Simple, low-cost environmental design interventions can provide structure to support and improve HCW safety in BCUs. These interventions should be implemented in both current and future BCUs.

Background Few data exist to guide the physical design of biocontainment units, particularly the doffing area. This can impact the contamination risk of healthcare workers (HCWs) during doffing of personal protective equipment (PPE). Methods In phase I of our study, we analyzed simulations of a standard patient care task with 56 trained HCWs focusing on doffing of high-level PPE. In phase II, using a rapid cycle improvement approach, we tested different balance aids and redesigned doffing area layouts with 38 students. In phase III, we tested 1 redesigned layout with an additional 10 trained HCWs. We assessed the effectiveness of design changes on improving the HCW performance (measured by occurrence and number of risky behaviors) and reducing the physical and cognitive load by comparing the results from phase I and phase III. Results The physical load was highest when participants were removing their shoe covers without any balance aid; the use of a chair required the lowest physical effort, followed by horizontal and vertical grab bars. In the revised design (phase III), the overall performance of participants improved. There was a significant decrease in the number of HCW risky behaviors (P = .004); 5 risky behaviors were eliminated and 2 others increased. There was a significant decrease in physical load when removing disposable shoe covers (P = .04), and participants reported a similar workload in the redesigned doffing layout (P = .43). Conclusions Through optimizing the design and layout of the doffing space, we reduced risky behaviors of HCWs during doffing of high-level PPE.

Background The safe removal of personal protective equipment (PPE) can limit transmission of serious communicable diseases, but this process poses challenges to healthcare workers (HCWs). Methods We observed 41 HCWs across 4 Ebola treatment centers in Georgia doffing PPE for simulated patients with serious communicable diseases. Using human factors methodologies, we obtained the details, sequences, and durations of doffing steps; identified the ways each step can fail (failure modes [FMs]); quantified the riskiness of FMs; and characterized the workload of doffing steps. Results Eight doffing steps were common to all hospitals—removal of boot covers, gloves (outer and inner pairs), the outermost garment, the powered air purifying respirator (PAPR) hood, and the PAPR helmet assembly; repeated hand hygiene (eg, with hand sanitizer); and a final handwashing with soap and water. Across hospitals, we identified 256 FMs during the common doffing steps, 61 of which comprised 19 common FMs. Most of these common FMs were above average in their riskiness at each hospital. At all hospitals, hand hygiene, removal of the outermost garment, and removal of boot covers were above average in their overall riskiness. Measurements of workload revealed that doffing steps were often mentally demanding, and this facet of workload correlated most strongly with the effortfulness of a doffing step. Conclusions We systematically identified common points of concern in protocols for doffing high-level PPE. Addressing FMs related to hand hygiene and the removal of the outermost garment, boot covers, and PAPR hood could improve HCW safety when doffing high-level PPE. We identified ways that doffing protocols for high-level personal protective equipment may fail to protect healthcare workers. Hand hygiene, removing the outermost garment, boot covers, and respirator hood harbored the greatest risk and failed in similar ways across different hospitals.

IMPORTANCE Hospitalized children are at increased risk of influenza-related complications, yet influenza vaccine coverage remains low among this group. Evidence-based strategies about vaccination of vulnerable children during all health care visits are especially important during the COVID-19 pandemic. OBJECTIVE To design and evaluate a clinical decision support (CDS) strategy to increase the proportion of eligible hospitalized children who receive a seasonal influenza vaccine prior to inpatient discharge. DESIGN, SETTING, AND PARTICIPANTS This quality improvement study was conducted among children eligible for the seasonal influenza vaccine who were hospitalized in a tertiary pediatric health system providing care to more than half a million patients annually in 3 hospitals. The study used a sequential crossover design from control to intervention and compared hospitalizations in the intervention group (2019-2020 season with the use of an intervention order set) with concurrent controls (2019-2020 season without use of an intervention order set) and historical controls (2018-2019 season with use of an order set that underwent intervention during the 2019-2020 season). INTERVENTIONS A CDS intervention was developed through a user-centered design process, including (1) placing a default influenza vaccine order into admission order sets for eligible patients, (2) a script to offer the vaccine using a presumptive strategy, and (3) just-in-time education for clinicians addressing vaccine eligibility in the influenza order group with links to further reference material. The intervention was rolled out in a stepwise fashion during the 2019-2020 influenza season. MAIN OUTCOMES AND MEASURES Proportion of eligible hospitalizations in which 1 or more influenza vaccines were administered prior to discharge. RESULTS Among 17 740 hospitalizations (9295 boys [52%]), the mean (SD) age was 8.0 (6.0) years, and the patients were predominantly Black (n = 8943 [50%]) or White (n = 7559 [43%]) and mostly had public insurance (n = 11 274 [64%]). There were 10 997 hospitalizations eligible for the influenza vaccine in the 2019-2020 season. Of these, 5449 (50%) were in the intervention group, and 5548 (50%) were concurrent controls. There were 6743 eligible hospitalizations in 2018-2019 that served as historical controls. Vaccine administration rates were 31% (n = 1676) in the intervention group, 19% (n = 1051) in concurrent controls, and 14% (n = 912) in historical controls (P < .001). In adjusted analyses, the odds of receiving the influenza vaccine were 3.25 (95% CI, 2.94-3.59) times higher in the intervention group and 1.28 (95% CI, 1.15-1.42) times higher in concurrent controls than in historical controls. (continued) Key Points Question Is a clinical decision support (CDS) strategy associated with improved influenza vaccination rates before discharge among eligible hospitalized children? Findings In this quality improvement study, the combinination of a defaultchecked influenza vaccine order in admission order sets for eligible p...

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