This blog post is courtesy of a special guest contributor, Kendra Perley, an Avantas team member. She offers a unique perspective on how trusting new technology has impacted her life.
Change is hard. Novelty can often feel scary and overwhelming. Change is something I’ve had to become well acquainted with since my life changed at the young age of seven. On a hot summer’s night in July, I was diagnosed with type 1 diabetes.
From that point on, my world revolved around finger pokes, insulin shots, nutrition and carb counting – all things most grade school kids aren’t excited about. But life went on. I adjusted to my new lifestyle of checking blood sugars, following a strict no-sugar diet, and took my insulin shots as prescribed.
You may be wondering what type 1 diabetes has to do with predictive analytics and volume forecasting for nurse scheduling. Surprisingly, more than you might think.
I spent 15 years injecting myself with insulin at least four times a day. I’ve seen a lot of syringes in my day. I’ve also seen a tremendous amount of innovation in technology with how type 1 diabetes is treated. For example, insulin pump therapy.
Insulin pumps have been around for a while now, but I didn’t decide to get one until I was in my early twenties. I wasn’t keen on the idea of having something attached to me 24×7, and in all honesty, I wasn’t ready to give up that much control to a tiny little machine.
I had spent more than half of my life being the control center of my diabetes management. But in truth, I wasn’t that great at it.
Getting my insulin pump set up, I spent hours with my endocrinologist, nurses, and diabetes educators entering all the information I needed into my pump to make it work for me. Like any new technology, there’s a learning curve and tweaks to be made as you start putting it to work.
Almost immediately I saw the benefits of an insulin pump. My blood sugars got better, but there was still room for improvement. Even after wearing my insulin pump for years, my doctor was puzzled as to why we couldn’t improve my blood sugars even more. That’s when I had to fess up. While I had given control over to this new technology, I was doing a lot of overriding based on the fact that the calculations my pump gave me simply “didn’t feel right.”
After all, it was my body and my illness – no one knew it like I did. How could I trust a machine? It took some convincing, but I decided to give full control to my insulin pump and take the amount of insulin it was telling me to based on its calculations. And something incredible happened, my blood sugars got over the plateau and were the best they had ever been. I trusted the pump and it did exactly what everyone was telling me it would.
When nurse managers and healthcare leaders hear that analytics and technology exists that can accurately predict nurse staffing and scheduling needs, it is often received with some suspicion. How can it do that?
Analyzing historical census data and other metrics to look for trends and patterns that recur over time, predictive analytics can forecast patient volume, allowing managers to align the appropriate amount and type of staff needed as far in advance as 120 days from the start of the shift.
Just like I did with my insulin pump, unit and department managers often believe that no one knows their department better than them, and they schedule their staff according to their own intuition. It is a significant change to implement a technology that is based on data and statistics rather than a person’s gut feeling. And the reality is that organizations will likely fail to achieve their expected ROI because people often do not trust the predictions.
But predictive analytics is not a hands-off technology. Predictions are made with organization- and unit-specific data, and it takes nuanced local information like room closures or new overflow capacity to make predictions even more accurate. A provider organization and a vendor must partner and communicate about any changes that might be happening at the unit level to ensure that the predictions are accurate, and become even more accurate over time.
Predictive analytics can help hospitals and health systems work smarter, analyzing the metrics they have readily available to make accurate staffing predictions. But much like how I felt about my insulin pump, trusting new technology doesn’t always come so easily. But with the right amount of data and a little bit of faith, success is possible.