Artificial intelligence: a savior for overwhelmed health care personnel?

During the past two years and counting, hospital and health care staff have been overwhelmed by the COVID-19 pandemic with droves of workers quitting their jobs as part of the Great Resignation. Could artificial intelligence (AI) play a role in helping fill some of the gaps? A recent flurry of stories suggests it could.

Hospitals such as Cedars-Sinai Medical Center in Los Angeles are turning to AI — computer systems or computerized programs that perform tasks normally done by humans — for help with assorted tasks, according to a story in Becker’s Hospital Review. Cedars-Sinai has employed twin clinical assistant robots to reduce nurses’ daily workload. The robots, which feature heart-shaped eyes that light up or make beeping noises, use AI, machine learning technology and social engineering to interact with clinicians and patients, performing simple tasks such as collecting medicine from the pharmacy. Within six weeks of their implementation last September, they saved clinical teams an estimated 300 miles of walking.

The technology comes at a pivotal time. Roughly 6% of hospitals (329 of 5,540) reporting staffing levels in the nation are experiencing critical staff shortages, according to data from the Department of Health and Human Services posted March 2 and reported by Becker’s. Meanwhile, about 17%, or 950 hospitals, are anticipating shortages within the next week. The three states with the highest percent of hospitals experiencing critical staff shortages are South Carolina (26.67%), Kentucky (21.7%) and Nebraska (18.95%).

“Stress has become a serious issue for physicians in recent years,” Robert Budman, M.D., chief medical information officer at Nuance Communications, told Healthcare IT News, in an article on leveraging AI to relieve physicians. “First, physicians have to navigate how to get their clinical work done in a busy day. On top of that, there are administrative burdens placed on them by the government, insurance plans and employers. And then, there’s simply the crush that they are feeling with their workload being exacerbated by COVID-19.”

Some AI technologies can allow health care organizations to alleviate workers’ pressure by anticipating nursing or ED staffing needs, or predicting turnover of beds, or can help address clinical documentation frustrations, Budman said.

Here are some novel uses of AI reported on recently:

  • Clinicians at Ochsner Health in New Orleans implemented an AI-based scheduling system for anesthesiologists. The tool provided more flexibility for anesthesiologists’ schedules and led to significantly improved physician engagement, Healthcare IT News reported.
  • Researchers at the Regenstrief Institute and Indiana University used machine learning models trained in statewide health information exchange data to predict a patient’s likelihood of being hospitalized with COVID-19, as reported by Healthcare IT News.
  • Researchers at Stanford and Johns Hopkins started a pilot to use AI and machine learning to help physicians triage patients, helping predict whether a patient is likely to need intensive care unit-level care or the assistance of a rapid response team, as reported by Becker’s Hospital Review.
  • University of Utah and Intermountain Primary Children’s Hospital investigators developed AI tools to mine data from electronic health records to help predict the onset and outcomes of cardiovascular disease, according to a Healthcare IT News article.
  • The Veterans Health Administration is working with tech company Cogitativo on a project using AI to identify beneficiaries who deferred care during COVID-19, Healthcare IT News reported. Their algorithm is combing electronic records to identify 12 clinical conditions, including diabetes, chronic kidney disease, and atherosclerosis, that could be exacerbated by delays in services.

While health systems are tackling these challenges, some patients frustrated by difficulty in booking appointments or long wait times to see overloaded providers are turning to do-it-yourself care at home, according to a recent article in The Wall Street Journal. Ordering home testing kits to measure hormone and cholesterol levels and detect food sensitivities, one woman reported making her own changes: adjusting diet, adding supplements and eliminating eggs. Test kits, devices and mobile apps are some of the tool’s patients are turning to.

The approach could miss larger problems, and patients are not necessarily skilled in interpreting lab results, cautioned clinicians who spoke to the Journal.

Journalists could find trend stories looking at what AI applications are being used in a particular specialty such as cardiology, or local stories looking at what their local or regional hospitals might be doing to employ such technology. The American Medical Informatics Association (AMIA) and the Health Information and Management Systems Society (HIMSS) have meetings coming up where AI projects likely will be the subject of several posters.

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