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As COVID Continues, Can Hospitals Create Better Bed Management Through Math? | NEWS-Line for Healthcare Professionals

As COVID Continues, Can Hospitals Create Better Bed Management Through Math?


The COVID-19 pandemic shined a spotlight on a significant healthcare problem: a sudden inundation of critically ill patients can take a hospital’s bed capacity to the limit – and beyond.

“COVID threw healthcare into an enormous temporary imbalance, especially early on as hospitals struggled to manage the influx of patients,” says Sanjeev Agrawal, co-author with Mohan Giridharadas of Better Healthcare Through Math (www.leantaas.com).

“Now there are concerns that another wave of the virus will once again put hospitals and their bed capacities to the test.”

Agrawal and Giridharadas, senior executives at LeanTaaS, a software company that focuses on improving healthcare operations, say that while the pandemic may have exacerbated the problem with hospital bed capacity, it didn’t create it.

Hospitals have confronted a lack of bed space for years, struggling to figure out how to match the never-ending admissions and discharges with the available capacity, often with mixed results.

“For patients, solving this problem is critical,” Giridharadas says. “If you’re in urgent need of care, you want that bed to be available. If you are already in the hospital, you don’t want to be discharged prematurely because the hospital failed to plan appropriately and needs to open up your bed for someone else. At the same time a lot can be done to facilitate smoother and quicker discharge both from a planning and process perspective.”

LeanTaaS is among those attacking the problem, in their case using technology and math to stabilize the mismatch between admissions and discharges. The company’s software monitors what hospital beds are in use, what beds are available, what the anticipated admissions are, and what the anticipated discharges are. The software even makes recommendations to the hospital staff for how to best maximize space.

“Dealing with hospital bed capacity can be much more complex than people realize,” Agrawal says. “All beds aren’t interchangeable. The hospital doesn’t want to place COVID patients with non-COVID patients. If someone just had hip surgery, they would prefer to put them on the orthopedic floor where nurses are trained to handle their specific needs. At the same time every unit has a ‘fingerprint’ – a unique pattern of patient discharges and demand patterns that can be predicted with some degree of accuracy to help make key decisions around bed placement. It’s like working a puzzle.”

But the rewards of solving that puzzle are great, both for the hospital and, especially, for the patients, Agrawal and Giridharadas say. Those rewards include:
Patient care is improved and wait times are reduced. Even when a hospital is able – eventually – to accommodate everyone who needs a bed, those patients may still have had to spend a significant amount of time waiting in the emergency department or in a post-surgery recovery room before a bed is freed up. “But if hospital staff can review the data and get a better understanding of all the options before the problems even arise, they can then make proactive, rather than reactive, decisions,” Giridharadas says.

Any backlog of elective surgeries can be dealt with more quickly. One way hospitals address bed shortages is to postpone elective surgeries. But such postponements lead to a backlog that eventually must be addressed. “All of the elective surgeries that were postponed during the COVID-19 pandemic still needs to be completed at some point in the near future,” Agrawal says. “Tracking the backlog can be a challenge. Here once again is a situation where using online tools with built-in math intelligence can be a huge help.”

Less chaos during the day. At the best of times, patient placement leaders and house supervisors have a hard time balancing the availability of beds with the need both actual and expected. Since discharges typically happen in the afternoons and bed demand starts earlier in the day, life can be quite chaotic in trying to find “the right bed for the right patient at the right time,” Agrawal says.

Hospital staff can focus on other issues. When the hospital staff is able to spend less time on the bed problem, they can move on to other issues. “That means they can do their overall jobs more effectively and more efficiently,” Giridharadas says. “That’s better for the patients as well.”
“A lot of people manage hospital capacity based on their personal backgrounds, experience and preferences,” Agrawal says. “But when you move to a data-driven way of decision making, people become more effective in their roles and hospitals are better organized, managed more tightly, and make better use of their physical resources.”

About Mohan Giridharadas and Sanjeev Agrawal

Mohan Giridharadas and Sanjeev Agrawal, co-authors of Better Healthcare Through Math, are senior executives at LeanTaaS (www.leantaas.com), a software company that focuses on improving healthcare operations. Over the past six to seven years, LeanTaaS has conducted thousands of conversations with physicians, nurses, administrators, and healthcare executives to understand the issues they face. LeanTaaS has invested well over $100 million in building software products that address these problems by mathematically matching supply and demand for healthcare assets, and helping more than 100 leading healthcare systems in the United States realize substantial improvement in operational performance.

Source: LeanTaaS

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