INTRODUCTION/HYPOTHESIS: Complications of Mechanical Ventilation (MV) are well-described and related to duration of exposure to the intervention. A protocolized approach to MV liberation is recommended by Critical Care society guidelines and avoidance of delay to MV liberation was recently selected as one of five 2021 Choosing Wisely® for Critical Care recommendations. Baseline data in our tertiary hospital Medical Intensive Care Unit (MICU) showed that the average time of extubation was 1:30PM, with only 16% of patients extubated in the morning before 10AM. These findings prompted a Quality Improvement (QI) initiative aimed at achieving earlier extubation of eligible patients. METHODS: A multidisciplinary QI project team was formed, with representation from attending physicians, respiratory therapists, nurses, and physicians-in-training. A SMART Aim was created in September of 2020, with a goal set for the rate of morning (6AM to 10AM) extubation for eligible patients to increase from 16% to 20% or greater by June of 2021. Countermeasures were developed based on root cause analysis and targeted early morning initiation of Spontaneous Breathing Trials (SBTs), limiting overnight sedation, and staff education on hospital SBT and extubation protocols. A novel telemedicine Respiratory Therapy service, initially formed in response to the COVID-19 pandemic, was leveraged to ensure early SBTs and sedation minimization. PDSA cycles were performed to optimize educational and telemedicine countermeasures. RESULTS: 334 patients were extubated during the study period. The cumulative rate of extubation between 6AM - 10AM increased from 16% in the pre-intervention period to 27% in the post-intervention period and an upward shift in the run chart baseline was observed. Reintubation rate within 48 hours was monitored as a balancing measure and did not increase in the post-intervention period. There was no shift in median ICU length of stay or median MV duration in the postintervention period. CONCLUSIONS: A multidisciplinary QI initiative was able to increase the rate of morning extubations in a tertiary hospital MICU. The initiative demonstrated the value of a novel telemedicine Respiratory Therapy service to ensure adherence to best practices and achieve improvements in quality of care.

A 24/7 telemedicine respiratory therapist (eRT) service was set up as part of the established University of Pennsylvania teleICU (PENN E-LERT®) service during the COVID-19 pandemic, serving five hospitals and 320 critical care beds to deliver effective remote care in lieu of a unit-based RT. The eRT interventions were components of an evidence-based care bundle and included ventilator liberation protocols, low tidal volume protocols, tube patency, and an extubation checklist. In addition, the proactive rounding of patients, including ventilator checks, was included. A standardized data collection sheet was used to facilitate the review of medical records, direct audio–visual inspection, or direct interactions with staff. In May 2020, a total of 1548 interventions took place, 93.86% of which were coded as “routine” based on established workflows, 4.71% as “urgent”, 0.26% “emergent”, and 1.17% were missing descriptors. Based on the number of coded interventions, we tracked the number of COVID-19 patients in the system. The average intervention took 6.1 ± 3.79 min. In 16% of all the interactions, no communication with the bedside team took place. The eRT connected with the in-house respiratory therapist (RT) in 66.6% of all the interventions, followed by house staff (9.8%), advanced practice providers (APP; 2.8%), and RN (2.6%). Most of the interaction took place over the telephone (88%), secure text message (16%), or audio-video telemedicine ICU platform (1.7%). A total of 5115 minutes were spent on tasks that a bedside clinician would have otherwise executed, reducing their exposure to COVID-19. The eRT service was instrumental in several emergent and urgent critical interventions. This study shows that an eRT service can support the bedside RT providers, effectively monitor best practice bundles, and carry out patient–ventilator assessments. It was effective in certain emergent situations and reduced the exposure of RTs to COVID-19. We plan to continue the service as part of an integrated RT service and hope to provide a framework for developing similar services in other facilities.

Background: During the COVID-19 pandemic, we initiated a new clinical rotation for respiratory care students in a virtual ICU (eICU). During this rotation, students experienced an increase in their baseline knowledge of telemedicine and mechanical ventilation. We hypothesized that qualitative feedback of the clinical rotations would reflect a positive learning experience. Methods: Students from two universities completed clinical rotations in a tele-ICU as a part of an IRB-approved observational study. They completed two, four-hour rotations with a telemedicine RT preceptor (eRT) with experience in the eICU. Students were involved in remote patient assessment, review and interpretation of ventilator waveforms, blood gases, and chest x-rays. Students received an introduction to lung protective ventilation, spontaneous breathing, and broncho-pulmonary hygiene protocols. At the end of the second day of the clinical rotation, students completed a survey which included qualitative questions regarding their experience. Results: In their comments, students stated eRTs provided guidance and created a comfortable learning environment that students would recommend to others. Interaction with tele-ICU RNs (eRN) was described as friendly, knowledgeable, and helpful. Students noted the high level of teamwork in the eICU and that they observed quality patient care provided. Students stated that interactions with tele-ICU MDs were educational; however, forty percent of students reported not interacting with eMDs. While some of the students did not interact with staff in the physical ICU, others noted that interactions via telecommunication platforms were positive and friendly. The biggest difference noted between this rotation and in-person rotations was that it is not hands on; however, students stated they were able to focus on technology and learning about ventilator waveforms and mechanics. When asked what it takes to be an effective eRT, a willingness to learn and be involved was described. Students felt it was important to be knowledgeable about technology, modes of mechanical ventilation, and waveforms. Additionally, the students noted it was important to be knowledgeable about diseases and patient-ventilator synchrony. Conclusions: Students’ experience in a virtual ICU was overwhelmingly positive, providing new perspectives on patient care.

Background: Clinical rotations are essential to respiratory therapy students (RTS) learning objectives. The COVID-19 pandemic profoundly affected RTS education by limiting their bedside exposure, as they were prohibited from caring for COVID-19 patients. Here we describe a clinical rotation at a tele-ICU (eICU) which gave RTS access to COVID-19 patients. Our goal was to increase their knowledge of the disease process to better prepare them for the workforce. Methods: Students from two universities completed clinical rotations in a tele-ICU as a part of an IRB-approved observational study. They completed two, four-hour rotations with an experienced telemedicine RT preceptor (eRT) in the eICU. Data collection occurred from February 2021 – May 2021. Along with their preceptors, RTS rounded on 320 ICU beds across five hospitals. Primary objectives of the clinical rotation included performing remote patient assessments, interpreting ventilator waveforms, arterial blood gases, and chest x-rays. RTS received education on lung protective ventilation and spontaneous breathing protocols. During ventilator rounds, RTS filled out demographic surveys to identify the complexity and diversity of the patient population. Results: Thirty-three RTS included in the study rounded on 370 patients during their remote clinical rotations. Of the patients RTS interacted with, 57% (n = 211) identified as male. Mean age of the population was 52.5 ± 18. Racial make-up closely resembled the diversity in the region with 39% (n = 145) Black and 50% (n = 183) white patients. Ninety-two percent of the patients were mechanically ventilated and RTS completed 239 patient-ventilator assessments. The primary disease processes of patients seen were ARDS (n = 178) and COVID-19 (n = 145). In patients with ARDS, 36% (n = 65) required follow-up due to issues related to adherence to protocol. Volume-targeted modes of ventilation were most commonly used, 47% (n = 175). Patient interventions included 73 instances of worsening symptoms on mechanically ventilated patients. Twenty-eight patients were deemed high risk airways which required increased surveillance. Conclusions: During this remote clinical rotation, RTS had the opportunity to interact with and complete assessments on patients diagnosed with COVID-19. This rotation prepared RTS to care for a diverse patient population via the eICU and increase their knowledge and experience with COVID-19 patients despite a lack of traditional hands-on experience.

Background: Pennsylvania Respiratory Research Collaborative (PRRC) convened a sub-group to study quality metrics monitored by respiratory departments in Pennsylvania healthcare facilities. The aim was to understand quality metrics tracked by and involving respiratory care departments as the first step in developing state-wide quality benchmarks. Methods: A survey focusing on quality metrics monitored by respiratory care departments was developed and sent to supervisors, managers, and directors within the state of Pennsylvania between April 25–May 31, 2021. In collaboration with PSRC Executive Director and Board, the survey committee provided the survey link via email to the PSRC listserv consisting of respiratory care leaders. Reminder emails were sent two weeks after the initial email invite. Respondents were asked not to complete the survey more than once. The survey was anonymous and received IRB exempt approval. Results: One hundred and ten leaders received the survey with a response rate of 64.54% (71/110). Of these respondents, 88.73% participate in a quality improvement process that includes respiratory care in multidisciplinary initiatives. Centers by hospital category included academic teaching facility (38.03%), community hospital (52.11%), acute rehabilitation (5.63%), critical access hospital (1.40%), and cancer specialty (1.40%). Distribution of hospital size included 600 beds (9.86%). Most common quality measures were ventilator-associated infections, medication barcode scanning, and COPD/PNA readmissions (Table 1). Quality metrics were shared with respiratory care staff most commonly during staff meetings (Figure 1). In addition to departmental information sharing, metrics are also reported to hospital administration as departmental report outs, operations, quality, and safety committees. The following metrics were listed the most number of times to be reported state-wide among PA respiratory care departments: ventilator-associated conditions, COPD readmission rates, unplanned extubations, and ventilator LOS. Conclusions: A large number of respondents are tracking similar metrics and reporting them internally. A statewide or nationwide reporting and benchmarking system managed by respiratory care will benefit Respiratory Departments as well as illustrating value of the profession. More study is needed to identify whether these findings are consistent throughout the country.

Background: Clinical rotations are foundational to student learning in respiratory therapy (RT) school. Telemedicine emerged as a means for managing critical care patients during the COVID-19 pandemic. We hypothesized that a clinical rotation at a tele-ICU would increase student knowledge of mechanical ventilation, telemedicine, and COVID-19. Methods: Students from two universities completed clinical rotations in a tele-ICU as a part of an IRB-approved observational study. Two, four-hour shifts were spent with an RT preceptor. RTs rounded on 320 ICU beds at 5 hospitals. Patient assessments were completed at the request of RTs in the ICUs and clinical emergencies were addressed in real time via remote monitoring. Students completed a pre-rotation survey assessing their confidence evaluating and managing mechanical ventilation, experience with telemedicine and technology, ARDS and COVID-19 patients. At the end of the rotation, students completed a second survey assessing knowledge of the same concepts. Wilcoxon signed ranks was applied to compare pre- and post-clinical rotation self-confidence surveys (Likert scale 1 – 10). Data are reported as median (IQR). P Results: Thirty-three out of 37 students (89%) completed surveys pre- and post-clinical rotations. Of those, 67% (n = 22) were female. Fifty-five percent of students reported prior knowledge of telemedicine, while 52% had observed interactions with the tele-ICU in previous clinical rotations. Mean self-confidence in mechanical ventilation, assessing waveforms, and knowledge of ARDS increased after the clinical rotation (pre-rotation 7.0–8.0 [5.0–9.0], post-rotation 8.7–9.5 [8.0–10]; P = 0.001). Similarly, reported knowledge related to spontaneous breathing protocols, lung protective ventilation, patient care planning, and use of data collection tools increased from the beginning to the end of the clinical rotation (pre-rotation 6.5– 8.3 [5–9.5], post-rotation 8.8–9.9 [7.5–10]; P = 0.001– 0.009). Student confidence in interprofessional communication increased from 8.5 [6.9–9.8] to 9.5 [7.8–10] (P = 0.03). Overall, the largest change was students’ ability to assess COVID-19 patients (pre-rotation 5 [1.2–6.8], post-rotation 8 [5.9–10]; P = 0.001). Conclusions: Students’ knowledge and skills in assessing patients via remote monitoring increased in a tele-ICU clinical rotation. Knowledge related to COVID-19 also increased statistically significantly.

Aim: Determine changes in rapid response team (RRT) activations and describe institutional adaptations made during a surge in hospitalizations for coronavirus disease 2019 (COVID-19). Methods: Using prospectively collected data, we compared characteristics of RRT calls at our academic hospital from March 7 through May 31, 2020 (COVID-19 era) versus those from January 1 through March 6, 2020 (pre-COVID-19 era). We used negative binomial regression to test differences in RRT activation rates normalized to floor (non-ICU) inpatient census between pre-COVID-19 and COVID-19 eras, including the sub-era of rapid COVID-19 census surge and plateau (March 28 through May 2, 2020). Results: RRT activations for respiratory distress rose substantially during the rapid COVID-19 surge and plateau (2.38 (95% CI 1.39-3.36) activations per 1000 floor patient-days v. 1.27 (0.82-1.71) during the pre-COVID-19 era; p=0.02); all-cause RRT rates were not significantly different (5.40 (95% CI 3.94-6.85) v. 4.83 (3.86-5.80) activations per 1000 floor patient-days, respectively; p=0.52). Throughout the COVID-19 era, respiratory distress accounted for a higher percentage of RRT activations in COVID-19 versus non-COVID-19 patients (57% vs. 28%, respectively; p=0.001). During the surge, we adapted RRT guidelines to reduce in-room personnel and standardize personal protective equipment based on COVID-19 status and risk to providers, created decision-support pathways for respiratory emergencies that accounted for COVID-19 status uncertainty, and expanded critical care consultative support to floor teams. Conclusion: Increased frequency and complexity of RRT activations for respiratory distress during the COVID-19 surge prompted the creation of clinical tools and strategies that could be applied to other hospitals.

In a large health system in the United States, investigators examined whether mortality, receipt of mechanical ventilation, and patient acuity changed over time among adult patients with COVID-19–related critical illness admitted to intensive care units.

Background: The Joint Commission National Patient Safety Goal 6.01.01 requires hospitals to, 9Make improvements to ensure that alarms on medical equipment are heard and responded to on time.9 Our department policy states, 9Alarms are set to ensure safe delivery of the mechanical ventilation to the patient, alert caregivers to possible changes in patient condition, ensure proper functionality of the ventilator, and to reduce unnecessary alarms to minimize staff alarm fatigue without risk to patient safety. 9 Past abstracts have described inappropriately set alarms, while some organizations are attempting to benchmark ventilator alarm settings. As a quality assurance project, we sought to determine staff adherence to department policy. Methods: Data collected from fifty ventilators included: high peak inspiratory pressure, high minute ventilation, low minute ventilation, high respiratory rate, high tidal volume, and low tidal volume alarms. Data were compared to our departmental policy by finding the mean and standard deviation for each parameter. Results: We found that clinicians were grossly non-compliant with ventilator alarm settings. When setting high tidal volume, 4% of alarm settings were complaint to our policy. For low tidal volume, low minute ventilation, and high respiratory rate the compliance rates were 28%. Two percent of high minute ventilation alarms were set according to policy. High peak inspiratory alarm settings were set to policy on 22% of the ventilators. Mean difference between high tidal volume alarm setting and the policy was 299.75 mL ± 358.78 mL. A mean divergence from policy of 138.72 mL ± 163.35 mL was found in low tidal volume settings. High minute ventilation alarm means were low by 6.15 L/min ± 2.97 L/min. Conversely, low minute ventilation alarms were set too high, with a mean of 1.49 L/min ± 2.67 L/min. Mean respiratory rate settings were too high by 6.4 breaths/min ± 7.22 breaths/min. Finally, high peak inspiratory pressure alarms had a mean setting 8.76 cm H2O ± 7.15 cm H2O higher than stated in departmental policy. Conclusions: Although benchmarking ventilator alarm data is worthwhile it may be challenging to achieve. One theory for why clinicians did not adhere to our policy is that it may be too conservative. Future research may indicate why clinicians deviate from standards and how best to align ourselves with stated policies. Based on our findings we are devising a plan to meet the Joint Commission standard.

Background: At the Hospital of the University of Pennsylvania, respiratory therapists (RTs) are required to assess for spontaneous breathing trial (SBT) readiness on all ventilated patients every morning. The RTs manually assess for SBT readiness by gathering different parameters from the electronic health record (EHR). This can become somewhat burdensome in a busy ICU. In addition patients may be ready for SBT at any time throughout the day and more frequent readiness assessments could expedite the liberation process. Our committee looked to leverage the EHR to create a novel program that will continuously screen EHR elements to assist the care team with ongoing SBT readiness assessments. Methods: A novel computer program (called the ABC App) was created, in collaboration with the Data Science team and Penn Center for Innovation to continuously screen all vented patients in the MICU by extracting data from the EHR. The information is then displayed in real-time on an ICU Dashboard, with green indicating SBT ready and red for Not SBT ready. When patients meet criteria for SBT readiness, the system alerts the RT via text message to do an SBT. If the patient is over sedated (based on RASS) the RN and providers are also prompted via text alert to address sedation. For patients not meeting readiness criteria, the parameters limiting weaning (ie, FIO2 or PEEP) are displayed on the dashboard with icons to nudge clinicians to consider weaning that parameter. The ICU dashboard and alerts were implemented in the HUP MICU for a 6-month pilot assessment. Results: Duration of ventilation decreased from 4.6 to 4.0 d. ICU LOS decreased by 1.2 d and hospital LOS dropped by 1.4 d. Conclusions: A real-time electronic dashboard and alert system affected a reduction in duration of mechanical ventilation and ICU length of stay. The RTs have found the text alerts and dashboard to be highly beneficial in the ICU with many competing priorities. With these positive results, we plan to expand the ICU dashboard and text alerting system to all ICUs in the Penn Medicine Health System.