Adherence to Personal Protective Equipment practices during the COVID-19 pandemic: A pilot study

A direct observational pilot project of healthcare personnel (HCP) was conducted to validate a tool that measures personal protective equipment (PPE) adherence at a large pediatric institution. Overall unit PPE adherence for all moments ranged from 50-61%. Masking was the most adhered to PPE moment (100%); hand hygiene prior to donning PPE had the lowest adherence (13%). Using data from this standardized tool, researchers can evolve PPE standards to maximize their adherence, effectiveness, and ease of utilization.

Perceptions of infection control professionals toward electronic surveillance software supporting inpatient infections: A mixed methods study

BACKGROUND

Electronic surveillance software (ESS) collects multiple patient data from hospital software to assist infection control professionals in the prevention and control of hospital-associated infections. This study aimed to understand the perceptions of end users (i.e., infection control professionals) and the facilitators and barriers related to a commercial ESS named ZINC and to assess its usability.

METHODS

A mixed-method research approach was adopted among infection control professionals 10 months after the implementation of commercial ESS in the university hospital of Nancy, France. A qualitative analysis based on individual semistructured interviews was conducted to collect professionals' perceptions of ESS and to understand barriers and facilitators. Qualitative data were systematically coded and thematically analyzed. A quantitative analysis was performed using the System Usability Scale (SUS).

RESULTS

Thirteen infection control professionals were included. Qualitative analysis revealed technical, organizational and human barriers to the installation and use stages and five significant facilitators: the relevant design of the ESS, the improvement of infection prevention and control practices, the designation of a champion/superuser among professionals, training, and collaboration with the developer team. Quantitative analysis indicated that the evaluated ESS was a "good" system in terms of perceived ease of use, with an overall median SUS score of 85/100.

CONCLUSIONS

This study shows the value of ESS to support inpatient infections as perceived by infection control professionals. It reveals barriers and facilitators to the implementation and adoption of ESS. These barriers and facilitators should be considered to facilitate the installation of the software in other hospitals.

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.

Improving healthcare worker adherence to the use of transmission-based precautions through application of human factors design: a prospective multi-centre study

A key component of transmission-based precautions (TBPs) is the use of personal protective equipment (PPE) but healthcare worker (HCW) adherence remains suboptimal. A human factors-based intervention was implemented to improve adherence to TBPs including (i) improved signage, (ii) standardized placement of signage, (iii) introduction of a mask with integrated face shield, and (iv) improvement in PPE availability. Donning of the correct PPE by HCWs improved significantly (79.7 vs 56.4%; P < 0.001). This approach may be more effective than education alone, but further study is required to determine sustainability and subsequent impact on transmission of healthcare-associated infections.

Adherence to contact precautions by different types of healthcare workers through video monitoring in a tertiary hospital

BACKGROUND

Contact precautions are required to prevent transmission of multi-drug-resistant organisms; however, reports on adherence rates vary. This study used video monitoring to evaluate adherence to the use of personal protective equipment (PPE) by different types of healthcare workers.

METHODS

This observational study was conducted in a 781-bed tertiary hospital from July 2016 to March 2017. Cameras were installed in areas where staff don PPE. Infection control teams observed the videos and assessed adherence rates.

RESULTS

In total, 1097 opportunities for donning PPE were observed. Most staff observed were nurses and nursing assistants (Ns/Nsas) (880/1097, 80.2%). Overall, the adherence rate to appropriate PPE use was 34.0%. The adherence rate among Ns/Nsas was lower (239/858, 27.9%) compared with infectious disease doctors (18/18, 100%) and cleaning staff (42/49, 85.7%). The adherence rate for PPE use for Clostridium difficile infection (CDI) with toxin detection was significantly higher than that for CDI without toxin detection and multi-drug-resistant organisms (P<0.001 for both). The adherence rate for patients with an independent functional status was higher than that for patients with a dependent functional status (P=0.018). The adherence rate was lower in the intensive care unit (ICU) than in non-ICU wards (27.6% vs 36.5%; P=0.006).

CONCLUSION

Video monitoring is a useful tool for monitoring adherence to PPE use, facilitating observation of more PPE opportunities than direct observation. Adherence to contact precautions varied by occupation; however, overall adherence was insufficient. The lower adherence rate in nurses might be due to more frequent care visits.

Role of Human Factors Engineering in Infection Prevention: Gaps and Opportunities

Human factors engineering (HFE), with its focus on studying how humans interact with systems, including their physical and organizational environment, the tools and technologies they use, and the tasks they perform, provides principles, tools, and techniques for systematically identifying important factors, for analyzing and evaluating how these factors interact to increase or decrease the risk of Healthcare-associated infections (HAI), and for identifying and implementing effective preventive measures. We reviewed the literature on HFE and infection prevention and control and identified major themes to document how researchers and infection prevention staff have used HFE methods to prevent HAIs and to identify gaps in our knowledge about the role of HFE in HAI prevention and control. Our literature review found that most studies in the healthcare domain explicitly applying (HFE) principles and methods addressed patient safety issues not infection prevention and control issues. In addition, most investigators who applied human factors principles and methods to infection prevention issues assessed only one human factors element such as training, technology evaluations, or physical environment design. The most significant gap pertains to the limited use and application of formal HFE tools and methods. Every infection prevention study need not assess all components in a system, but investigators must assess the interaction of critical system components if they want to address latent and deep-rooted human factors problems.

Slow adoption of automated infection prevention surveillance: are human factors contributing?

Although automated surveillance technology has been evolving for decades, adoption of these technologies is in a nascent state. The current trajectory of public reporting, continued emergence of multidrug-resistant organisms, and mandated antimicrobial stewardship initiatives will result in an increased surveillance workload for ICPs. The use of traditional surveillance methods will be inefficient in meeting the demands for more data and are potentially flawed by subjective interpretation. An examination is offered of the slow adoption of automated surveillance technology from a system perspective with the inherent ambiguities that may operate within the ICP work structure. Formal qualitative research is needed to assess the human factors associated with lack of acceptance of automated surveillance systems. Identification of these factors will allow the National Healthcare Safety Network and professional organizations to offer educational programs and mentoring to the ICP community that target knowledge deficits and the embedded culture that embraces the status quo. With the current focus on fully electronic surveillance systems that perform surveillance in its entirety without case review, effective use of the data will be dependent on ICP skills and their understanding of the strengths and limitations of output from algorithmic detection models.