ai can fix the crisis in healthcare labour costs how
AI opens up many exciting possibilities in healthcare, and it’s easy to get stuck on the most interesting ones, like diagnosing scary diseases, talking to curious patients, and figuring out who is most likely to have an emergency. In each of these situations, mistakes can have huge effects, regulators will have high expectations, and workflows will be in place for a long time. Changes will happen slowly in these fields.
A much more immediate chance is to deal with labor costs, which are a major problem for health systems.
Because of these labor costs in healthcare, the industry’s finances are getting worse and worse.
Premier, a large buying group that works with hospitals, says that hospital labor rates went up 6.5% last year, while Medicare reimbursement rates went up only 2.7%. The gap is even bigger in some fields that have had to rely more and more on contract workers. For example, contract nurses’ median hourly rates are expected to rise from $64 to $132 an hour between 2020 and 2023, while their hours are expected to rise by 91%. So, the amount the health system spends on hiring is up 27% from last year. Workers are leaving the healthcare industry at a high rate because of things like burnout and getting older, so the industry must make better use of the workers it has and keep them. If they don’t, the consulting firm McKinsey says clinical labor costs will keep going up at a rate of more than 11% per year until 2027. It’s scary for the business.
Changing how nurses use their time
Since nurses often make up more than half of the staff in health systems, how they spend their time is an important place to look. According to a study in the Permanente Journal, medical-surgical nurses spent 35% of their time on paperwork and 21% on coordinating care. In comparison, taking care of patients took 19% of the time, giving out medications took 17%, and evaluating patients took only 7%. Yes, more than half of the nurses’ time was spent on paperwork and talking to other people instead of directly caring for patients.
AI can do these things in a lot of different ways, like keeping track of patients’ vital signs and writing updated notes for the health record. Some of the biggest names in health IT have already started pilot projects to bring generative AI, like the kind used in ChatGPT, to these specific use cases. If these pilots work, it will not only cut down on the need for labor but will also give nurses more time to do the kinds of things that made them want to become nurses in the first place.
Improving Day-to-Day Management
The way front-line staff are managed is a second important place to look. Laudio is one example of an AI start-up that is working in this area. CEO and Co-Founder Russ Richmond says that better front-line management can cut staff turnover in health systems by 20–25% per year and increase employee engagement scores by more than 20%.
For example, if we see that someone on the team has been the only experienced nurse on a shift for the last five or seven shifts, we can suggest that the manager check in with them to see how they’re doing and make any necessary changes to the schedule.”
First, the customer, then AI
Laudio’s method is similar to that of successful tech start-ups, which don’t focus on IT until they’ve solved the customer’s problem. Over time, put together a list of what actions work best in what situations. This list can be very different, for example, between an ICU and an environmental services team.
When healthcare institutions take this user-centered approach, they can save money on hiring, contract labor, labor rates, and other labor costs. There is a lot of loosely managed work and work that doesn’t touch a patient in the healthcare field. AI can help fix these problems by making staff more efficient and giving them more time to spend on direct patient care.