Streams of data are flowing all around us. With advancements in technology, the speed at which this data is accessed is faster than ever. And we can’t seem to get enough.
Data analytics have become a compelling wave of interest in healthcare as it offers improvements to several facets of medical care and informs healthcare leaders about how to outperform the competition in a rapidly changing environment.
With our obsession with data, it is becoming increasingly easy for provider organizations to feel overwhelmed. Where do healthcare organizations even start? When you’re dealing with something as delicate as patient care, how do you find the right balance between utilizing information technology and ensuring empathy and compassion remain the focal point?
Percentages, bar graphs, row after row of data is typically how analysis is presented. While this may be impressive, what does it really mean? What can you do with it and because of it? A good place to start is to identify and define the problem around who it is affecting and what you are trying to achieve. Build a story around the data, and state what needs to happen and why.
Take, for example, the amount of time staff spend on the clock before or after a scheduled shift – referred to as incidental worked time (IWT). This is an important metric to monitor and offers an easy way to reduce labor costs.
Because there are clinical justifications that cause IWT, such as staying a little later to ensure a smooth shift transition for a high-acuity patient, most organizations have a reasonable tolerance level. However, according to Avantas research, these situations only make up about 40 percent of all IWT occurrences, leaving more than half of them deemed unnecessary and preventable. On average, there is an opportunity of more than twenty-thousand dollars in annual savings tied to IWT for a single nursing unit. These are dollars that could be invested elsewhere, such as new medical equipment.
Leadership can use analytics to monitor how much IWT is occurring on a unit and determine if it could be reduced. They can point this out to the unit manager and tell him or her that their staff needs to be in and out on time, without taking into account any underlying causes. This type of approach will likely not do anything to lower incidences of IWT.
A more empathetic approach would be to talk to staff to determine reasons why their shifts are stretching longer. Maybe one staff member is just innately prompt. To them, being early is on time, and being on time is late. This is an opportunity for the manager to explain how clocking in before the time they are scheduled is actually hurting the department.
Perhaps another staff member is struggling to get their charting completed in a timely manner because of a new electronic records system. The root cause is determined and the manager realizes this staff member needs additional training and education on the new charting system. By the manager spending time with their staff and seeing the issue from their perspective, it connects staff members to the solution that drives results.
As we become more reliant on data for nearly every aspect of our lives, it’s important not to lose sight that data is only meaningful if we can make sense of it and use it to make impactful improvements. When considering how to optimize your workforce to improve patient care and organizational outcomes, approaching analytics with empathy and compassion will guide your organization to significant results.