The importance of approaching healthcare analytics with empathy

Artificial intelligence (AI) is weaving its way into healthcare whether patients know it or not.

AI has become a compelling wave of interest in healthcare as it offers to improve aspects of medical care and inform healthcare leaders how to advance in a rapidly changing environment. But are there circumstances when human compassion prevails over the rapid problem solving ability of machines? Of course.

The rapid digitization of health data has created opportunities to improve healthcare. Provider organizations seem to have become obsessed with dissecting their data to uncover valuable insights that can increase efficiencies and control costs. Healthcare data analytics can help hospitals and health systems work smarter, analyzing the metrics they have readily available.

While it can be muddled for someone who does not live and breathe in the world of AI and computer science, there’s a significant leap from using advanced mathematical techniques, such as predictive analytics, to help solve problems, and giving computers license to make those decisions independently.

One area of healthcare that remains beneficial to retain empathy is in workforce operations. Scheduling and staffing can benefit immensely from advanced mathematical techniques, but approaching analytics with empathy is essential.

For example, in hospitals, the amount of time staff spend on the clock before or after a scheduled shift – referred to as incidental worked time (IWT) – is an important metric to monitor. 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 research conducted by Avantas, these situations only make up about 40 percent of all IWT occurrences, leaving more than half of them deemed unnecessary and preventable.

What may be surprising to staff and managers is that a few minutes of extra time a staff member spends on the clock can aggregate to hours at the unit level, potentially meaning thousands of dollars being spent on preventable IWT occurrences each pay period.

A department leader can use analytics to monitor how much IWT is occurring on a particular unit and determine if it needs to be reduced. The leader can go to the unit manager and tell him or her their staff needs to be in and out on time, without considering the underlying causes. This type of approach will likely not do anything to lower incidences of IWT.

An 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. They most likely think they are being helpful. With the right education, this scenario can be curtailed.

Or perhaps another staff member is struggling to get their charting completed in time because of a new electronic records system. The root cause is determined and the manager realizes this staff member just 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, rather than just a metric, it connects staff members to the solution that drives results.

Big data and advanced analytics can certainly reveal insightful information. But without understanding what story the data is telling and what actions should be taken to make improvements, data is just a collection of numbers – sitting impressively idle. Data is not perfect, and algorithms are not magic. It requires a clear-eyed view to filter out emotional responses to the data to avoid errors.

Predictive analytics is a tool to be used in combination with extensive knowledge of staffing strategies; it will not solve all of an organization’s problems alone. Experts are needed to routinely monitor predictions and functional leaders within the healthcare organization need to make sure it is being applied as intended.

There is a lot about healthcare that is complicated. But what stays constant is that compassion and empathy are the foundation of providing patient care. As technology and data continue to drive improvements and offer insights, it’s important to remember that it is people who are able to make developments to the delivery of care. When considering how to optimize the workforce to improve patient care and organizational outcomes, approaching analytics with empathy and compassion will guide the organization to impactful results.

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