Variability in infection surveillance methods and impact on surgical site infection rates

How effective are monthly departmental tracer surveys? A 5-year retrospective study of 138 surveys in 96 departments

BACKGROUND

Repeat department-wide surveys are commonly employed for infection control. There remains debate concerning their cost-effectivess. The aim of the study was to measure the impact of repeat department-wide surveys in major in-patient departments (IPDs) and ambulatory facilities (AFs) in a tertiary care hospital. This was a retrospective study of 138 surveys condcuted in 96 departments over a 5-year period.

METHODS

Two itemized questionnaires were designed to assess the most frequently inadequately adhered to infection control measures: one for IPD (with 21 items) and the other for AF (with 17 items).

RESULTS

A total of 72 surveys were conducted in 49 IPDs, of which 39 (54%) were repeat surveys, and 66 surveys in 47 AFs, of which 33 (50%) were repeat surveys. The baseline rate of adherence/department was 71% ± 14 for the IPD, with an increase from the first to the last survey to 82% ± 13 (P = .037). In 15/21 measured infection control items, adherence improved. Adherence to infection control items was lower at baseline in the AFs than in the IPDs (63 ± 27), with an increase to 76 ± 20 (non significant). Although adherence improved for 9 items, it deteriorated in another 8, producing an overall statistically unchanged outcome.

CONCLUSION

Repeat whole-department surveys contribute moderately to increased adherence to infection control guidelines. AFs demonstrate lower rates of adherence to infection control guidelines and are less receptive to educational measures.

Reportable infections following colon surgery in a large public healthcare system in New York City: The consequences of being a level 1 trauma center

OBJECTIVES

To examine differences in risk factors and outcomes of patients undergoing colon surgery in level 1 trauma centers versus other hospitals and to investigate the potential financial impact of these reportable infections.

DESIGN

Retrospective cohort study between 2015 and 2022.

SETTING

Large public healthcare system in New York City.

PARTICIPANTS

All patients undergoing colon surgery; comparisons were made between (1) all patients undergoing colon surgery at the level 1 trauma centers versus patients at the other hospitals and (2) the nontrauma and trauma patients at the level 1 trauma centers versus the nontrauma patients at other hospitals.

RESULTS

Of 5,217 colon surgeries reported, 3,531 were at level 1 trauma centers and 1686 at other hospitals. Patients at level 1 trauma centers had significantly increased American Society of Anesthesiology (ASA) scores, durations of surgery, rates of delayed wound closure, and rates of class 4 wounds, resulting in higher SIRs (1.1 ± 0.15 vs 0.75 ± 0.18; P = .0007) compared to the other hospitals. Compared to the nontrauma patients at the other hospitals, both the nontrauma and trauma patients at the level 1 trauma centers had higher ASA scores, rates of delayed wound closure, and of class 4 wounds. The SIRs of the nontrauma patients (1.16 ± 1.29; P = .008) and trauma patients (1.26 ± 2.69; P = .066) at the level 1 trauma center were higher than the SIRs of nontrauma patients in the other hospitals (0.65 ± 1.18).

CONCLUSIONS

Patients undergoing colon surgery at level 1 trauma centers had increased complexity of surgery compared to the patients in other hospitals. Until there is appropriate adjustment for these risk factors, the use of infections following colon surgery as a reportable quality measure should be re-evaluated.

Using artificial intelligence to reduce orthopedic surgical site infection surveillance workload: Algorithm design, validation, and implementation in 4 Spanish hospitals

BACKGROUND

Surgical site infection (SSI) surveillance is a labor-intensive endeavor. We present the design and validation of an algorithm for SSI detection after hip replacement surgery, and a report of its successful implementation in 4 public hospitals in Madrid, Spain.

METHODS

We designed a multivariable algorithm, AI-HPRO, using natural language processing (NLP) and extreme gradient boosting to screen for SSI in patients undergoing hip replacement surgery. The development and validation cohorts included data from 19,661 health care episodes from 4 hospitals in Madrid, Spain.

RESULTS

Positive microbiological cultures, the text variable "infection", and prescription of clindamycin were strong markers of SSI. Statistical analysis of the final model indicated high sensitivity (99.18%) and specificity (91.01%) with an F1-score of 0.32, AUC of 0.989, accuracy of 91.27%, and negative predictive value of 99.98%.

DISCUSSION

Implementation of the AI-HPRO algorithm reduced the surveillance time from 975 person/hours to 63.5 person/hours and permitted an 88.95% reduction in the total volume of clinical records to be reviewed manually. The model presents a higher negative predictive value (99.98%) than algorithms relying on NLP alone (94%) or NLP and logistic regression (97%).

CONCLUSIONS

This is the first report of an algorithm combining NLP and extreme gradient-boosting to permit accurate, real-time orthopedic SSI surveillance.

Strategies to prevent surgical site infections in acute-care hospitals: 2022 Update

The intent of this document is to highlight practical recommendations in a concise format designed to assist acute-care hospitals in implementing and prioritizing their surgical-site infection (SSI) prevention efforts. This document updates the Strategies to Prevent Surgical Site Infections in Acute Care Hospitals published in 2014. This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA). It is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise.

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).

The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries

Background

Surveillance of surgical site infections (SSIs) is essential for better prevention. We developed a screening method for SSIs in adults.

Methods

The training dataset included data from patients who underwent orthopedic surgeries (N = 1,090), colorectal surgeries (N = 817), and abdominal hysterectomies (N = 523) during 2015-2018. The gold standard for the validation of the screening tool was the presence of SSI as determined by a trained infection control practitioner, via manual full medical record review, using the US Center for Disease Control and Prevention criteria. Using multivariable regression models, we identified the correlates of SSI. Patients who had at least one of these correlates were classified as likely to having SSI and those who did not have any of the correlates were classified as unlikely to have SSI. We calculated the sensitivity and specificity of this tool compared to the gold standard and applied the tool to a validation dataset (N = 1,310, years 2019-2020).

Results

SSI was diagnosed by an infection control specialist in 8.2, 5.2, and 31.2% of the patients in the training dataset who underwent hysterectomies, orthopedic surgeries and colorectal surgeries, respectively, vs. 6.2, 6.6, and 25.5%, respectively, in the validation dataset. The correlates of SSI after abdominal hysterectomy were prolonged hospitalization, ordering wound or blood culture, emergency room visit and reoperation; in orthopedic surgery, emergency room visit, wound culture, reoperation, and documentation of SSI, and in colorectal surgeries prolonged hospitalization, readmission, and ordering wound or blood cultures. Area under the curve was >90%. The sensitivity and specificity (95% CI) of the screening tool were 98% (88-100) and 58% (53-62), for abdominal hysterectomy, 91% (81-96) and 82% (80-84) in orthopedic surgeries and 96% (90-98) and 62% (58-66) in colorectal surgeries. The corresponding values for the validation dataset were 89% (67-97) and 75% (69-80) in abdominal hysterectomy; 85% (72-93) and 83% (80-86) in orthopedic surgeries and 98% (93-99) and 59% (53-64) in colorectal surgeries. The number of files needed to be fully reviewed declined by 61-66.

Conclusion

The presented semi-automated simple screening tool for SSI surveillance had good sensitivity and specificity and it has great potential of reducing workload and improving SSI surveillance.

Reliability and validity of multicentre surveillance of surgical site infections after colorectal surgery

Background

Surveillance is the cornerstone of surgical site infection prevention programs. The validity of the data collection and awareness of vulnerability to inter-rater variation is crucial for correct interpretation and use of surveillance data. The aim of this study was to investigate the reliability and validity of surgical site infection (SSI) surveillance after colorectal surgery in the Netherlands.

Methods

In this multicentre prospective observational study, seven Dutch hospitals performed SSI surveillance after colorectal surgeries performed in 2018 and/or 2019. When executing the surveillance, a local case assessment was performed to calculate the overall percentage agreement between raters within hospitals. Additionally, two case-vignette assessments were performed to estimate intra-rater and inter-rater reliability by calculating a weighted Cohen’s Kappa and Fleiss’ Kappa coefficient. To estimate the validity, answers of the two case-vignettes questionnaires were compared with the answers of an external medical panel.

Results

1111 colorectal surgeries were included in this study with an overall SSI incidence of 8.8% (n = 98). From the local case assessment it was estimated that the overall percent agreement between raters within a hospital was good (mean 95%, range 90–100%). The Cohen’s Kappa estimated for the intra-rater reliability of case-vignette review varied from 0.73 to 1.00, indicating substantial to perfect agreement. The inter-rater reliability within hospitals showed more variation, with Kappa estimates ranging between 0.61 and 0.94. In total, 87.9% of the answers given by the raters were in accordance with the medical panel.

Conclusions

This study showed that raters were consistent in their SSI-ascertainment (good reliability), but improvements can be made regarding the accuracy (moderate validity). Accuracy of surveillance may be improved by providing regular training, adapting definitions to reduce subjectivity, and by supporting surveillance through automation.

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.