Leading companies like Uber, Google, Delta Airlines and UPS deliver value by using artificial intelligence (AI) to analyze historical data, predict what will happen and suggest the next right action. By applying these best practices in healthcare sector, hospitals and health systems can improve the patient experience, as well as the bottom line.
During the featured session at Becker's AI & Digital Virtual Event, Sanjeev Agrawal, president and COO of LeanTaaS, discussed how AI and machine learning can be used to optimize various aspects of hospital operations ranging from OR block utilization to flow through inpatient units and scheduling in infusion centers.
Four key takeaways were:
- As a country, we can't afford inefficient utilization of valuable healthcare assets. Demand for care is on the rise, but at the same time, more physicians and nurses are leaving the workforce than are entering it. On the revenue side, reimbursement levels aren't increasing. Despite these challenges, asset utilization remains poor. "The average OR utilization in the United States is 55 percent and average net margins for hospitals are zero," Mr. Agrawal said. "The patient experience has never been worse. If we can use advanced mathematics to squeeze assets and serve more patients with the same number of operating rooms, inpatient rooms and staff, that can make a two to three percentage point difference in EBITDA."
- Predictive analytics can transform operating room efficiency. The OR is the economic backbone of the hospital. "More than 60 percent of revenues and often profits come from the OR. Through predictive analytics, we can study surgeon booking patterns, predict the likelihood that someone will use their time and ask them to release time that will go unused," Mr. Agrawal said.
Natural language processing can also be applied for case length prediction. "Tools like these can free up tremendous amounts of OR capacity," Mr. Agrawal said. "Imagine being able to perform between 5 and 20 percent more cases per OR per year."
- It's also possible to use AI to maximize inpatient and infusion center capacity. With data from EHRs or bed-tracking systems, hospitals can precisely predict short- and long-term inpatient census data by day of week, hour of day and by unit. "With that information, you can improve bed turns," Mr. Agrawal said. "By sending the right patient home with what they need and getting the right patient in faster, we've seen organizations improve bed turns by almost 20 percent." With optimized scheduling templates, infusion centers can see 15 to 20 percent more patients.
- Generative AI is the next frontier for healthcare. iQueue Autopilot is the first generative AI hospital operations solution. It can analyze surgical volume and trends, identify which staff will be needed for inpatient units, support OR block time decisions and more.
"The true promise of generative AI is enabling people to work at the top of their license. Through technology, we are headed toward AI-enabled 'air traffic control' for providers," Mr. Agrawal said.
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