Addressing Sterile Processing Instrument Errors With Advanced Technology and Data Insights

Sterile Processing Perspectives with Marjorie M. Wall, EDBA, MLOS, CRCST, CIS, CHL, CSSBB.

Surgical instrument errors, a persistent and urgent challenge in sterile processing departments, have significant implications for patient safety and operating room (OR) efficiency. Despite ongoing efforts to mitigate these errors, the complexity and variability of sterile processing tasks make addressing them a complex problem. This article reviews 3 key studies on surgical instrument errors. It integrates insights from an interview with Peter Nichol, MD, PhD, a leading expert in pediatric surgery and health care informatics, to explore potential solutions.

Nichol compares the complexity of sterile processing to the manufacturing of airplanes, emphasizing that if a problem arose in airplane production, the entire process would be halted until the issue was resolved.¹ Given its intricate and critical nature, he suggests that the same level of attention and detail should be applied to sterile processing, where many interconnected elements must be fully understood and managed.¹

 Nichol and his research team initiated a multiyear research initiative in which they risk-modeled sterile processing errors, quantified hospital system-reported errors, and finally put boots to the ground to measure sterile processing errors directly in the real world.

Risk Modeling of Errors in the Surgical Instrument Cycle

The first study, "Risk Modeling of Errors in the Surgical Instrument Cycle: Insights into Solutions for an Expensive and Persistent Problem," offers a groundbreaking analysis of the complex series of tasks involved in sterile processing and the potential for errors at each stage.² By mapping out the entire Surgical Instrument Cycle, the study identified 104 discrete tasks that a simple surgical instrument undergoes from when it leaves the surgeon's hand in the operating room until it is returned for subsequent use.²

One of the study's surprising findings is the high cumulative Risk of Error Score (RES) of 4.8057 per instrument, with a significant 91% of this risk associated with tasks performed in the sterile processing environment.² The study highlighted that 62% of these tasks are executed in environments with high-stress scores, particularly within the sterile processing departments, both pre- and postwasher.² These high-stress environments exacerbate the risk of errors, particularly in tasks involving visualization, identification, and inspection of surgical instruments.²

These visualization-related challenges must be addressed; however, errors in visualization tasks are particularly problematic because they often go undetected until the instrument is used during surgery. This increases the risk to patient safety and leads to significant operational inefficiencies.¹ Nichol pointed out that the complexity of the tasks and the stress under which sterile processing staff operate make it difficult to maintain high accuracy in these critical inspection tasks consistently.¹

The study's error modeling approach revealed that six of the eight tasks with the highest risk for error are performed in sterile processing and involve direct human interaction with instruments.² These tasks are classified as "complicated non-routine," with an error rate ranging from 0.1 to 0.25, depending on the stress level of the environment.² The study suggests that reducing the stress levels in these environments and simplifying these tasks could significantly lower the overall risk of errors.2 For instance, interventions that minimize environmental stressors, optimize workflow, and ensure a fully trained workforce could reduce the RES by up to 75%.

 Nichol also discussed the potential for advanced technologies to mitigate these risks. Technological interventions, such as AI-assisted visualization tools, could transform how these high-risk tasks are performed. He explained that reducing reliance on human inspection can lower the risk of errors and improve the reliability of sterile processing.¹ He further emphasized that while automation and AI can play a crucial role, it is equally important to address the underlying stressors in the work environment to achieve sustainable improvements.¹

Patterns in Staff-Reported Surgical Instrument Errors and Visualization Failures

The study "Patterns in Staff-Reported Surgical Instrument Errors Point to Failures in Visualization as a Critically Weak Point in Sterile Processing" examines how visualization failures contribute to surgical instrument errors.³ In this study, the research team analyzed a large hospital system’s quality safety events to understand patterns in sterile processing reported errors. According to the study, 83% of the reported errors were related to failures in visualization, specifically in tasks like inspection, identification, and assembly of surgical instruments.³ These errors, which include missed detection of bioburden, incomplete instrument assembly, and missing instruments, are primarily due to the inherent limitations of human visual capabilities, particularly under the stress and high throughput demands of the sterile processing environment.³

One of the study's most compelling aspects is its exploration of how these errors are reported. The study found that the current reporting mechanisms are cumbersome, labor-intensive, and often incomplete.³ Only 20.4% of Patient Safety Notices (PSNs) incident reporting forms used in health care to document and analyze adverse events were fully completed, and 15% were submitted days after the event.³ This delay in reporting suggests that the manual nature of data entry into non-integrated systems, such as PSNs, poses a barrier to capturing accurate and timely data on surgical instrument errors.³

 Peter Nichol, who coauthored the study, elaborated on this issue during our interview. He emphasized that "the manual entry of data into these systems is not only burdensome but also highly prone to errors and omissions." He further explained that the lack of integration with electronic medical records (EMR) exacerbates this problem, requiring staff to re-enter information that could otherwise be automatically populated.¹

The study also delves into the types of errors most frequently reported. Bioburden or contamination errors, such as debris, blood, tissue, and hair left on instruments, were among the most common, accounting for nearly 69% of the mistakes.³ This indicates a need for improved inspection protocols and technologies to assist sterile processing staff in detecting these issues more effectively.

 Nichol stressed the importance of technological interventions to address these challenges.¹ He mentioned that AI and advanced imaging technologies can potentially reduce the incidence of visualization-related errors by providing real-time feedback and enhancing the accuracy of inspections.¹ This aligns with the study's conclusion that implementing such technologies could reduce the rates of surgical instrument errors and improve overall patient safety and OR efficiency.

Observed Rates of Surgical Instrument Errors

The study "Observed Rates of Surgical Instrument Errors Point to Visualization Tasks as Being a Critically Vulnerable Point in Sterile Processing and a Significant Cause of Lost Chargeable OR Minutes" provides an in-depth analysis of the frequency, types, and impact of errors related to surgical instruments, revealing a troubling picture of how common these issues are within the sterile processing environment.⁴ In this study, 20 volunteers tracked any errors identified related to sterile processing in real time in the operating room.⁴

According to the study, 26.16% of the observed surgical cases experienced at least one instrument error, with some involving multiple errors.⁴ The study identified three primary types of errors: missing instruments, broken or poorly functioning instruments, and issues with tray assembly. Most of these errors were related to failures in visualization tasks such as inspection, identification, and functionality checks.⁴

One of the study's most significant findings is that 88.6% of all observed errors were related to visualization tasks.⁴ This points to a critical vulnerability in the sterile processing of surgical instruments. The study notes, "Errors arising from failures in visualization (ie, inspection, identification, function) accounted for the majority of errors." This highlights the importance of improving the training and technology used in these tasks to reduce the occurrence of such errors.

The financial implications of these errors are substantial and demand cost-effective solutions. The study estimated the annual cost of delays due to surgical instrument errors to be between $6.75 million and $9.42 million in lost chargeable OR minutes.⁴ These delays, often caused by the need to locate or replace missing or malfunctioning instruments, result in operational inefficiencies and financial loss for health care institutions.⁴

In our interview, Peter Nichol emphasized the potential of advanced technologies to address these visualization-related errors. He shared that most surgical instrument errors stem from human limitations in performing complex visualization tasks under stressful conditions.¹ This is where the integration of advanced technologies like AI and machine learning can significantly impact by reducing the reliance on human visual inspection.¹ He further explained that adopting AI and other technologies could help mitigate these issues by providing real-time feedback and reducing the cognitive load on sterile processing staff, offering a hopeful path toward improved patient safety.¹

Overall, this study's findings underscore the need for significant improvements in the sterile processing workflow, particularly in visualization tasks. Nichol suggested that a comprehensive overhaul of the sterile processing system, including integrating AI technologies and enhanced training protocols, could help reduce the incidence of these errors and improve overall patient safety and OR efficiency.¹

Integrating Insights from Peter Nichol

 Peter Nichol's extensive experience in pediatric surgery and health care informatics provides a unique perspective on the challenges and opportunities within sterile processing. During our interview, Nichol emphasized the role of data and technology in transforming sterile processing practices to improve patient safety and operational efficiency.¹

Challenges in Visualization and Data Utilization

 Nichol noted that one of the primary challenges in sterile processing is the reliance on human visual inspection, which is inherently prone to errors.¹ "The majority of surgical instrument errors stem from the human limitation in performing complex visualization tasks under stressful conditions," he explained.¹ These errors, often subtle and difficult to detect, can lead to significant disruptions in surgical procedures and increase the risk of adverse patient outcomes.¹ Nichol argued that while training can help mitigate these issues, it cannot eliminate them due to the inherent variability in human performance.¹

 Nichol advocated integrating advanced technologies, such as AI and machine learning, to address these challenges in sterile processing workflows.¹ "AI and advanced imaging technologies have the potential to significantly reduce the incidence of visualization-related errors by providing real-time feedback and enhancing the accuracy of inspections," he stated.¹ He highlighted that these technologies could be particularly effective in standardizing inspection processes, thereby reducing the cognitive load on sterile processing staff and improving overall reliability.¹

The Future Role of AI in Sterile Processing

 Nichol also discussed the broader implications of adopting AI in health care, particularly in sterile processing.¹ He envisions a future where AI assists in visualization tasks and plays a role in predictive analytics, helping to anticipate and prevent errors before they occur. "We are moving towards a future where AI will not just be a tool for inspection, but a comprehensive system that integrates with electronic medical records (EMR) to provide predictive insights and ensure that surgical instruments are always in optimal condition," he said.¹

One key area where AI can significantly impact is the standardization and optimization of surgical instrument sets. Nichol pointed out that "AI could analyze historical data on instrument usage, outcomes, and surgeon preferences to create optimized instrument sets tailored to specific procedures and even individual surgeons." This level of customization would reduce the risk of errors and improve the efficiency of surgical procedures by ensuring that the correct instruments are always available and ready for use.¹

Cultural and Organizational Shifts Required

While the potential benefits of AI and advanced technologies are apparent, Nichol emphasized that their successful implementation requires significant cultural and organizational shifts within health care institutions.¹ "The adoption of these technologies will require a cultural shift within sterile processing departments and the broader hospital environment," he explained.¹ This shift involves embracing new technologies and rethinking how sterile processing professionals are trained and their roles are defined.¹

 Nichol also highlighted the need for health care institutions to invest in infrastructure and training to support the integration of AI and advanced technologies.¹ "To fully realize the benefits of AI in sterile processing, hospitals need to invest in the necessary infrastructure, including high-resolution imaging systems, data integration platforms, and comprehensive training programs for staff," he noted.¹ He stressed that without these foundational elements, the full potential of AI in improving patient safety and operational efficiency cannot be achieved.¹

Where to Go from Here: A Call to Action

As the health care industry continues to evolve, there is a clear need for more collaborative research and innovation in sterile processing. Nichol emphasized the importance of collaboration between sterile processing professionals, surgeons, and health care informatics experts to drive meaningful change.1 The future of sterile processing will be shaped by those who are willing to collaborate across disciplines and leverage the power of data and technology to improve outcomes.¹

 Nichol's call to action is clear: the sterile processing community must embrace AI and advanced technologies to address the persistent challenges in surgical instrument management. He encouraged sterile processing professionals to be pioneers or trailblazers by participating in research, adopting new technologies, and advocating for the necessary cultural and organizational changes within their institutions.

Integrating AI and advanced imaging technologies into sterile processing is not just an option—it is an imperative for the future of health care. As Nichol explained, we have a tremendous opportunity to set the table for a future where sterile processing is not just a back-office function but a critical component of surgical success and patient safety.¹ The time to act is now, and the path forward requires collaboration, innovation, and a commitment to excellence in sterile processing.

References

1. Nichol P. Interview by M. M. Wall. August 9, 2024.
2. Nichol PF, Saari MJ. Patterns in staff reported surgical instrument errors point to failures in visualization as a critically weak point in sterile processing of surgical instruments. Perioper Care Oper Room Manag. 2023;33.
3. Nichol PF, Saari MJ. Risk modeling of errors in the surgical instrument cycle, insights into solutions for an expensive and persistent problem. Perioper Care Oper Room Manag. 2023;32.
4. Nichol PF, Saari MJ, Navas N, et al. Observed rates of surgical instrument errors point to visualization tasks as being a critically vulnerable point in sterile processing and a significant cause of lost chargeable OR minutes. BMC Surg. 2024;24(1).