By Neeraj Bhavani, Founder, Tagnos
February 2021– For hospitals, operating rooms (ORs) are big business. The current pandemic is affecting this business in unprecedented ways, but the following shows how the ORs generate revenue and how they can optimize it, while improving throughput and patient satisfaction.
One recent survey found that the four types of physicians that generate the most revenue for hospitals are surgeons. Cardiovascular surgeons head up the list, producing an average of $3.7 million annually per physician.
Concurrently, ORs represent substantial costs for hospitals. Each minute in the operating room costs at least $36, two-thirds of which constitutes labor costs, according to a study published in JAMA Surgery. These opposing forces combine to create significant challenges for hospitals.
Causes of OR inefficiency
Because hospitals receive such a large percentage of revenues from the federal government, they cannot simply solve the problem by negotiating higher prices. Instead, hospitals must boost OR efficiency.
The good news is that there is lots of room for improvement. For example, a 2016 study of three urban hospitals found that 88% of the first surgery cases each day were delayed. The primary cause of the delays, according to the researchers, was people – patients, physicians and clinical staff.
Other factors that contribute to OR delays were lack of prompt notification to environmental services teams responsible for cleaning the rooms, as well as difficulty in communicating among care teams, which remains a challenge in some instances due to inadequate communications equipment and other times due to the sheer number of individual members of a care team.
What hospitals can do about OR inefficiency
In recent years, many leading hospitals and health systems have turned to real-time location system (RTLS) technology to alleviate issues with OR inefficiency. Here’s how RTLS works: A radio frequency identification or wi-fi enabled sensor is placed in a badge worn by providers, staff members or patients, or affixed to a piece of equipment. Then, those sensors ping receivers throughout the hospital as people and equipment move around, which sends signals to the RTLS platform that informs users of their locations.
RTLS is certainly helpful but it is not enough. More than simply knowing the locations of staff and equipment, hospital administrators need a way of communicating with care team members about patient progress through care episodes, as well as a means of ascertaining the causes of OR inefficiency. This is where artificial intelligence (AI) and machine learning enter the picture. Augmenting RTLS, AI and machine learning combine to send automatic notifications to providers when patients move on to the next stage of care, removing the need for providers and care team members to manually communicate about these common events.
Integrated with other platforms such as electronic health records and scheduling systems, these combined technologies can then be leveraged to identify the causes of delays so workflows and patient flows can be adjusted. Additionally, these solutions should offer predictions about expected OR traffic and case lengths to give managers continuous awareness throughout the day about staffing and equipment needs.
Because surgeries create so much revenue for hospitals, administrators cannot afford to live with the inefficiency that continuously hampers their productivity. While it is certainly important to know the location of staff and equipment, this knowledge does not completely solve the inefficiency problem. Combining location data with AI and other systems enables hospitals to identify factors that contribute to delays and develop insights to boost OR productivity, helping hospitals secure their financial futures.
As the industry starts to catch up after the recent post-holiday Covid surge, there may be unforeseen adjustments to hospital operations, but there will always be ORs. The latest technologies can go a long way in helping them to save time—and money—when we start to find the way of the “new normal” in healthcare delivery.
About the Author
Neeraj founded Tagnos which orchestrates the patient journey inside the hospital using IoT and AI. He has raised over $12M for Tagnos through recognized venture capitalists, corporate investors including Honeywell, Zebra Technologies and Cisco, and prominent angel investors. He has taken Tagnos through EvoNexus and Cisco EIR(entrepreneur-in-residence) program. Neeraj is a recognized expert in wireless healthcare and workflow automation and holds few patents in the space. He has served as Sponsorship Chair on the board of the Healthcare Information and Management Systems Society (HIMSS) Southern California Chapter and served as co-Chair for EvoNexus loT group. Neeraj is also past President of TiE (The Indus Entrepreneurs) SoCal chapter where he founded a virtual incubator called TiE SoCaL Labs which gave birth to TiE SoCal Angels. Prior to founding Tagnos, he served in management consulting and IT leadership roles at Kaiser Permanente, IBM, Amgen, Blue Shield and THQ Wireless. Neeraj earned a Master’s degree in Computer Science from BITS Pilani (India) and an MBA from UCLA Anderson School of Management with an emphasis in Finance and Entrepreneurship.
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