Clinical Decision Support Systems to Reduce Unnecessary Clostridioides difficile Testing Across Multiple Hospitals.

BACKGROUND: Inappropriate Clostridioides difficile testing has adverse consequences for patients, hospitals, and public health. Computerized clinical decision support (CCDS) systems in the electronic health record (EHR) may reduce C. difficile test ordering; however, effectiveness of different approaches, ease of use, and best fit into healthcare providers' (HCP) workflow are not well understood. METHODS: Nine academic and 6 community hospitals in the United States participated in this 2-year cohort study. CCDS (hard stop or soft stop) triggered when a duplicate C. difficile test order was attempted or if laxatives were recently received. The primary outcome was the difference in testing rates pre- and post-CCDS interventions, using incidence rate ratios (IRRs) and mixed-effect Poisson regression models. We performed qualitative evaluation (contextual inquiry, interviews, focus groups) based on a human factors model. We identified themes using a codebook with primary nodes and subnodes. RESULTS: In 9 hospitals implementing hard-stop CCDS and 4 hospitals implementing soft-stop CCDS, C. difficile testing incidence rate (IR) reduction was 33% (95% confidence interval [CI]: 30%-36%) and 23% (95% CI: 21%-25%), respectively. Two hospitals implemented a non-EHR-based human intervention with IR reduction of 21% (95% CI: 15%-28%). HCPs reported generally favorable experiences and highlighted time efficiencies such as inclusion of the patient's most recent laxative administration on the CCDS. Organizational factors, including hierarchical cultures and communication between HCPs caring for the same patient, impact CCDS acceptance and integration. CONCLUSIONS: CCDS systems reduced unnecessary C. difficile testing and were perceived positively by HCPs when integrated into their workflow and when displaying relevant patient-specific information needed for decision making.

Effect of an Intervention Package and Teamwork Training to Prevent Healthcare Personnel Self-contamination During Personal Protective Equipment Doffing.

BACKGROUND: More than 28 000 people were infected with Ebola virus during the 2014-2015 West African outbreak, resulting in more than 11 000 deaths. Better methods are needed to reduce the risk of self-contamination while doffing personal protective equipment (PPE) to prevent pathogen transmission. METHODS: A set of interventions based on previously identified failure modes was designed to mitigate the risk of self- contamination during PPE doffing. These interventions were tested in a randomized controlled trial of 48 participants with no prior experience doffing enhanced PPE. Contamination was simulated using a fluorescent tracer slurry and fluorescent polystyrene latex spheres (PLSs). Self-contamination of scrubs and skin was measured using ultraviolet light visualization and swabbing followed by microscopy, respectively. Doffing sessions were videotaped and reviewed to score standardized teamwork behaviors. RESULTS: Participants in the intervention group contaminated significantly fewer body sites than those in the control group (median [interquartile range], 6 [3-8] vs 11 [6-13], P = .002). The median contamination score was lower for the intervention group than the control group when measured by ultraviolet light visualization (23.15 vs 64.45, P = .004) and PLS swabbing (72.4 vs 144.8, P = .001). The mean teamwork score was greater in the intervention group (42.2 vs 27.5, P < .001). CONCLUSIONS: An intervention package addressing the PPE doffing task, tools, environment, and teamwork skills significantly reduced the amount of self-contamination by study participants. These elements can be incorporated into PPE guidance and training to reduce the risk of pathogen transmission.

Barriers to physical distancing among healthcare workers on an academic hospital unit during the coronavirus disease 2019 (COVID-19) pandemic.

BACKGROUND: Physical distancing among healthcare workers (HCWs) is an essential strategy in preventing HCW-to-HCWs transmission of severe acute respiratory coronavirus virus 2 (SARS-CoV-2). OBJECTIVE: To understand barriers to physical distancing among HCWs on an inpatient unit and identify strategies for improvement. DESIGN: Qualitative study including observations and semistructured interviews conducted over 3 months. SETTING: A non-COVID-19 adult general medical unit in an academic tertiary-care hospital. PARTICIPANTS: HCWs based on the unit. METHODS: We performed a qualitative study in which we (1) observed HCW activities and proximity to each other on the unit during weekday shifts July-October 2020 and (2) conducted semi-structured interviews of HCWs to understand their experiences with and perspectives of physical distancing in the hospital. Qualitative data were coded based on a human-factors engineering model. RESULTS: We completed 25 hours of observations and 20 HCW interviews. High-risk interactions often occurred during handoffs of care at shift changes and patient rounds, when HCWs gathered regularly in close proximity for at least 15 minutes. Identified barriers included spacing and availability of computers, the need to communicate confidential patient information, and the desire to maintain relationships at work. CONCLUSIONS: Physical distancing can be improved in hospitals by restructuring computer workstations, work rooms, and break rooms; applying visible cognitive aids; adapting shift times; and supporting rounds and meetings with virtual conferencing. Additional strategies to promote staff adherence to physical distancing include rewarding positive behaviors, having peer leaders model physical distancing, and encouraging additional safe avenues for social connection at a safe distance.

Improving physical distancing among healthcare workers in a pediatric intensive care unit.

BACKGROUND: Healthcare workers (HCWs) not adhering to physical distancing recommendations is a risk factor for acquisition of severe acute respiratory coronavirus virus 2 (SARS-CoV-2). The study objective was to assess the impact of interventions to improve HCW physical distancing on actual distance between HCWs in a real-life setting. METHODS: HCWs voluntarily wore proximity beacons to measure the number and intensity of physical distancing interactions between each other in a pediatric intensive care unit. We compared interactions before and after implementing a bundle of interventions including changes to the layout of workstations, cognitive aids, and individual feedback from wearable proximity beacons. RESULTS: Overall, we recorded 10,788 interactions within 6 feet (∼2 m) and lasting >5 seconds. The number of HCWs wearing beacons fluctuated daily and increased over the study period. On average, 13 beacons were worn daily (32% of possible staff; range, 2-32 per day). We recorded 3,218 interactions before the interventions and 7,570 interactions after the interventions began. Using regression analysis accounting for the maximum number of potential interactions if all staff had worn beacons on a given day, there was a 1% decline in the number of interactions per possible interactions in the postintervention period (incident rate ratio, 0.99; 95% confidence interval, 0.98-1.00; P = .02) with fewer interactions occurring at nursing stations, in workrooms and during morning rounds. CONCLUSIONS: Using quantitative data from wearable proximity beacons, we found an overall small decline in interactions within 6 feet between HCWs in a busy intensive care unit after a multifaceted bundle of interventions was implemented to improve physical distancing.

The case for wearable proximity devices to inform physical distancing among healthcare workers.

OBJECTIVE: Despite the importance of physical distancing in reducing SARS-CoV-2 transmission, this practice is challenging in healthcare. We piloted use of wearable proximity beacons among healthcare workers (HCWs) in an inpatient unit to highlight considerations for future use of trackable technologies in healthcare settings. MATERIALS AND METHODS: We performed a feasibility pilot study in a non-COVID adult medical unit from September 28 to October 28, 2020. HCWs wore wearable proximity beacons, and interactions defined as <6 feet for ≥5 s were recorded. Validation was performed using direct observations. RESULTS: A total of 6172 close proximity interactions were recorded, and with the removal of 2033 false-positive interactions, 4139 remained. The highest proportion of interactions occurred between 7:00 Am-9:00 Am. Direct observations of HCWs substantiated these findings. DISCUSSION: This pilot study showed that wearable beacons can be used to monitor and quantify HCW interactions in inpatient settings. CONCLUSION: Technology can be used to track HCW physical distancing.

Targeted gown and glove use to prevent Staphylococcus aureus acquisition in community-based nursing homes: A pilot study.

OBJECTIVE: To test the feasibility of targeted gown and glove use by healthcare personnel caring for high-risk nursing-home residents to prevent Staphylococcus aureus acquisition in short-stay residents. DESIGN: Uncontrolled clinical trial. SETTING: This study was conducted in 2 community-based nursing homes in Maryland. PARTICIPANTS: The study included 322 residents on mixed short- and long-stay units. METHODS: During a 2-month baseline period, all residents had nose and inguinal fold swabs taken to estimate S. aureus acquisition. The intervention was iteratively developed using a participatory human factors engineering approach. During a 2-month intervention period, healthcare personnel wore gowns and gloves for high-risk care activities while caring for residents with wounds or medical devices, and S. aureus acquisition was measured again. Whole-genome sequencing was used to assess whether the acquisition represented resident-to-resident transmission. RESULTS: Among short-stay residents, the methicillin-resistant S. aureus acquisition rate decreased from 11.9% during the baseline period to 3.6% during the intervention period (odds ratio [OR], 0.28; 95% CI, 0.08-0.92; P = .026). The methicillin-susceptible S. aureus acquisition rate went from 9.1% during the baseline period to 4.0% during the intervention period (OR, 0.41; 95% CI, 0.12-1.42; P = .15). The S. aureus resident-to-resident transmission rate decreased from 5.9% during the baseline period to 0.8% during the intervention period. CONCLUSIONS: Targeted gown and glove use by healthcare personnel for high-risk care activities while caring for residents with wounds or medical devices, regardless of their S. aureus colonization status, is feasible and potentially decreases S. aureus acquisition and transmission in short-stay community-based nursing-home residents.

Respiratory Practices in the Long-term Care Setting: A Human Factors-Based Risk Analysis.

OBJECTIVE: To systematically assess safety risks pertaining to tracheostomy care in the long-term care (LTC) setting using a human factors engineering approach. DESIGN: We utilized a 5-part approach to complete our proactive risk assessment: (1) performed a hierarchical task analysis of the processes of tracheostomy stoma and suctioning; (2) identified failure modes where a subtask may be completed inappropriately; (3) prioritized each failure mode based on a risk priority scale; (4) identified contributing factors to and consequences for each of the prioritized failure modes; and (5) identified potential solutions to eliminate or mitigate risks. SETTING: Three high-acuity LTC facilities with ventilator units across Maryland. METHODS: The hierarchical task analysis was conducted jointly by 2 human-factors experts and an infectious disease physician based on respiratory care policies from the Centers for Disease Control and Prevention and existing policies at each LTC facility. The findings were used to guide direct observations with contextual inquiry and focus group sessions to assess safety risks for residents receiving tracheostomy care. RESULTS: Direct observations of tracheostomy care and suctioning in the LTC setting revealed significant variations in practice. Respiratory therapists working in LTC reported lack of training and ambiguity concerning recommended procedures to reduce infection transmission in daily care. Highest risk steps identified in tracheostomy care and suctioning included hand hygiene, donning gloves, and providing intermittent suctioning as the suction catheter was withdrawn. Participants identified risk mitigation strategies targeting these high-risk failure modes that addressed contributing factors related to 5 work system components: person (knowledge and competency), task (eg, urgency or time constraints), tools and technology (eg, availability of hand sanitizer), environment (eg, communal rooms), and organization (eg, patient safety culture). CONCLUSIONS AND IMPLICATIONS: Human factors analysis of the highest-risk steps in respiratory care activities in the LTC setting suggest several potential mitigation strategies to decrease the risk of infection transmission. Clear procedure guidelines with training are needed to reduce ambiguity and improve care in this setting. Involving frontline staff in patient safety issues using human factors principles and risk analysis may encourage participation and improve the infection prevention culture in LTC.

A novel personal protective equipment coverall was rated higher than standard Ebola virus personal protective equipment in terms of comfort, mobility and perception of safety when tested by health care workers in Liberia and in a United States biocontainment unit.

BACKGROUND: During the 2014-2016 Ebola virus epidemic, more than 500 health care workers (HCWs) died in spite of the use of personal protective equipment (PPE). The Johns Hopkins University Center for Bioengineering Innovation and Design (CBID) and Jhpiego, an international nongovernmental organization affiliate of Johns Hopkins, collaborated to create new PPE to improve the ease of the doffing process. METHODS: HCWs in Liberia and a US biocontainment unit compared standard Médecins Sans Frontière PPE (PPE A) with the new PPE (PPE B). Participants wore each PPE ensemble while performing simulated patient care activities. Range of motion, time to doff, comfort, and perceived risk were measured. RESULTS: Overall, 100% of participants preferred PPE B over PPE A (P < .0001); 98.1% of respondents would recommend PPE B for their home clinical unit (P < .0001). There was a trend towards greater comfort in PPE B. HCWs at both sites felt more at risk in PPE A than PPE B (71.9% vs 25% in Liberia, P < .0001; 100% vs 40% in the US biocontainment unit, P < .0001). CONCLUSIONS: HCWs preferred a new PPE ensemble to Médecins Sans Frontière PPE for high-consequence pathogens. Further studies on the safety of this new PPE need to be conducted.

Evaluation of environmental cleaning of patient rooms: Impact of different fluorescent gel markers.

In this systematic evaluation of fluorescent gel markers (FGM) applied to high-touch surfaces with a metered applicator (MA) made for the purpose versus a generic cotton swab (CS), removal rates were 60.5% (476 of 787) for the MA and 64.3% (506 of 787) for the CS. MA-FGM removal interpretation was more consistent, 83% versus 50% not removed, possibly due to less varied application and more adhesive gel.

Human factors-based risk analysis to improve the safety of doffing enhanced personal protective equipment.

OBJECTIVE: To systematically assess enhanced personal protective equipment (PPE) doffing safety risks. DESIGN: We employed a 3-part approach to this study: (1) hierarchical task analysis (HTA) of the PPE doffing process; (2) human factors-informed failure modes and effects analysis (FMEA); and (3) focus group sessions with a convenience sample of infection prevention (IP) subject matter experts. SETTING: A large academic US hospital with a regional Special Pathogens Treatment Center and enhanced PPE doffing protocol experience.ParticipantsEight IP experts. METHODS: The HTA was conducted jointly by 2 human-factors experts based on the Centers for Disease Control and Prevention PPE guidelines. The findings were used as a guide in 7 focus group sessions with IP experts to assess PPE doffing safety risks. For each HTA task step, IP experts identified failure mode(s), assigned priority risk scores, identified contributing factors and potential consequences, and identified potential risk mitigation strategies. Data were recorded in a tabular format during the sessions. RESULTS: Of 103 identified failure modes, the highest priority scores were associated with team members moving between clean and contaminated areas, glove removal, apron removal, and self-inspection while preparing to doff. Contributing factors related to the individual (eg, technical/ teamwork competency), task (eg, undetected PPE contamination), tools/technology (eg, PPE design characteristics), environment (eg, inadequate space), and organizational aspects (eg, training) were identified. Participants identified 86 types of risk mitigation strategies targeting the failure modes. CONCLUSIONS: Despite detailed guidelines, our study revealed 103 enhanced PPE doffing failure modes. Analysis of the failure modes suggests potential mitigation strategies to decrease self-contamination risk during enhanced PPE doffing.

Improving daily patient room cleaning: an observational study using a human factors and systems engineering approach.

BACKGROUND: While playing a critical role in preventing healthcare-associated infections, patient room cleaning is often unsatisfactorily performed. To improve patient room cleaning, a human factors and systems engineering (HFSE) approach is needed to understand the complex cleaning process and associated work system factors. PURPOSE: We conducted an observational study to assess the performance of environmental care (EVC) associates during daily patient room cleaning and identify work system factors influencing their performance. METHODS: This study was conducted in eight adult medicine inpatient units at a large urban academic medical center. An HFSE researcher shadowed 10 day-shift EVC associates performing daily patient room cleanings and used a semi-structured observation form to collect quantitative data (e.g., duration of room cleaning, orders for surface cleaning) and qualitative data (e.g., challenges to patient room cleaning). Descriptive statistics (e.g., median, interquartile range) were reported for cleaning performance, and bivariate and regression analyses were conducted to identify factors influencing cleaning performance. We also performed link analyses of the workflow of EVC associates and qualitative analyses of observer notes to identify challenges to daily patient room cleaning. RESULTS: We observed 89 patient room cleanings. Median duration of cleaning a room was 14 minutes, and median percentage of surfaces cleaned in a room was 63%. High-touch surfaces that were frequently missed during daily cleaning included the bedrails, telephone, patient and visitor chairs, and cabinet. Work system factors that could influence cleaning performance included the type of unit, the presence of the patient and family members in the room, cleaning patterns and orders of EVC associates, and interruptions EVC associates encountered while cleaning. CONCLUSIONS: Daily patient room cleaning was influenced by a number of work system factors. To improve daily patient room cleaning, multifaceted interventions are needed to address these system-level factors.