Royal Philips surveyed almost 3,000 healthcare leaders around the world and found that while workforce shortages are exhausting providers and leading to delays in care, many are hoping that AI and automation technology can help ease the burden.

"It's showing a very clear pattern that the health and well-being of care providers and the burnout they're facing is driving a direct impact to the quality of care that they're able to deliver," Jeff DiLullo, chief region leader for Philips North America, told HCB News.

During the pandemic, many healthcare workers experienced stress and burnout, leading them to retire or transition to another career. On top of that, the rising aging population and comorbidities are putting more stress on fewer workers.

"To me, it's the flywheel effect,” DiLullo explained. “The more pressure you put on the people that are remaining, the faster they're likely to make a decision to move into another line of work.”

Philips detailed these findings in its ninth annual Future Health Index survey, which was published yesterday. Not only does it reflect the leaders' concerns, it also explores their excitement for ways that future and existing technology can address these problems.

Almost all — 88% — of the respondents think that technology that can automate repetitive tasks and processes is part of the solution. At present, 53% of them are using this technology to automate patient check-ins and appointment scheduling.

DiLullo described NYU Langone Health as having "one of the most digitized hospital ecosystems" that he's seen in the industry. Because of their technology, the nurses can scan something on a phone such as the administration of a medication and it automatically ties to the patient's medical record.

"Think about 10 minutes an hour for every single nurse in that network," said DiLullo. "It's a massive savings of time, but you have to choose to decide to digitize your enterprise."

In the next three years, 44% of the respondents plan to implement automation for workflow prioritization to allow clinicians to take on high volumes of patients without having to sacrifice on quality. Other areas of interest include equipment maintenance and monitoring, billing processes, clinical data entry, and clinical documentation.

AI is a big area of interest, but 79% of the leaders reported concerns about the possibility of data bias exacerbating disparities in health outcomes. DiLullo gave an example of a hospital in Tennessee that may use personal biomarkers in that demographic area to lead generative AI to make conclusions about diagnoses for cancer or Alzheimer's disease.

He explained that if you're building on a data set of a reasonably homogenous population, you can create biases against another population. An example of that could be West Memphis, which is largely an African-American population and may have completely different biomarkers.

"The truth is the bias is going to be there because you can't have it be perfect," he said. "Our view is to make it a diagnostic tool that informs and guides a radiologist, and they should always make the determination because they're the person that's trained."

Something that nearly all — 99% — of the leaders agree on is that there are opportunities for data-driven insights to improve care. The challenge is bringing all the data together from disparate sources — 61% citing a desire to improve interoperability between different platforms or healthcare settings.

One area of interest is population health analytics. Philips is helping hospitals use data science to start looking for population trends so they can shift their priorities of care to where it's needed the most.

"It's not mainstream yet, but it's the power of common interoperable data that we're pulling from our devices or other devices to create that ecosystem of patient-level data," said DiLullo.