Hospital infection control and behaviour of operating room staff

Risk factors and prediction model for inpatient surgical site infection after elective abdominal surgery

BACKGROUND

Surgical site infections (SSIs) are the commonest healthcare-associated infection. In addition to increasing mortality, it also lengthens the hospital stay and raises healthcare expenses. SSIs are challenging to predict, with most models having poor predictability. Therefore, we developed a prediction model for SSI after elective abdominal surgery by identifying risk factors.

AIM

To analyse the data on inpatients undergoing elective abdominal surgery to identify risk factors and develop predictive models that will help clinicians assess patients preoperatively.

METHODS

We retrospectively analysed the inpatient records of Shaanxi Provincial People’s Hospital from January 1, 2018 to January 1, 2021. We included the demographic data of the patients and their haematological test results in our analysis. The attending physicians provided the Nutritional Risk Screening 2002 (NRS 2002) scores. The surgeons and anaesthesiologists manually calculated the National Nosocomial Infections Surveillance (NNIS) scores. Inpatient SSI risk factors were evaluated using univariate analysis and multivariate logistic regression. Nomograms were used in the predictive models. The receiver operating characteristic and area under the curve values were used to measure the specificity and accuracy of the model.

RESULTS

A total of 3018 patients met the inclusion criteria. The surgical sites included the uterus (42.2%), the liver (27.6%), the gastrointestinal tract (19.1%), the appendix (5.9%), the kidney (3.7%), and the groin area (1.4%). SSI occurred in 5% of the patients (n = 150). The risk factors associated with SSI were as follows: Age; gender; marital status; place of residence; history of diabetes; surgical season; surgical site; NRS 2002 score; preoperative white blood cell, procalcitonin (PCT), albumin, and low-density lipoprotein cholesterol (LDL) levels; preoperative antibiotic use; anaesthesia method; incision grade; NNIS score; intraoperative blood loss; intraoperative drainage tube placement; surgical operation items. Multivariate logistic regression revealed the following independent risk factors: A history of diabetes [odds ratio (OR) = 5.698, 95% confidence interval (CI): 3.305-9.825, P = 0.001], antibiotic use (OR = 14.977, 95%CI: 2.865-78.299, P = 0.001), an NRS 2002 score of ≥ 3 (OR = 2.426, 95%CI: 1.199-4.909, P = 0.014), general anaesthesia (OR = 3.334, 95%CI: 1.134-9.806, P = 0.029), an NNIS score of ≥ 2 (OR = 2.362, 95%CI: 1.019-5.476, P = 0.045), PCT ≥ 0.05 μg/L (OR = 1.687, 95%CI: 1.056-2.695, P = 0.029), LDL < 3.37 mmol/L (OR = 1.719, 95%CI: 1.039-2.842, P = 0.035), intraoperative blood loss ≥ 200 mL (OR = 29.026, 95%CI: 13.751-61.266, P < 0.001), surgical season (P < 0.05), surgical site (P < 0.05), and incision grade I or III (P < 0.05). The overall area under the receiver operating characteristic curve of the predictive model was 0.926, which is significantly higher than the NNIS score (0.662).

CONCLUSION

The patient’s condition and haematological test indicators form the bases of our prediction model. It is a novel, efficient, and highly accurate predictive model for preventing postoperative SSI, thereby improving the prognosis in patients undergoing abdominal surgery.

Analysis of the Application Effect of PDCA Cycle Management Combined With Risk Factor Management Nursing for Reducing Infection Rate in Operating Room

Purpose

To explore the application effect of plan-do-check-action (PDCA) cycle management combined with risk factor management nursing in an operating room.

Methods

A total of 150 surgical patients in our hospital from November 2020 to February 2021 were selected as the conventional group, and 150 surgical patients in our hospital from March 2021 to June 2021 were selected as the research group. The conventional group implemented routine infection management, and the research group implemented PDCA cycle management combined with risk factor management. Detection of pathogenic bacteria, incidence of incision infection, infection control, occurrence of irregular events, and nursing quality in the operating room were observed in the two groups.

Results

The detection rate of Gram-negative bacillus and Gram-positive cocci, infection rate of incision, and total incidence of irregular events in the research group were lower than those in the conventional group (P < 0.05). The qualified rate of disinfection of object surface, hands of medical staff and air, and nursing quality scores in the research group were higher than those in the conventional group (P < 0.05).

Conclusion

Plan-do-check-action (PDCA) cycle management combined with risk factor management nursing can reduce the detection rate of pathogenic bacteria and infection rate of incision in the operating room, reduce the incidence of irregular events, improve the qualified rate of disinfection, and greatly improve the quality of nursing, which can be considered to be widely used in clinical practice.

Microbial Air Monitoring in Turbulent Airflow Operating Theatres: Is It Possible to Calculate and Hypothesize New Benchmarks for Microbial Air Load?

Multiple studies have demonstrated the presence of microorganisms commonly associated with surgical site infections (SSIs), in the air within the operating theatre (OT). In some countries such Italy, the limit of microbial concentration in the air for OT with turbulent airflows is 35 CFU/m³ for an empty OT and 180 CFU/m³ during activity. This study aims to hypothesize new benchmarks for the airborne microbial load in turbulent airflow operating theatres in operational and at rest conditions using the percentile distribution of data through a 17-year environmental monitoring campaign in various Italian hospitals that implemented a continuous quality improvement policy. The quartile distribution analysis has shown how in operational and at rest conditions, 75% of the values were below 110 CFU/m³ and 18 CFU/m³, respectively, which can be considered a new benchmark for the monitored OTs. During the initial stages of the monitoring campaign, 28.14% of the concentration values in operational conditions and 29.29% of the values in at rest conditions did not conform to the Italian guidelines’ reference values. In contrast, during the last 5 years, all values in both conditions conformed to the reference values and 98.94% of these values were below the new benchmarks. Continuous improvement has allowed contamination to be reduced to levels well below the current reference values.

The Use of a Three-in-One Practice-Management-Innovation Training Model in the Construction of an Infection Control Team

Objective

This study aims to explore the role of a three-in-one practice, management, and innovation training model (also called as three-in-one practice-management-innovation training model) in the construction of an infection control team.

Methods

This study retrospectively analyzed the position structure, mastery of professional knowledge, and working methods of the full-time and part-time personnel of the Changzhou Cancer Hospital, compared the training content of Jiangsu Hospital Infection Control Center with the actual situation of the hospital, and formulated and implemented a three-in-one practice-management-innovation training model. First, the team members were selected for the construction and management of the Hospital Infection Management Department according to the relevant responsibility and management requirements, and their learning and mastery of the basic knowledge and skills concerning infection control were completed based on their professional roles. In line with the regulations of the hospital and department, full-time personnel were ensured of having the opportunity to participate in provincial- and municipal-level academic exchanges and then learn from each other, through collaboration between doctors and nurses, how to exercise basic management skills. At the same time, a fair competitive incentive mechanism was established through the three-level network of the hospital infection committee, the hospital infection management department, and nosocomial infection management department to implement innovative project-based management and cultivate an awareness of hospital infection control in all employees.

Results

The professional structure of the full-time infection control personnel has been optimized, the awareness of the infection control team concerning active participation in practice has gradually increased, and infection control management and innovation has been significantly improved.

Conclusion

After the selection of an infection control management team and the delivery of well-planned training, the quality of infection control management has improved.

Evaluation of hand hygiene: Is university medical education effective in prevention of hospital-acquired infections?

OBJECTIVE

Hand hygiene (HH) compliance is associated with effective prevention of health care-associated infections (HAI), the topic being very important due to current COVID-19 pandemic. There is a growing debate about the role of educational institutions in the low HH compliance of health workers. This study aimed to assess HH knowledge, self-assessment and attitudes of medical students in relation to provided educational background.

METHODS

A cross-sectional survey (mixed methods-approach) combined with the curriculum analysis and questionnaires. Quantitative method: a questionnaire of knowledge of HH issues (QK), and a questionnaire of self-assessment and attitudes (SAQ) towards HH. Qualitative method focused on an analysis of content of the curriculum documents.

RESULTS

250 (KQ) and 238 (SAQ) questionnaires were analysed from students of general medicine (n = 262; average age 22.5 years). Below-average knowledge of HH and a high self-assessment of knowledge and compliance with HH was reported by 72.2% and 76.0% of students, respectively. Significant differences in knowledge and self-assessment of HH were found among study years and gender. The content analysis has revealed gaps in HH-related information in general medicine educational programme.

CONCLUSIONS

It is highly expected that there might be some association between low HH knowledge level, false self-assessment and educational programme in medical students.

Prevention of Prosthetic Joint Infection: From Traditional Approaches towards Quality Improvement and Data Mining

A projected increased use of total joint arthroplasties will naturally result in a related increase in the number of prosthetic joint infections (PJIs). Suppression of the local peri-implant immune response counters efforts to eradicate bacteria, allowing the formation of biofilms and compromising preventive measures taken in the operating room. For these reasons, the prevention of PJI should focus concurrently on the following targets: (i) identifying at-risk patients; (ii) reducing “bacterial load” perioperatively; (iii) creating an antibacterial/antibiofilm environment at the site of surgery; and (iv) stimulating the local immune response. Despite considerable recent progress made in experimental and clinical research, a large discrepancy persists between proposed and clinically implemented preventative strategies. The ultimate anti-infective strategy lies in an optimal combination of all preventative approaches into a single “clinical pack”, applied rigorously in all settings involving prosthetic joint implantation. In addition, “anti-infective” implants might be a choice in patients who have an increased risk for PJI. However, further progress in the prevention of PJI is not imaginable without a close commitment to using quality improvement tools in combination with continual data mining, reflecting the efficacy of the preventative strategy in a particular clinical setting.