Inside the operating room: why static checks miss the real environmental risks

Every year, hundreds of millions of surgical procedures take place in operating rooms around the world, in environments that are supposed to be among the most rigorously controlled spaces in modern medicine. Air cleanliness, temperature, humidity, surface disinfection and noise levels are all specified in exhaustive detail by national standards and hospital protocols. Yet a growing body of evidence suggests that the way we actually measure operating room environmental quality is fundamentally out of step with the way the environment behaves. A new qualitative study from China, published in Frontiers in Public Health, argues that the dominant monitoring paradigm—static hygienic indicators such as airborne bacterial colony counts and surface microbial contamination—captures the operating room at rest, but systematically misses the dynamic environmental shifts that unfold during real clinical activity. The gap, the researchers contend, may be quietly contributing to surgical site infections and occupational exposure incidents that better surveillance could help prevent.

The study, led by Yanan Li, Tong Zhang and Dongmei Bian of the Department of Surgery Operating Room at Xijing Hospital, Fourth Military Medical University in Xi’an, took an unusual approach to this problem. Rather than deploying sensors or running measurements, the team asked the people who live and work inside operating rooms what they actually think environmental quality means, and how it should be judged. Using a descriptive qualitative design, the researchers purposively recruited 20 experienced professionals from four tertiary Grade A hospitals in different geographic regions of China: seven operating room nurses, six surgeons, five anesthesiologists and two infection control specialists. After ethics approval in March 2026, each participant completed a formal semi-structured interview lasting roughly 17 minutes on average, conducted either face to face in a private, soundproofed room or by telephone according to preference and logistics.

The technical machinery behind the analysis was as important as the sample. All recordings were transcribed within 24 hours to preserve data integrity and minimize recall bias, and each transcript was returned to the corresponding participant for review, with no substantive disagreements reported. The 20 interviews generated 341 recorded minutes, 68,195 words of transcript and 452 initial codes, which were managed and coded in NVivo 15.0 using Colaizzi’s seven-step phenomenological method. The team employed a deliberately hybrid analytic orientation: significant statements and meaning units were derived inductively from the transcripts, while the Donabedian model—the classic structure-process-outcome framework for assessing medical service quality—was used to organize the resulting categories rather than to predetermine them. Two researchers independently coded each transcript and compared code sets after every four to five interviews, resolving disagreements by discussion or, when consensus proved impossible, through a third researcher acting as arbiter, with all decisions recorded in a written audit trail. Data saturation was reached after interview 18 and confirmed in two additional interviews, with no new codes or themes emerging in any professional group or Donabedian domain.

Three core themes emerged from the coding. The first was a reconceptualization of what operating room environmental quality actually comprises. Participants described a four-dimensional connotation: the physical environment, encompassing temperature, humidity, ventilation, lighting, noise and internal functional layout; the chemical environment, including the disinfectants, pharmaceuticals and anesthetic agents that saturate the surgical workspace; the biological environment, the core of nosocomial infection and occupational protection, spanning airborne microbes, electrosurgical smoke and, in tumor surgery, aerosols containing toxic gases and potentially hazardous tissue particles; and finally the humanistic environment, addressing the dual needs of medical staff and patients through preoperative reassurance, intraoperative warming, privacy protection, teamwork atmosphere and the management of work stress. This last dimension is striking because conventional environmental audits rarely touch it at all, yet participants consistently described it as inseparable from the others.

The second theme was a set of nine preliminary candidate indicators for dynamic evaluation, organized across the three Donabedian domains. Under structure quality, participants pointed to structure and layout, policies and regulations, and personnel allocation and management. Under process quality, they identified personnel safety, personnel comfort and infection control. Under outcome quality, they proposed satisfaction evaluation, the incidence of adverse events, and the qualification rate of objective environmental parameter indicators. The logic is that foundational conditions—layout, equipment, ventilation systems, protective materials, entry protocols—shape what is possible; operational monitoring—personnel traffic, surgical smoke evacuation, waste anesthetic gas scavenging, noise control, temperature and humidity management—captures what is actually happening; and outcome measures—satisfaction scores, occupational exposure events, environmental parameter compliance, and patient-related measures where valid data exist—close the feedback loop. One infection control specialist argued that purification system parameters should be treated as an outcome indicator, noting that the air exchange rate and fresh air volume must meet requirements, and that the dynamic qualification rate of intraoperative indicators is very important, with key intraoperative time nodes selected for real-time monitoring.

Why does static monitoring fall short? The evidence assembled in the study is compelling. Noise levels in the operating room are not constant; they fluctuate significantly with surgical stages and personnel activities, and research cited by the team shows that high noise levels are associated with increased communication failures and, in systematic reviews, with objectively increased risks of postoperative complications including surgical site infections. Waste anesthetic gases exhibit concentration variations throughout the surgical procedure, influenced by induction phases, equipment leaks and ventilation efficiency, and without effective scavenging systems their concentrations can exceed recommended thresholds during surgery, posing continuous occupational exposure risks. Indoor microbial loads are directly correlated with personnel movement and door opening frequencies, as simulation studies have demonstrated, meaning that static sampling fails to capture transient pollution events that occur precisely when the surgical team is most active. Real-time monitoring technologies do exist—continuous particle and microbiological air sampling, real-time waste anesthetic gas sensing, noise dosimetry, and networked sensors streaming ventilation parameters—but most capture only a single parameter, air sampling results are surrogate measures that do not map directly onto wound contamination, validated intraoperative thresholds remain scarce, and issues of calibration, cost, alarm burden and data integration restrict routine use.

The third theme concerned what healthcare professionals perceive as the safety and health implications of the current environment, for both staff and patients. Surgeons described cluttered cables along activity paths that personnel could trip over or disconnect during surgery, noise from intraoperative instruments causing distraction and delaying surgical progress, and unstable surgical lighting that was sometimes too glaring and sometimes failed to illuminate the surgical area clearly. Anesthesiologists and nurses described unstable temperatures that they perceived could increase the risk of postoperative infection, patients feeling cold due to nervousness or physical weakness, and scrub nurses suffering eye soreness from staring at the surgical field for long periods. One anesthesiologist noted that the smoke produced by electrosurgical units irritates the respiratory tract of medical staff and that ordinary surgical masks cannot provide completely effective protection. Another participant described smelling anesthetic gas while operating beside pediatric patients whose masks were not sealed tightly, and formaldehyde leaking when doctors fixed specimens. The study is careful to note that these accounts reflect professional perceptions and second-hand observations rather than measured patient-level clinical outcomes, and should not be interpreted as evidence of causal effects on infection, recovery or prognosis.

What makes the study’s implications particularly timely is the rise of intelligent operating suites. The integration of advanced medical equipment and digital workflows has significantly heightened the complexity of intraoperative environments, and the researchers suggest that digital operating suites may help bridge static assessment and intraoperative feedback by integrating time-stamped data from environmental sensors, ventilation and purification systems, anesthesia workstations, surgical smoke evacuation devices and workflow records into a shared dashboard. Such a system could display parameter trends, identify deviations from locally defined thresholds, and prompt the responsible team to review conditions at key intraoperative time points. The team is explicit that this pathway is a practical implementation hypothesis derived from the candidate framework rather than evidence of effectiveness, since the study did not evaluate any specific technology. They also acknowledge that institutionalizing dynamic indicators would require more than deploying sensors: selecting a feasible core set of indicators, defining ownership of data review and escalation, integrating records across devices, minimizing alarm burden and documentation workload, ensuring staff training and adherence, protecting data governance and privacy, and allocating resources for equipment maintenance and continuous quality review.

The researchers are equally candid about their limitations. All participants were recruited from tertiary Grade A hospitals, and the eligibility criteria favored experienced professionals with intermediate or senior titles, meaning the sample may underrepresent junior staff and perspectives from primary or lower-level hospitals, limiting transferability to other healthcare settings. Patients were not interviewed, and patient-level clinical outcomes were not measured. The Donabedian framework and the researchers’ operating room backgrounds may have influenced theme generation despite inductive coding and reflexive discussions. Most fundamentally, this qualitative study generated candidate evaluation elements only; it did not assess content validity, weighting, feasibility, reliability, thresholds or discriminative ability. The team proposes that future work should use Delphi consultation, content-validity assessment, feasibility testing, reliability evaluation, threshold development and empirical validation before any indicator system is implemented or used for performance assessment.

Even with those caveats, the study lands at a moment when the operating room is being reconceptualized as a four-dimensional, integrated perioperative ecosystem in which physical, chemical, biological and psychosocial determinants interact synergistically. Current protocols, the authors observe, exhibit a disproportionate emphasis on patient-centric infection prevention while overlooking occupational exposure risks faced by perioperative staff, and environmental mitigation strategies predominantly rely on preoperative static sanitization and postoperative terminal disinfection, largely neglecting dynamic intraoperative surveillance. The candidate framework that emerges from these 20 interviews—structural conditions, process monitoring and outcome-related feedback, integrated across occupational health and patient safety—offers a qualitative foundation for building a genuinely dynamic assessment system. Whether it survives Delphi consultation and empirical testing remains to be seen, but the message from the professionals who work inside the operating room is clear: the environment they operate in is not static, and the way we evaluate it should not be either.

Subject of Research: The cognition of dynamic evaluation of operating room environmental quality among medical staff: a qualitative study

Article Title: The cognition of dynamic evaluation of operating room environmental quality among medical staff: a qualitative study

Article References: Li, Y., Zhang, T., & Bian, D. (2026). The cognition of dynamic evaluation of operating room environmental quality among medical staff: a qualitative study. Frontiers in Public Health, 14, Article 1950404. https://doi.org/10.3389/fpubh.2026.1950404

Image Credits: AI Generated

DOI: 10.3389/fpubh.2026.1950404

Keywords: cognition, dynamic, evaluation, operating, room, environmental, quality, medical, staff, qualitative, scientific research