Benefit of systematic selection of pairs of cases matched by surgical specialty for surveillance of bacterial transmission in operating rooms

A threshold of 100 or more colony-forming units on the anesthesia machine predicts bacterial pathogen detection: a retrospective laboratory-based analysis

PURPOSE

Preventing the spread of pathogens in the anesthesia work area reduces surgical site infections. Improved cleaning reduces the percentage of anesthesia machine samples with ≥ 100 colony-forming units (CFU) per surface area sampled. Targeting a threshold of < 100 CFU when cleaning anesthesia machines may be associated with a lower prevalence of bacterial pathogens. We hypothesized that anesthesia work area reservoir samples returning < 100 CFU would have a low (< 5%) prevalence of pathogens.

METHODS

In this retrospective cohort study of bacterial count data from nine hospitals, obtained between 2017 and 2022, anesthesia attending and assistants' hands, patient skin sites (nares, axilla, and groin), and anesthesia machine (adjustable pressure-limiting valve and agent dials) reservoirs were sampled at case start and at case end. The patient intravenous stopcock set was sampled at case end. The isolation of ≥ 1 CFU of Staphylococcus aureus, methicillin-resistant Staphylococcus aureus, Enterococcus, vancomycin-resistant Enterococcus, gram-negative (i.e., Klebsiella, Acinetobacter, Pseudomonas, and Enterobacter spp.) or coagulase-negative Staphylococcus was compared for reservoir samples returning ≥ 100 CFU vs those returning < 100 CFU.

RESULTS

Bacterial pathogens were isolated from 24% (7,601/31,783) of reservoir samples, 93% (98/105) of operating rooms, and 83% (2,170/2,616) of cases. The ratio of total pathogen isolates to total CFU was < 0.0003%. Anesthesia machine reservoirs returned ≥ 100 CFU for 44% (2,262/5,150) of cases. Twenty-three percent of samples returning ≥ 100 CFU were positive for ≥ 1 bacterial pathogen (521/2,262; 99% lower confidence limit, 22%) vs 3% of samples returning < 100 CFU (96/2,888; 99% upper limit, 4%).

CONCLUSIONS

Anesthesia machine reservoir samples returning < 100 CFU were associated with negligible pathogen detection. This threshold can be used for assessment of terminal, routine, and between-case cleaning of the anesthesia machine and equipment. Such feedback may be useful because the 44% prevalence of ≥ 100 CFU was comparable to the 46% (25/54) reported earlier from an unrelated hospital.

Estimation of the contribution to intraoperative pathogen transmission from bacterial contamination of patient nose, patient groin and axilla, anesthesia practitioners' hands, anesthesia machine, and intravenous lumen

BACKGROUND

Earlier studies showed net cost saving from anesthesia practitioners' use of a bundle of infection prevention products, with feedback on monitored Staphylococcus aureus intraoperative transmission. ESKAPE pathogens also include Enterococcus and gram-negative pathogens: Klebsiella, Acinetobacter, Pseudomonas, and Enterobacter. We evaluated whether bacterial contamination of patient nose, patient groin and axilla, anesthesia practitioners' hands, anesthesia machine, and intravenous lumen all contribute meaningfully to ESKAPE pathogen transmission within anesthesia work areas.

METHODS

The retrospective cohort study used bacterial count data from nine hospitals, 43 months, and 448 ESKAPE pathogen transmission events within anesthesia areas of 86 operating rooms. Transmission was measured within and between pairs of successive surgical cases performed in the same operating room on the same day.

RESULTS

There were 203 transmission events with S. aureus, 72 with Enterococcus, and 173 with gram negatives. ESKAPE pathogens in the nose contributed to transmission for 50% (99% confidence limit ≥45%) of case pairs, on the groin or axilla for 54% (≥49%), on the hands for 53% (≥47%), on the anesthesia machine for 21% (≥17%), and in the intravenous lumen for 24% (≥20%). ESKAPE pathogens in the nose started a transmission pathway for 27% (≥22%) of case pairs, on the groin or axilla for 24% (≥19%), on the hands for 38% (≥33%), on the anesthesia machine for 11% (≥7.6%), and in the intravenous lumen for 8.0% (≥5.3%). All P ≤ 0.0022 compared with 5%.

CONCLUSIONS

To prevent intraoperative ESKAPE pathogen transmission, anesthesia practitioners would need to address all five categories of infection control approaches: nasal antisepsis (e.g., povidone-iodine applied the morning of surgery), skin antisepsis (e.g., chlorhexidine wipes), hand antisepsis with dispensers next to the patient, decontamination of the anesthesia machine before and during anesthetics, and disinfecting caps for needleless connectors, disinfecting port protectors, and disinfecting caps for open female Luer type connectors.

The efficacy of multifaceted versus single anesthesia work area infection control measures and the importance of surgical site infection follow-up duration

BACKGROUND

Earlier a randomized trial showed efficacy of a multifaceted intervention approach for reducing surgical site infection: hand hygiene, vascular care, environmental cleaning, patient decolonization (nasal povidone iodine, chlorhexidine wipes), with feedback on pathogen transmission. The follow-up prospective observational study showed effectiveness when applied to all operating rooms of an inpatient surgical suite. In practice, many organizations will at baseline not be using conditions equivalent to the control groups but instead functionally have had ongoing a single intervention for infection control (e.g., encouraging better hand hygiene). Organizations also differ in how well and long they survey every surgical patient for postoperative surgical site infection. Thus, estimation of the expected net cost savings from implementing multifaceted intervention depends on the relative efficacy of multifaceted approach versus single intervention approaches and on the incidence of surgical site infection, the latter depending itself on the monitoring period for infection development.

METHODS

The retrospective cohort analysis included 4865 patients from two single intervention and two multifaceted studies, each of the four studies with matched control groups. We used Poisson regression with robust variance to estimate the relative risk reduction in surgical site infections for the multifaceted approach versus single interventions and, with 30-day follow-up versus ≥60-day follow-up for infection.

RESULTS

The multifaceted approach was associated with an estimated 68% reduction in postoperative surgical site infections relative to single interventions (risk ratio 0.32, 97.5% confidence interval 0.15-0.70, P = 0.001). There were approximately 2.61-fold more surgical site infections detected with follow-up for at least 60 days of medical records relative to 30 days of records reviewed (97.5% CI 1.62 to 4.21, P < 0.001).

CONCLUSIONS

An evidence-based, multifaceted approach to anesthesia work area infection control can generate substantial reductions in surgical site infections. A follow-up period of at least 60-days is indicated for infection detection.

Quantifying and Interpreting Inequality in Surgical Site Infections per Quarter Among Anesthetizing Locations and Specialties

Background Earlier studies have shown that prevention of surgical site infection can achieve net cost savings when targeted to operating rooms with the most surgical site infections. Methodology This retrospective cohort study included all 231,057 anesthetics between May 2017 and June 2022 at a large teaching hospital. The anesthetics were administered in operating rooms, procedure rooms, radiology, and other sites. The 8,941 postoperative infections were identified from International Classification of Diseases diagnosis codes relevant to surgical site infections documented during all follow-up encounters over 90 days postoperatively. To quantify the inequality in the counts of infections among anesthetizing locations, the Gini index was used, with the Gini index being proportional to the sum of the absolute pairwise differences among anesthetizing locations in the counts of infections. Results The Gini index for infections among the 112 anesthetizing locations at the hospital was 0.64 (99% confidence interval = 0.56 to 0.71). The value of 0.64 is so large that, for comparison, it exceeds nearly all countries' Gini index for income inequality. The 50% of locations with the fewest infections accounted for 5% of infections. The 10% of locations with the most infections accounted for 40% of infections and 15% of anesthetics. Among the 57 operating room locations, there was no association between counts of cases and infections (Spearman correlation coefficient r = 0.01). Among the non-operating room locations (e.g., interventional radiology), there was a significant association (Spearman r = 0.79). Conclusions Targeting specific anesthetizing locations is important for the multiple interventions to reduce surgical site infections that represent fixed costs irrespective of the number of patients (e.g., specialized ventilatory systems and nightly ultraviolet-C disinfection).

Quantifying and interpreting inequality of surgical site infections among operating rooms

PURPOSE

The incidence of surgical site infection differs among operating rooms (ORs). However, cost effectiveness of interventions targeting ORs depends on infection counts. The purpose of this study was to quantify the inequality of infection counts among ORs.

METHODS

We performed a single-centre historical cohort study of elective surgical cases spanning a 160-week period from May 2017 to May 2020, identifying cases of infection within 90 days using International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes. We used the Gini index to measure inequality of infections among ORs. As a reference, the Gini index for inequality of household disposable income in the US in 2017 was 0.39, and 0.31 for Canada.

RESULTS

There were 3,148 (3.67%) infections among the 85,744 cases studied. The 20% of 57 ORs with the most and least infections accounted for 44% (99% confidence interval [CI], 36 to 52) and 5% (99% CI, 2 to 8), respectively. The Gini index was 0.40 (99% CI, 0.31 to 0.50), which is comparable to income inequality in the US. There were more infections in ORs with more minutes of cases (Spearman correlation ρ = 0.68; P < 0.001), but generally not in ORs with more total cases (ρ = 0.11; P = 0.43). Moderately long (3.3 to 4.8 hr) cases had a large effect, having greater incidences of infection, while not being so long as to have just one case per day per OR. There was substantially greater inequality in infection counts among the 557 observed combinations of OR specialty (Gini index 0.85; 99% CI, 0.81 to 0.88).

CONCLUSIONS

Inequality of infections among ORs is substantial and caused by both inequality in the incidence of infections and inequality in the total minutes of cases. Inequality in infections among OR and specialty combinations is due principally to inequality in total minutes of cases.

Sample times for surveillance of S. aureus transmission to monitor effectiveness and provide feedback on intraoperative infection control

Background

Reductions in perioperative surgical site infections are obtained by a multifaceted approach including patient decolonization, vascular care, hand hygiene, and environmental cleaning. Associated surveillance of S. aureus transmission quantifies the effectiveness of these basic measures to prevent transmission of pathogenic bacteria and viruses to patients and clinicians, including Coronavirus Disease 2019 (COVID-19). To measure transmission, the observational units are pairs of successive surgical cases in the same operating room on the same day. In this prospective cohort study, we measured sampling times for inexperienced and experienced personnel.

Methods

OR PathTrac kits included 6 samples collected before the start of surgery and 7 after surgery. The time for consent also was recorded. We obtained 1677 measurements of time among 132 cases.

Results

Sampling times were not significantly affected by technician's experience, type of anesthetic, or patient's American Society of Anesthesiologists’ Physical Status. Sampling times before the start of surgery averaged less than 5 min (3.39 min [SE 0.23], P < 0.0001). Sampling times after surgery took approximately 5 min (4.39 [SE 0.25], P = 0.015). Total sampling times averaged less than 10 min without consent (7.79 [SE 0.50], P < 0.0001), and approximately 10 min with consent (10.22 [0.56], P = 0.70).

Conclusions

For routine use of monitoring S. aureus transmission, when done by personnel already present in the operating rooms of the cases, the personnel time budget can be 10 min per case.

Strategies for daily operating room management of ambulatory surgery centers following resolution of the acute phase of the COVID-19 pandemic

We performed a narrative review to explore the economics of daily operating room management decisions for ambulatory surgery centers following resolution of the acute phase of the Coronavirus Disease 2019 (COVID-19) pandemic. It is anticipated that there will be a substantive fraction of patients who will be contagious, but asymptomatic at the time of surgery. Use multimodal perioperative infection control practices (e.g., including patient decontamination) and monitor performance (e.g., S. aureus transmission from patient to the environment). The consequence of COVID-19 is that such processes are more important than ever to follow because infection affects not only patients but the surgery center staff and surgeons. Dedicate most operating rooms to procedures that are not airway aerosol producing and can be performed without general anesthesia. Increase throughput by performing nerve blocks before patients enter the operating rooms. Bypass the phase I post-anesthesia care unit whenever possible by appropriate choices of anesthetic approach and drugs. Plan long-duration workdays (e.g., 12-h). For cases where the surgical procedure does not cause aerosol production, but general anesthesia will be used, have initial (phase I) post-anesthesia recovery in the operating room where the surgery was done. Use anesthetic practices that achieve fast initial recovery of the brief ambulatory cases. When the surgical procedure causes aerosol production (e.g., bronchoscopy), conduct phase I recovery in the operating room and use multimodal environmental decontamination after each case. Use statistical methods to plan for the resulting long turnover times. Whenever possible, have the anesthesia and nursing teams stagger cases in more than one room so that they are doing one surgical case while the other room is being cleaned. In conclusion, this review shows that while COVID-19 is prevalent, it will markedly affect daily ambulatory workflow for patients undergoing general anesthesia, with potentially substantial economic impact for some surgical specialties.

Perioperative Infection Transmission: the Role of the Anesthesia Provider in Infection Control and Healthcare-Associated Infections

PURPOSE OF REVIEW

This review aims to highlight key factors in the perioperative environment that contribute to transmission of infectious pathogens, leading to healthcare-associated infection. This knowledge will provide anesthesia providers the tools to optimize preventive measures, with the goal of improved patient and provider safety.

RECENT FINDINGS

Over the past decade, much has been learned about the epidemiology of perioperative pathogen transmission. Patients, providers, and the environment serve as reservoirs of origin that contribute to infection development. Ongoing surveillance of pathogen transmission among these reservoirs is essential to ensure effective perioperative infection prevention.

SUMMARY

Recent work has proven the efficacy of a strategic approach for perioperative optimization of hand hygiene, environmental cleaning, patient decolonization, and intravascular catheter design and handling improvement protocols. This work, proven to generate substantial reductions in surgical site infections, can also be applied to aide prevention of SARS-CoV-2 spread in the COVID-19 era.

Sample sizes for surveillance of S. aureus transmission to monitor effectiveness and provide feedback on intraoperative infection control including for COVID-19

Reductions in perioperative surgical site infections are obtained by a multifaceted approach including patient decolonization, hand hygiene, and hub disinfection, and environmental cleaning. Associated surveillance of S. aureus transmission quantifies the effectiveness of the basic measures to prevent the transmission to patients and clinicians of pathogenic bacteria and viruses, including Coronavirus Disease 2019 (COVID-19). To measure transmission, the observational units are pairs of successive surgical cases in the same operating room on the same day. We evaluated appropriate sample sizes and strategies for measuring transmission.

There was absence of serial correlation among observed counts of transmitted isolates within each of several periods (all P ≥.18). Similarly, observing transmission within or between cases of a pair did not increase the probability that the next sampled pair of cases also had observed transmission (all P ≥.23).

Most pairs of cases had no detected transmitted isolates. Also, although transmission (yes/no) was associated with surgical site infection (P =.004), among cases with transmission, there was no detected dose response between counts of transmitted isolates and probability of infection (P =.25).

The first of a fixed series of tests is to use the binomial test to compare the proportion of pairs of cases with S. aureus transmission to an acceptable threshold. An appropriate sample size for this screening is N =25 pairs. If significant, more samples are obtained while additional measures are implemented to reduce transmission and infections. Subsequent sampling is done to evaluate effectiveness. The two independent binomial proportions are compared using Boschloo's exact test. The total sample size for the 1^st and 2^nd stage is N =100 pairs.

Because S. aureus transmission is invisible without testing, when choosing what population(s) to screen for surveillance, another endpoint needs to be used (e.g., infections). Only 10/298 combinations of specialty and operating room were relatively common (≥1.0% of cases) and had expected incidence ≥0.20 infections per 8 hours of sampled cases. The 10 combinations encompassed ≅17% of cases, showing the value of targeting surveillance of transmission to a few combinations of specialties and rooms.

In conclusion, we created a sampling protocol and appropriate sample sizes for using S. aureus transmission within and between pairs of successive cases in the same operating room, the purpose being to monitor the quality of prevention of intraoperative spread of pathogenic bacteria and viruses.

Futility of Cluster Designs at Individual Hospitals to Study Surgical Site Infections and Interventions Involving the Installation of Capital Equipment in Operating Rooms

Anesthesia workspaces are integral components in the chains of many intraoperative bacterial transmission events resulting in surgical site infections (SSI). Matched cohort designs can be used to compare SSI rates among operating rooms (ORs) with or without capital equipment purchases (e.g., new anesthesia machines). Patients receiving care in intervention ORs (i.e., with installed capital equipment) are matched with similar patients receiving care in ORs lacking the intervention. We evaluate statistical power of an alternative design for clinical trials in which, instead, SSI incidences are compared directly among ORs (i.e., the ORs form the clusters) at single hospitals (e.g., the 5 ORs with bactericidal lights vs. the 5 other ORs). Data used for parameter estimates were SSI for 24 categories of procedures among 338 hospitals in the State of California, 2015. Estimated statistical power was ≅8.4% for detecting a reduction in the incidence of SSI from 3.6% to 2.4% over 1 year with 5 intervention ORs and 5 control ORs. For ≅80% statistical power, >20 such hospitals would be needed to complete a study in 1 year. Matched paired cluster designs pair similar ORs (e.g., 2 cardiac ORs, 1 to intervention and 1 to control). With 5 pairs, statistical power would be even less than the estimated 8.4%. Cluster designs (i.e., analyses by OR) are not suitable for comparing SSI among ORs at single hospitals. Even though matched cohort designs are non-randomized and thus have lesser validity, matching patients by their risk factors for SSI is more practical.