Houston Methodist has piloted ambient clinical intelligence and AI tools to enhance operating room (OR) efficiency and cost savings. Given the critical role of ORs in patient care, the healthcare industry faces the challenge of balancing the high value of OR services with equally high operational costs. A 2022 study in the Journal of Orthopaedic Business estimated that each minute of OR time averages a cost of $46.04. Enhancing OR Efficiency with Ambient Sensor Technology.
To maintain OR service value, healthcare systems aim to improve service quality, reduce costs, or both. Increasing efficiency throughout the surgical process is a common approach, though identifying sources of inefficiency remains challenging. Advances in ambient intelligence, technologies that autonomously interact with humans, offer new ways to streamline electronic health record (EHR) documentation and alleviate clinician burnout. Ambient clinical intelligence, in particular, is now being tested in ORs, yielding promising results.
In an interview with HealthTech Analytics, Roberta L. Schwartz, executive vice president and chief innovation officer at Houston Methodist, and Tony DeDominico, vice president of operations, discussed how the health system uses ambient sensor technology and AI to improve OR efficiency.
Enhancing OR Efficiency with Ambient Sensor Technology
Schwartz explained that OR efficiency is a widespread issue for healthcare providers. OR minutes are some of the most expensive on a health system’s campus, creating incentives for leadership to fit more cases into the OR docket and reduce overtime. Houston Methodist explored emerging technologies, such as AI and ambient sensors, to address this challenge.
The health system partnered with Apella, a company specializing in ambient sensor technology and AI for ORs, to pilot ambient sensors that collect video data during procedures. This data, combined with historical information, allows AI to predict scheduling needs, staffing requirements, and expected surgery durations, thereby reducing reliance on human judgment and enhancing decision-making accuracy.
Schwartz likened this predictive system to planning a flight, where accurate departure information is crucial. Similarly, real-time OR data helps OR staff make informed decisions, thereby increasing efficiency.
This technology assists charge nurses, who typically oversee staffing and resource allocation. Nurses develop an understanding of surgeon preferences and case requirements over time, yet their clinical judgment can be influenced by various factors, such as job stress. The AI provides precise, data-driven predictions to support decision-making, allowing nurses to manage staffing more effectively.
Gaining Clinician Buy-In
Implementing ambient sensors in ORs can be challenging, as clinicians may feel uneasy about being recorded. Schwartz noted that emphasizing the benefits of the technology—such as improved accuracy and streamlined communication—has been essential in gaining clinician acceptance. DeDominico highlighted that the AI’s ability to send clinicians relevant updates, such as when a patient is ready for surgery, has increased clinician satisfaction by reducing unnecessary waiting.
To further build trust, Houston Methodist created a transparent process for accessing video recordings. A video review requires approval from the chief quality officer, the head of the department, and the head of the OR committee. Schwartz indicated that video reviews, used primarily for training and quality improvements, are rare.
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Measuring Success
Houston Methodist measures OR efficiency through metrics like OR block utilization. Ambient sensors allow for precise tracking of block time usage, identifying underutilized slots that can be reallocated to surgeons in need. This helps reduce unused OR blocks and optimize scheduling.
Additionally, ambient sensing can aid in infection control. In the event of a patient infection, video data can be reviewed to assess whether OR protocols may have contributed, thus improving patient safety and reducing costs associated with treating infections.
Schwartz emphasized the importance of a strong change management strategy when implementing AI and ambient sensing technologies. She noted that extensive communication and collaboration across the organization are essential for a successful rollout.
“The return on investment is very clear,” Schwartz stated. “The hardest part is the change management.”
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