A Study of Workspace Design Characteristics Exemplified by Nurses’ Satisfaction Within Three Intensive Care Units in a University Hospital

Background: The critical conditions of intensive care patients require providing them with a higher acuity of care. Thus, it is essential to focus on critical care nurses and improve their work environment in a way that maximizes productivity, collaboration, satisfaction, and leads to improved patient care. Purpose: This study aims to explore the role the workplace layout design play in determining nurses’ satisfaction in three intensive care units (ICUs) at a university hospital. Method: A prospective, cross-sectional, single-center, survey-based design was employed in this study. Data were obtained, via a standardized questionnaire, from 36 morning shift nurses. The nurses’ self-reported satisfaction scores in three different ICUs with differing overall layouts, nursing station locations, and workplace design were statistically compared. Results: The study found that ICU 1 (private rooms, single corridor, central nursing station, close to supported services) had higher nursing satisfaction levels than ICUs 2 and 3 (open wards with separate service zones), F (2,34) = 5.054, p = .012. However, overall satisfaction was higher with the ICU 2 primary workspace design, possibly due to the perceived acoustic privacy in this configuration, F (2,34)= 4.492, p = .019. The ability of the ICU layout design to enhance teamwork and minimize traffic in patients care areas was found to be an important predictor of nurses’ satisfaction. The primary workspace design capacity to minimize congestion and the presence of large numbers of providers in a confined workplace might account for variation in nurses’ satisfaction. Conclusion: Physical environment variables in the ICU design may contribute to staff workplace satisfaction scores and may help in guiding informed choices regarding the future ICU design.

Characteristics associated with delays in decision to transfer injured patients

Introduction The regionalized nature of trauma care necessitates interfacility transfer which is vulnerable to delays given its complexity. Little is known about the interval of time a patient spends at the sending hospital prior to when the transfer is initiated—the “decision to transfer” time. This primary objective of the study was to explore the impact of patient, environmental, and institutional characteristics on decision to transfer time. Methods This was a retrospective cohort study of injured adult patients who underwent emergent interfacility transfer by a provincial critical care transport organization over a 31-month period. Quantile regression was used to evaluate the impact of patient, environmental, and institutional characteristics on the time to decision to transfer. Results A total of 1128 patients were included. The median decision to transfer time was 2.42 h and the median total transport time was 3.12 h. The following variables were associated with an increase in time to decision to transfer at the 90th percentile of time: age >75 (+2.47 h), age 66–75 (+3.70 h), age 56–65 (+1.20 h), transfer between 00:00 and 07:59 (+2.08 h), and transfer in the summer (+2.25 h). The following variables were associated with a decrease in time to decision to transfer at the 90th percentile of time: Glasgow Coma Scale 3–8 (−2.21 h), respiratory rate >30 (−2.01 h), sending site being a community hospital with <100 beds (−4.11 h), or the sending site being a nursing station (−5.66 h). Conclusion Time to decision to transfer was a sizable proportion of the patients interfacility transfer. Older patients were associated with a delay in decision to transfer as were patients transferred overnight and in the summer. These findings may be used to support the implementation of geriatric trauma triage guidelines and promote ongoing education and quality improvement initiatives to decrease delay.

431. SARS-CoV-2 Environmental Contamination in Hospitalized COVID-19 Patients’ Rooms

Background The correlation between SARS-CoV-2 RNA and infectious viral contamination of the hospital environment is poorly understood. Methods housed in a dedicated COVID-19 unit at an academic medical center. Environmental samples were taken within 24 hours of the first positive SARS-CoV-2 test (day 1) and again on days 3, 6, 10 and 14. Patients were excluded if samples were not obtained on days 1 and 3. Surface samples were obtained with flocked swabs pre-moistened with viral transport media from seven locations inside (bedrail, sink, medical prep area, room computer, exit door handle) and outside the room (nursing station computer). RNA extractions and RT-PCR were completed on all samples. RT-PCR positive samples were used to inoculate Vero E6 cells for 7 days and monitored for cytopathic effect (CPE). If CPE was observed, RT-PCR was used to confirm the presence of SARS-CoV-2. Results We enrolled 14 patients (Table 1, Patient Characteristics) between October 2020 and May 2021. A total of 243 individual samples were obtained – 97 on day 1, 98 on day 3, 34 on day 6, and 14 on day 10. Overall, 18 (7.4%) samples were positive via RT-PCR – 9 from bedrails (12.9%), 4 from sinks (11.4%), 4 from room computers (11.4%) and 1 from the exit door handle (2.9%). Notably, all medical prep and nursing station computer samples were negative (Figure 1). Of the 18 positive samples, 5 were from day 1, 10 on day 3, 1 on day 6 and 2 on day 10. Only one sample, obtained from the bedrails of a symptomatic patient with diarrhea and a fever on day 3, was culture-positive (Figure 2). Table 1. Patient Characteristics Figure 1. Proportion of RT-PCR Positive Samples by Sample Day and Location Figure 2. Cell cultures of negative control (left) and CPE positive sample (right) Conclusion Overall, the amount of environmental contamination of viable SARS-CoV-2 virus in rooms housing COVID-19 infected patients was low. As expected, more samples were considered contaminated via RT-PCR compared to cell culture, supporting the conclusion that the discovery of genetic material in the environment is not an indicator of contamination with live infectious virus. More studies including RT-PCR and viral cell culture assays are needed to determine the significance of discovering SARS-CoV-2 RNA versus infectious virus in the clinical environment. Disclosures David J. Weber, MD, MPH, PDI (Consultant)

Evaluating the Effective Factors of Hospital Rooms on Patients’ Recovery Using the Data Mining Method

Objectives: This study aims to investigate the effective environmental factors of hospital rooms in patients’ recovery through data mining techniques. Background: Previous studies have shown the positive effect of the interior environment of the hospitals on patients’ recovery. The methods of these studies were mainly based on the evidence and patients’ perception while hospital environments are associated with a large amount of data that make them an appropriate case for data mining studies. But data mining studies in hospitals mainly focused on medical and management purposes rather than evaluating the interior environment condition. Methods: We analyzed the hospital information system data of a hospital using Python programming language and some of its libraries. Preprocessing and eliminating the outliers, labeling and clustering of diseases, data visualization and analysis, final evaluation, and concluding were done using the knowledge discovery in databases process. Results: Pearson coefficient value for rooms’ area was .5 and, respectively, for the distance from the ward entrance and nursing station were .75 and .70. The χ2 values for the variables of room types, location, and occupation were 24.62, 18.98, and 21.53, respectively, and for the beds’ location was 0.12. Conclusions: The results confirmed the correlation of the length of stay with the room types, location, and occupation, distance from the nursing station and ward entrance and also showed a moderate correlation with the rooms’ area. However, no evidence was found about the relationship between the beds’ location in rooms and patients’ length of hospital stay.

Real Time Drip Monitoring System Using XKC-Y26-NPN

The Projects aims to Present a real time Monitoring System which will be used to monitor the Intravenous Fluid remaining in the IV fluid bottle and to provide with an indication such that a timely alarm or an indication can be generated which will then be attended by the hospital staff. The need of the project arises from the fact that often times due to negligence or the absence of required staff, the needs of the patient is overlooked which not only result in discomfort but also can cause infection and even blood backflow. The project utilizes XKC Y-26 N-P-N sensor to detect the overall level of the fluid left in the bottle and if it is found that the level has gone below certain stipulated level an alarm system gives indication to the nursing station. The project also combines the temperature and heart sensors as it is vital to monitor the two important parameters, then with assistance from Excel data streamer Module the data is sent to excel sheet so that it can be displayed in an interactive model. The project has the potential to be used in hospitals which will be beneficial given the adverse Covid related scenario and the entire setup can be used to detect not only the IV fluid level but also any other fluid and sensor that is given to the patient.

Linking Staff Cases in a Hospital COVID-19 Outbreak Using Electronic Tracking Data

Background: Significant outbreaks of SARS-CoV-2 infections have occurred in healthcare personnel (HCP). We used an electronic tracking system (ETS) as a tool to link staff cases of COVID-19 in place and time during a COVID-19 outbreak in a community hospital. Methods: We identified SARS-CoV-2 infection cases through surveillance, case investigation and contact tracing, and voluntary testing. For those wearing ETS badges (Centrak), data were reviewed for places occupied by the personnel during their incubation and infectious windows. Contacts beyond 15 minutes in the same location were considered close contacts. Results: Over 6 weeks (August 10–September 14, 2020), 35 HCPs tested positive for SARS-CoV-2 by NAAT testing. In total, 18 nurses and aides were clustered on 1 hospital unit, 7 cases occurred among respiratory therapists that visited that unit, and 10 occurred in other departments. Overall, 17 individuals wore ETS badges as part of hand hygiene monitoring. ETS data established potential transmission opportunities in 17 instances, all but 2 before symptom onset or positive test result. Contacts were most often (10 of 17) in common work areas (nursing stations), with a median time of 45 minutes (IQR, 21–137). Contacts occurred within and between departments. A few COVID-19 patients were cared for in this location at the time of the outbreak. However, we did not detect HCP-to-patient nor patient-to-HCP transmission. Conclusions: Significant HCP-to-HCP transmission occurred during this outbreak based on ETS location. These events often occurred in shared work areas such as the nursing station in addition to break areas noted in other reports. ETS systems, installed for other purposes, can serve to reinforce standard epidemiology.Funding: NoDisclosures: None

Improving vaccine administration in patients with solid malignancies in the outpatient setting.

194 Background: Pneumococcal and influenza vaccinations are recommended for all patients with any malignancy in accordance with the Infectious Disease Society of America. Patients undergoing chemotherapy for solid tumors have a 40-50 fold higher risk for the development of invasive pneumococcal disease compared to healthy adults with a case fatality rate of 35% and should receive the sequential 13-valent pneumococcal conjugate vaccine (PCV13) and 23-valent pneumococcal polysaccharide vaccine (PPSV23). In the outpatient setting, lack of provider knowledge, complexity of the pneumococcal vaccine regimen and disruption in work-flow of a busy clinic can lead to low rates of administration. Towards this end, we conducted a quality project to improve administration of both pneumococcal and influenza vaccines by at least 50% at one of our outpatient oncology clinics at Montefiore Medical Center in Bronx, NY during a 4 month period. Methods: We first provided provider and nursing education with regard to safety and efficacy of the vaccines in both the clinic as well as the infusion setting. Nurses were then prompted to screen patients and offer the vaccines during intake prior to all infusions and clinic visits. We created bulk orders which allowed nurses greater control of releasing vaccine orders previously entered by the director of the clinic. We also posted “cheat-sheets” on optimal timing, safety and sequence of administration of the vaccines in every patient room and nursing station. After our first cycle, we identified that there was a delay in work-flow in the outpatient clinic with delivery of the vaccines to the clinic from the pharmacy. We therefore obtained a secure vaccine fridge that was placed at the nursing station, which allowed nurses easy access to the vaccines. Results: When vaccine administration during the 2018-2019 influenza season was compared to the 2019-2020 influenza season, we found that these interventions improved the administration of the influenza vaccine by 70%. There was a dramatic increase in the number of PCV-13 vaccines administered by 350% (more than 5-fold) and increase in PPVS-23 by 12.5%. No immediate adverse reactions during this cycle were reported to our nurse manager. Conclusions: A simple intervention of improved work-flow of vaccine administration and increased education of providers and nurses translated to a dramatic improvement in the administration of influenza and PCV-13 vaccines in a busy outpatient oncology clinic.

489. A Case-Control Approach to an Outbreak of SARS-CoV-2 on an Acute Stroke Unit in the U.S

Background Detailed descriptions of hospital-acquired SARS-CoV-2 infections and transmission chains in healthcare settings are crucial to controlling outbreaks and improving patient safety. However, such reports are scarce. We sought to determine origins and factors associated with nosocomial transmission of SARS-CoV-2 in a 528-bed teaching hospital in Western New York. Methods The index patient, who had mental illness, wandered throughout the ward, would not wear a facemask, and was often kept seated at the nursing station, developed COVID-19 on day- 22 of hospitalization. A case-control approach was used, wherein all patients, staff, and 128 randomly selected environmental surfaces on the outbreak unit (case), and randomly selected patients, staff, and environmental surfaces on designated COVID-19 and non-COVID-19 units (control), were tested for SARS-COV-2 by RT-PCR and IgG SARS-COV-2 antibodies (SAR-Ab). Compliance with hand hygiene (HH) and COVID-specific personal protective equipment (PPE) was assessed. Results 145 staff and 26 patients were potentially exposed resulting in 25 secondary cases (14 staff and 11 patients). 4/14 (29%) of the staff and 7/11 (64%) of the patients who tested positive, and later became ill, were asymptomatic at the time of testing (Figures 1–2). There was no difference in mean cycle threshold for SARS-COV-2 gene targets between asymptomatic and symptomatic individuals. 0/32 randomly selected staff from the positive and negative control wards tested positive. PPE compliance based on 354 observations was not significantly different between wards. Environmental surface contamination with SARS-COV-2 RNA was not different between outbreak and control wards. Mean monthly HH compliance, based on 20,146 observations, was lower on the outbreak ward (p &lt; 0.006) (Figure 3). 142 staff volunteered for serologic testing. The proportion staff with detectable SAR-Ab was higher on the outbreak ward (OR 3.78: CI 1.01–14.25). Figure 1 Figure 2 Figure 3 Conclusion The risk of staff exposure was higher in an outbreak setting than on a dedicated COVID-19 unit (Figure 4). Noncompliant patient behavior, decreased hand hygiene, and pre-symptomatic transmission can contribute to nosocomial spread and are important considerations for ongoing infection control efforts. Figure 4 Disclosures All Authors: No reported disclosures