Leveraging AI to Address Skill Mismatch in the Healthcare Industry

By April Miller, Senior Writer, ReHack.com
LinkedIn: April Miller
X: @rehackmagazine

While skills gaps are everywhere, they’re especially impactful in healthcare. Increased burnout and rising demand since the COVID-19 pandemic have taken things to new heights as hospitals struggle with staffing.

It’s not just a matter of people leaving the industry. Fewer people are entering the field to begin with, from declining nursing school enrollment to similar drops in other medical roles. Thankfully, things aren’t entirely bleak. Artificial intelligence (AI) could help bridge these growing talent gaps. Here’s how you can use it to that end.

1. Improving Hiring and Retention

One of the best ways to use AI to address skills mismatches is to apply it to hiring. Filling gaps and preventing turnover is largely a matter of finding the ideal person for each position. AI makes it easier to do that in less time.

AI tools can scan resumes or look for passive candidates on job sites like LinkedIn to identify good fits for each open role. They can then reach out to them automatically or suggest them to the hospital’s HR team. Some AI tools can even handle scheduling and negotiate contracts to attract more workers or put people in workflows that work for them.

Applying technology to hiring and onboarding accelerates the sourcing and screening process to minimize the costs and delays that typically come with it. Since AI is good at spotting details humans may miss, it may also be better at finding ideal candidates.

2. Automating Administrative Duties

You can also automate time-consuming tasks with AI to give staff more time with patients. By removing the need to manage the least engaging parts of the job, you’ll help recruits learn faster and prevent burnout. Both of those benefits are key to overcoming current skills gaps.

This automation doesn’t have to be complicated to be effective. Sending automated text alerts to patients, for example, can improve patient attendance rates while saving time and resources. Automated scheduling, data entry and billing all have similar benefits.

Data-centric and predictable workflows are often the easiest to automate. Consequently, applying AI here will lead to a positive ROI in less time, letting you invest more in the workforce to improve training or boost morale. These steps will prevent burnout and turnover to put an end to the labor shortage.

3. Assisting Professionals on the Job

More advanced AI systems can reduce workloads elsewhere. While you can’t safely automate patient care in its entirety, you can streamline it with AI to make smart decisions faster. This assistance will make labor shortages feel less impactful and help newer employees get needed experience faster.

Some AI models can diagnose patients quickly and accurately. Using these systems helps doctors determine the best course of action in less time. Patients get the help they need and doctors get more time in their schedules. Similarly, some AI tools can personalize care plans to tailor treatments to unique patients for more effective care.

Tools like these let you do more with less staff. Since they provide reliable decision-making help, they’re also great educational support for training nurses or medical students. Using them could ensure your workforce has the skills they need in the future.

Obstacles to Consider When Implementing Healthcare AI

As impressive as these AI applications are, the technology does have some challenges to be aware of. It’s easy to get swept up in the AI hype and overlook some glaring obstacles that deserve attention. By contrast, recognizing these challenges will help you use these tools safely.

Bias is one of the biggest concerns for AI in healthcare. Some demographics have a history of being misrepresented in medical data, which creates bias and inaccuracy when you use that data to train AI models. You should ensure any AI tools you use have learned on bias-free data and don’t factor things like race or gender where possible. You should also have a human expert make the final decision in every case.

Data privacy is another potential issue. AI requires a lot of information, and keeping tons of healthcare data in one place is a recipe for privacy breaches if you aren’t careful. Use synthetic data — which doesn’t have any real-world details — or remove identifiers from AI data where possible. Encrypt all AI data sets and limit their access as much as possible.

Finally, you should recognize that AI tools are complicated and expensive. Apply them where they’re most impactful first. Start with simple things, like automating administrative tasks, before moving on to bigger challenges, using the lessons you learned in the first AI rollout. You may also need to train employees to work with AI to use these tools more effectively.

AI Could Be the Solution to Many Healthcare Headaches

The healthcare industry faces some hefty challenges ahead. However, new technologies provide a potential solution. While AI is far from perfect, it can be a huge help if you know how to use it safely.

Applying AI in these three use cases will help you overcome the growing skill mismatch. Doing so can ensure a higher standard of care despite ongoing workforce challenges.