The impact of automatic video auditing with real-time feedback on the quality and quantity of handwash events in a hospital setting

Improving hand hygiene of young children with a digital intervention: a cluster-randomised controlled field trial

Contagious diseases that affect young children place a great burden on them and their families. Proper hand hygiene is an important measure to reduce the disease burden, however, its implementation in day care centres is challenging. This paper introduces a digital intervention to support independent and good handwashing among young children. The intervention leverages animated instructions triggered by water and soap use, together with a symbolic reward shown to children on a screen during and immediately after handwashing. We tested the intervention in a pre-registered, cluster-randomised controlled field trial in 4 day care centres in Finland and Germany with 162 children over 42 days. The intervention increased soaping time, used as a proxy for handwashing quality, by 5.30 s (+ 62%, p < 0.001). The effect occurs immediately at the onset of the intervention and is maintained throughout the intervention phase.

Harnessing of Artificial Intelligence for the Diagnosis and Prevention of Hospital-Acquired Infections: A Systematic Review

Healthcare-associated infections (HAIs) are the most common adverse events in healthcare and constitute a major global public health concern. Surveillance represents the foundation for the effective prevention and control of HAIs, yet conventional surveillance is costly and labor intensive. Artificial intelligence (AI) and machine learning (ML) have the potential to support the development of HAI surveillance algorithms for the understanding of HAI risk factors, the improvement of patient risk stratification as well as the prediction and timely detection and prevention of infections. AI-supported systems have so far been explored for clinical laboratory testing and imaging diagnosis, antimicrobial resistance profiling, antibiotic discovery and prediction-based clinical decision support tools in terms of HAIs. This review aims to provide a comprehensive summary of the current literature on AI applications in the field of HAIs and discuss the future potentials of this emerging technology in infection practice. Following the PRISMA guidelines, this study examined the articles in databases including PubMed and Scopus until November 2023, which were screened based on the inclusion and exclusion criteria, resulting in 162 included articles. By elucidating the advancements in the field, we aim to highlight the potential applications of AI in the field, report related issues and shortcomings and discuss the future directions.

Current issues in hand hygiene

BACKGROUND

Multiple aspects of hand hygiene have changed in recent years.

METHODS

A PubMed search was conducted to identify recent articles about hand hygiene.

RESULTS

The COVID-19 pandemic caused temporary changes in hand hygiene compliance rates and shortages of alcohol-based hand sanitizers (ABHSs), and in marketing of some products that were ineffective or unsafe. Fortunately, ABHSs are effective against SARS-CoV-2 and other emerging pathogens including Candida auris and mpox. Proper placement, maintenance, and design of ABHS dispensers have gained additional attention. Current evidence suggests that if an adequate volume of ABHS has been applied to hands, personnel must rub their hands together for at least 15 seconds before hands feel dry (dry time), which is the primary driver of antimicrobial efficacy. Accordingly, practical methods of monitoring hand hygiene technique are needed. Direct observation of hand hygiene compliance remains a challenge in many healthcare facilities, generating increased interest in automated hand hygiene monitoring systems (AHHMSs). However, several barriers have hindered widespread adoption of AHHMSs. AHHMSs must be implemented as part of a multimodal improvement program to successfully improve hand hygiene performance rates.

CONCLUSIONS

Remaining gaps in our understanding of hand hygiene warrant continued research into factors impacting hand hygiene practices.

Artificial Intelligence Applications in Health Care Practice: A Scoping Review (Preprint)

Background

Artificial intelligence (AI) is often heralded as a potential disruptor that will transform the practice of medicine. The amount of data collected and available in health care, coupled with advances in computational power, has contributed to advances in AI and an exponential growth of publications. However, the development of AI applications does not guarantee their adoption into routine practice. There is a risk that despite the resources invested, benefits for patients, staff, and society will not be realized if AI implementation is not better understood.

Objective

The aim of this study was to explore how the implementation of AI in health care practice has been described and researched in the literature by answering 3 questions: What are the characteristics of research on implementation of AI in practice? What types and applications of AI systems are described? What characteristics of the implementation process for AI systems are discernible?

Methods

A scoping review was conducted of MEDLINE (PubMed), Scopus, Web of Science, CINAHL, and PsycINFO databases to identify empirical studies of AI implementation in health care since 2011, in addition to snowball sampling of selected reference lists. Using Rayyan software, we screened titles and abstracts and selected full-text articles. Data from the included articles were charted and summarized.

Results

Of the 9218 records retrieved, 45 (0.49%) articles were included. The articles cover diverse clinical settings and disciplines; most (32/45, 71%) were published recently, were from high-income countries (33/45, 73%), and were intended for care providers (25/45, 56%). AI systems are predominantly intended for clinical care, particularly clinical care pertaining to patient-provider encounters. More than half (24/45, 53%) possess no action autonomy but rather support human decision-making. The focus of most research was on establishing the effectiveness of interventions (16/45, 35%) or related to technical and computational aspects of AI systems (11/45, 24%). Focus on the specifics of implementation processes does not yet seem to be a priority in research, and the use of frameworks to guide implementation is rare.

Conclusions

Our current empirical knowledge derives from implementations of AI systems with low action autonomy and approaches common to implementations of other types of information systems. To develop a specific and empirically based implementation framework, further research is needed on the more disruptive types of AI systems being implemented in routine care and on aspects unique to AI implementation in health care, such as building trust, addressing transparency issues, developing explainable and interpretable solutions, and addressing ethical concerns around privacy and data protection.

Hand Hygiene Behaviours Monitored by an Electronic System in the Intensive Care Unit-A Prospective Observational Study

BACKGROUND

Hand hygiene (HH) compliance is hard to improve and underlying behaviours are not clearly understood among healthcare workers.

AIM

To study healthcare workers' HH behaviours.

METHODS

Prospective observational study. Sanibit electronic hand hygiene system was installed in a 10-bed surgical intensive care unit that automatically detected HH opportunities when healthcare workers entered or exited a patient room, and tracked healthcare worker's HH compliance. HH compliance rate and patient contact time were calculated and analyzed at both the ICU and individual levels over time.

FINDINGS

A total of 27,692 HH opportunities were recorded during this 6-month trial period. The HH compliance rate was significantly higher when healthcare workers exited patient rooms than when they entered rooms (37.3% vs. 26.1%, P < 0.001). The full, partial, and total HH compliance rates of quick in-out of room (in room less than 3 seconds) events were significantly lower than those of long in-out room (in room more than 30 seconds) events (23.45% vs 32.77%, 21.44% vs 35.03%, and 44.88% vs 67.81% respectively) (P-value <0.001). There was also significantly differences in HH compliance among individual healthcare workers (P < 0.001). No statistically significant difference was found in overall HH compliance rate and patient contact time over hours of the day or days of the week except partial HH compliance rates.

CONCLUSION

Patterns of healthcare workers' HH behaviors are complex and variable, which could facilitate targeted and personalized interventions to improve HH compliance.

DEVELOPMENT AND VALIDATION OF A CHECKLIST FOR THE SAFETY OF HOSPITALIZED CHILDREN

ABSTRACT Objective: to develop and validate a checklist of safety actions for hospitalized children. Method: a methodological research study carried out from March 2017 to March 2020 in two phases: 1) Identification of the themes and elaboration of the checklist through the literature review; 2) Content validation with expert judges by means of the Delphi technique, applying the Content Validity Index (CVI), accepting values >0.8 for the CVI per item and >0.9 for the checklist. The data collection instrument was organized using an ordinal progressive valuation scale, of the Likert type. The content validation stage was performed in three rounds using a Google Forms® electronic form. Fifteen experts participated in the survey in the first round and 14 in the second and third rounds. The statistical analysis of the data was performed with the aid of Google Forms® and of the Excel® software, and the results were presented descriptively and in a table. Results: the final version of the checklist consisted of 6 categories and 23 check items, validated with a Content Validity Index of 0.98. The checklist was also validated in relation to the objectives (0.95) and to the structure and presentation (0.98). Conclusion: validation of the content, objectives, structure and presentation of the checklist allows this tool to be implemented in any pediatric hospitalization unit, contributing to the care practice aimed at the safety of hospitalized children.

Implementing an electronic hand hygiene system improved compliance in the intensive care unit

BACKGROUND

Hand hygiene (HH) compliance is low and difficult to improve among health care workers. We aim to validate an electronic HH system and assess the impact of this system on HH compliance and quality changes over time at both group and individual levels.

METHODS

An automated electronic HH system was installed in a 10-bed surgical intensive care unit.

RESULTS

The full HH compliance rate increased significantly from 8.4% in week 1 to 20.5% in week 16 with week 10 being the highest (27.4%). The partial compliance rate maintained relative consistency between 13.2% and 20.0%. The combined compliance rate (full compliance rate + partial compliance rate) increased from 23.5% in week 1 to 34.6% in week 16 with week 10 being the highest (41.4%).

DISCUSSION

We found significant variations among providers in terms of HH opportunities per shift, full compliance, partial compliance and combined compliance rates. The average duration of hand rubbing over time in partial compliance occurrences did not change significantly over time.

CONCLUSIONS

A sensor-based platform with automated HH compliance and quality monitoring, real time feedback and comprehensive individual level analysis, improved providers' HH compliance in an intensive care unit. There were significant variations among individual providers.

Electronic Monitoring Systems for Hand Hygiene: Systematic Review of Technology

BACKGROUND

Hand hygiene is one of the most effective ways of preventing health care-associated infections and reducing their transmission. Owing to recent advances in sensing technologies, electronic hand hygiene monitoring systems have been integrated into the daily routines of health care workers to measure their hand hygiene compliance and quality.

OBJECTIVE

This review aims to summarize the latest technologies adopted in electronic hand hygiene monitoring systems and discuss the capabilities and limitations of these systems.

METHODS

A systematic search of PubMed, ACM Digital Library, and IEEE Xplore Digital Library was performed following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies were initially screened and assessed independently by the 2 authors, and disagreements between them were further summarized and resolved by discussion with the senior author.

RESULTS

In total, 1035 publications were retrieved by the search queries; of the 1035 papers, 89 (8.60%) fulfilled the eligibility criteria and were retained for review. In summary, 73 studies used electronic monitoring systems to monitor hand hygiene compliance, including application-assisted direct observation (5/73, 7%), camera-assisted observation (10/73, 14%), sensor-assisted observation (29/73, 40%), and real-time locating system (32/73, 44%). A total of 21 studies evaluated hand hygiene quality, consisting of compliance with the World Health Organization 6-step hand hygiene techniques (14/21, 67%) and surface coverage or illumination reduction of fluorescent substances (7/21, 33%).

CONCLUSIONS

Electronic hand hygiene monitoring systems face issues of accuracy, data integration, privacy and confidentiality, usability, associated costs, and infrastructure improvements. Moreover, this review found that standardized measurement tools to evaluate system performance are lacking; thus, future research is needed to establish standardized metrics to measure system performance differences among electronic hand hygiene monitoring systems. Furthermore, with sensing technologies and algorithms continually advancing, more research is needed on their implementation to improve system performance and address other hand hygiene-related issues.

Three-year hand hygiene monitoring and impact of real-time reminders on compliance

BACKGROUND

Hand hygiene remains both the major strategy and an ongoing challenge for infection control. The main issues in the sustainability of hand hygiene automatic monitoring are healthcare worker (HCW) turnover rates and declining participation.

AIM

To assess hand hygiene compliance and the impact of real-time reminders over three years.

METHODS

HCW compliance was observed for the use of alcohol-based hand rubs (AHR) on room entry and exit. Linear multi-level mixed models with time autocorrelations were performed to analyse the repeated measurements of daily room compliance and the effect of reminders over eight quarters (24 months).

FINDINGS

In all, 111 HCWs were observed and 525,576 activities were identified in the database. There was an improvement in compliance both on room entry and exit over two years, and the rooms which had activated reminders had better performance than the rooms which did not have activated reminders.

CONCLUSIONS

This study showed the benefit of using real-time reminders; even 20% of rooms with an activated reminder improved overall hand hygiene compliance. A randomized real-time reminder setting may be a potential solution in reducing user fatigue and enhancing HCW self-awareness.

Information technology on hand hygiene compliance among health care professionals: A systematic review and meta-analysis

AIM

To determine the effectiveness of information technology interventions on hand hygiene compliance among health care professionals.

BACKGROUND

Performing hand hygiene is the optimal approach to prevent the transmission of health care-associated infections. However, results regarding the effectiveness of information technology interventions on hand hygiene compliance were inconsistent to date.

EVALUATION

A search for studies published up to May 2020 was undertaken. A meta-analysis was conducted using RevMan 5.3 software.

KEY ISSUES

The most commonly used information technology systems were as follows: automated training, electronic counting devices and remote monitoring, real-time hand hygiene reminders and feedback, and automated monitoring. These four types of technology systems can significantly improve hand hygiene compliance among health care professionals (odds ratio = 3.06, p < .001).

CONCLUSION

The four types of information technology can be effectively used to change the hand hygiene behaviour. Because the information systems can monitor personnel and conduct statistical analyses automatically, they save labour costs of human monitors, are more time efficient and eliminate accompanying human error.

IMPLICATIONS FOR NURSING MANAGEMENT

The use of the four types of information technology is convenient and could reduce health care-associated infections; thus, they could be widely used in the future as the key to increase hand hygiene compliance rate.

How does innovative technology impact nursing in infectious diseases and infection control? A scoping review

Aim

Considering the increasing number of emerging infectious diseases, innovative approaches are strongly in demand. Additionally, research in this field has expanded exponentially. Thus, faced with this diverse information, we aim to clarify key concepts and knowledge gaps of technology in nursing and the field of infectious diseases.

Design

This scoping review followed the methodology of scoping review guidance from Arksey and O’Malley.

Methods

Six databases were searched systematically (PubMed, Web of Science, IEEE Explore, EBSCOhost, Cochrane Library and Summon). After the removal of duplicates, 532 citations were retrieved and 77 were included in the analysis.

Results

We identified five major trends in technology for nursing and infectious diseases: artificial intelligence, the Internet of things, information and communications technology, simulation technology and e‐learning. Our findings indicate that the most promising trend is the IoT because of the many positive effects validated in most of the reviewed studies.

Powdered Activated Charcoal Tracing in Hand Hygiene Training and Compliance Assessment During the COVID-19 Pandemic

Objective

Because of the COVID-19 pandemic there has been a significant increase in the prevalence of nosocomial infections. As a result, we sought to find an effective, efficient and safe way to train healthcare workers on proper hand washing techniques. We used powdered activated carbon (PAC) as a tracer to visually display hand washing defects after the hand washing process. The real-time visual assessment of the efficacy of the hand washing technique aided in the immediate correction of errors, and this definitively improved hand hygiene techniques of the interns.

Methods

Clinical interns at the emergency department of Shengjing Hospital were included in this study and received training in relation to the six-step hand-washing technique developed by the World Health Organization (WHO). The subjects’ hand-washing defects or faults were traced using PAC and corrected accordingly. Acceptance of the PAC tracing method by the interns, and its safety, were both assessed using a questionnaire survey.

Results

The results indicated that the back of the hands, fingers, and the wrists were prone to hand-washing defects. The hand-washing defects were significantly reduced after targeted corrections by the trainers. Subjects reported satisfactory acceptance toward the PAC tracing method and the method was relatively safe for subjects.

Conclusion

The PAC tracing method can visually display hand-washing defects and significantly improve the effectiveness of hand-washing training.

Sustaining compliance with hand hygiene when resources are low: A quality improvement report

Background

Sustainability of hand hygiene is challenging in low resource settings. Adding ownership and goal setting to the WHO-5 multimodal intervention may help sustain high compliance.

Aim

To increase and sustain compliance of nursing and medical staff with hand hygiene in a tertiary referral center with limited resources.

Methods

A quality improvement initiative was conducted over two years (2016–2018). After determining baseline compliance rates, the WHO-5 multimodal intervention was implemented with staff education and training, system change, hospital reminders, direct observation and feedback, and hospital safety climate. Additionally, the medical staff was responsible for continuous surveillance of compliance (ownership) until rates above 90% were achieved and sustained (goal setting).

Results

Of 2987 observations collected between August 2016 and April 2018, 1630 (54.5%) were before, and 1357 (45.5%) were after patient encounters. The average overall compliance with hand hygiene was sustained at 94% for nursing and medical staff. Two instances of drops below 90% were associated with incidence of nosocomial Rotavirus infections. There were no similar infections during intervention periods with compliance rates above the set goal. Analysis using p-charts revealed significant improvement in compliance rates from baseline (χ² (1) = 7.94, p = 0.005).

Conclusion

Adding ownership and goal setting to the WHO-5 multimodal intervention may help achieve, and sustain high rates of compliance with hand hygiene. Involving health care workers in quality improvement initiatives is feasible, durable, reliable, and cheap, especially in settings with limited financial resources.

Using Artificial Intelligence in Infection Prevention

Purpose of Review

Artificial intelligence (AI) offers huge potential in infection prevention and control (IPC). We explore its potential IPC benefits in epidemiology, laboratory infection diagnosis, and hand hygiene.

Recent Findings

AI has the potential to detect transmission events during outbreaks or predict high-risk patients, enabling development of tailored IPC interventions. AI offers opportunities to enhance diagnostics with objective pattern recognition, standardize the diagnosis of infections with IPC implications, and facilitate the dissemination of IPC expertise. AI hand hygiene applications can deliver behavior change, though it requires further evaluation in different clinical settings. However, staff can become dependent on automatic reminders, and performance returns to baseline if feedback is removed.

Summary

Advantages for IPC include speed, consistency, and capability of handling infinitely large datasets. However, many challenges remain; improving the availability of high-quality representative datasets and consideration of biases within preexisting databases are important challenges for future developments. AI in itself will not improve IPC; this requires culture and behavior change. Most studies to date assess performance retrospectively so there is a need for prospective evaluation in the real-life, often chaotic, clinical setting. Close collaboration with IPC experts to interpret outputs and ensure clinical relevance is essential.