satisfaction. Ideally, we wanted the patient to be in and out in under 70 minutes. Maybe 85 when we were being generous. Instead I found that patients were quite happy being in the clinic for 200 minutes! That was more than double what we were aiming for. Further analysis showed that patients tended to prefer a slightly longer visit. Patients felt that if the visit was short, the doctor may have missed the right diagnosis. The patient wanted to spend more time, probably with the doctor. They wanted a full explanation of the medicines they were prescribed. Essentially, patients wanted to spend about 1 ½ – 2 hours in the clinic so that they could trust they had gotten the right diagnosis.
By linking the data up, I was able to see that we were pushing the patients out of the clinic too fast. By pushing them out so fast, it leads to patients who failed to take their medicine. Patients called in to ask questions about their prognosis. It pushed the work to other places. Based on this analysis, we looked at our goals in more detail. What were we trying to accomplish?
Predictive Analytics brought context to the discussion. We had to reevaluate our goals around TAT. Were our goals about clinic efficiency, or were they about providing a positive patient experience? We now knew that patients were happy spending 90- 150 minutes in the clinic. Armed with our new understanding, we had to weigh the choices. Our patients wanted to spend more time with our most costly resource, the physician. Or at least spend more time with a well-informed nurse.
We, at Saxony Partners believe that providing fresh perspectives—and fostering an environment in which new perspectives are taken seriously–contributes to our clients’ success and sets us apart. We seek to be open-minded and to allow the data to determine how a product or process should be created or improved. And we do so with a passion for getting our clients and their customers what they need, when they need it. When you partner with us, you partner for success.
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