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1.
American Journal of Respiratory and Critical Care Medicine ; 205(1), 2022.
Article in English | EMBASE | ID: covidwho-1927769

ABSTRACT

RATIONALE During this unprecedented COVID-19 pandemic intensive care units (ICU) need efficient ways to deliver patient care. As hospital workload increases, so does the risk for medical error and delays in care. A systematic initial approach and timely documentation is important to provide an efficient and thorough assessment and to facilitate communication within the interprofessional team. We aimed to evaluate documentation of key assessment elements at ICU admission. METHODS The Checklist for Early Recognition and Treatment of Acute Illness and Injury (CERTAIN) is a validated tool that reduces errors in the initial assessment and ongoing care of critically ill patients. With Mayo IRB approval, electronic medical records (EMR) of a convenience sample of ICU patients admitted to medical, surgical and mixed ICUs at our institution during October 2021 were reviewed to assess documentation of the CERTAIN primary survey, including assessment of airway, breathing, cardiac, disability, and exposure (ABCDE);vital signs;intravenous access;point of care labs and ultrasound (POCUS);differential diagnosis;and plan by systems including code status and goals of care. Patients admitted for post-operative monitoring and those who declined the use of their medical records for research were excluded. RESULTS Forty patient EMRs were reviewed. Median age was 65 years, 47.5% were female, and respiratory failure was the most common reason for ICU admission. Documented frequency of airway assessment was 32.5%, breathing 92.5%, cardiac 70%, disability 42.5%, and exposure 85%. Thorough vital sign review including temperature was documented in 47.5% of ICU admissions. A comment or plan for intravenous or intraosseous access was documented in 75% of patients. Completion or review of same day point of care labs was documented in 55%. Cardiac POCUS was documented in 9 of 40 ICU admissions. No patients had documented lung or abdominal POCUS. 80% had a differential diagnosis documented as part of their initial assessment. All patients had a complete plan by systems. 85% of patients had a documented code status, although it was unclear if it had been actively re-addressed on ICU admission. CONCLUSION EMR documentation of key findings at the time of ICU admission leaves significant opportunities for improvement, with particularly large gaps in primary survey and POCUS assessment. The results of this study, combined with ongoing direct observation of ICU admissions using the CERTAIN checklist, will inform future recommendations to improve the performance and documentation of key assessment elements during the “golden first hour” of ICU admission.

3.
American Journal of Respiratory and Critical Care Medicine ; 203(9):2, 2021.
Article in English | Web of Science | ID: covidwho-1407513
4.
American Journal of Respiratory and Critical Care Medicine ; 203(9):2, 2021.
Article in English | Web of Science | ID: covidwho-1407512
5.
American Journal of Respiratory and Critical Care Medicine ; 203(9), 2021.
Article in English | EMBASE | ID: covidwho-1277783

ABSTRACT

Background: Peak flow testing is a common procedure performed in ambulatory care. There are currently no data regarding aerosol generation during this procedure. We measured small particle concentrations generated during peak flow testing. Several peak flow devices were compared to assess for differences in aerosol generation. The amount of aerosol generation should objectively inform infection control and mitigation strategies during the COVID-19 pandemic. Methods: Five healthy volunteers performed peak flow maneuvers in a particle free laboratory space. Two devices continuously sampled the ambient air during the procedure. One device can detect ultrafine particles from 0.02 - 1 micron, while the second device can detect particles of size 0.3, 0.5, 1.0, 2.0, 5.0, and 10 microns. Five different peak flow meters were compared to ambient baseline during masked and unmasked tidal breathing. Results: Ultrafine particles (0.02 - 1 micron) were generated during peak flow rate measurement. Ultrafine particle mean concentration was lowest with Respironics peak flow meter (1.25±0.47 particles/cc) and similar between Philips (3.06±1.22), Clement Clarke (3.55±1.22 particles/cc), Respironics low range (3.50±1.52 particles/cc), and Monaghan (3.78±1.31 particles/cc) peak flow meters. Although ultrafine particle mean concentration increased during peak flow measurements compared ambient baseline during masked (0.22±0.29 particles/cc) and unmasked (0.15±0.18 particles/cc) tidal breathing, these differences were small and remained well below ambient PFT room particle concentrations (89.9±8.95 particles/cc). Conclusions: In this study, we were able to establish the feasibility of measuring small particle production after peak flow testing. Our study shows that ultrafine particles are generated during peak flow measurement. Although all peak flow meters demonstrated increased mean particle concentration, differences were small compared to the mean particle concentrations found in the ambient clinical environment. Outpatient practices should be aware of the potential risk of these findings and take appropriate infection control precautions.

6.
American Journal of Respiratory and Critical Care Medicine ; 203(9), 2021.
Article in English | EMBASE | ID: covidwho-1277466

ABSTRACT

Objective: Virtual learning experiences have become widely used during the ongoing COVID-19 global crisis. Given its cost-effectiveness, accessibility, and flexibility, remote training experiences are likely to assume a permanent and expanded role in medical education and quality improvement initiatives. However, little is known about how best to measure the effectiveness of remote training interventions. The Checklist for Early Recognition and Treatment of Acute Illness and Injury (CERTAIN) is an established critical care quality improvement program with evidence of improved care processes and patient outcomes in an international quality improvement trial. Our aim was to develop a structured implementation and longitudinal evaluation framework that measures the complex contributors to the impact of this remote training program, including incorporation into processes of care and sustainment over time. Methods: We convened an international topic review group that included individuals with diversity in clinical expertise, nationality, and experience in medical education, quality improvement, implementation science, and research methodology. We recruited individuals with experience designing and participating in various medical remote training programs, including teleconferences, tele-consults, online video/chat platforms, and virtual simulation classrooms. Through a series of facilitated discussions, we directed the group to develop a conceptual framework to guide the development of remote learning programs and accompanying evaluation tools to measure their impact. Results: The review group members included education experts and continuing medical education participants from China and the United States with practice backgrounds in Critical Care, Internal Medicine, Anesthesiology and Emergency Medicine. The group developed a conceptual framework based on the CIPP (context-input-process-product) quality evaluation model. The framework includes three phases: before, during, and after the remote training. The proposed quantitative and qualitative evaluation tools blend the Proctor taxonomy, an expansion of the popular RE-AIM framework used to categorize implementation outcomes, to include early (i.e. acceptability, appropriateness, feasibility), mid (i.e. adoptions, fidelity), and late (i.e. sustainability) stage outcomes to provide a more complete understanding of the implementation process and facilitate generalization of our findings. Elements of the Logic Model were also used to guide the program development process. Conclusions: We propose a dynamic, longitudinal implementation evaluation framework that has sufficient rigor and flexibility to meet the needs of the existing and emerging remote medical training programs in global practice settings. The outcomes from these mixed-methods analyses will provide a robust toolbox to guide the design, delivery, implementation, and sustainment of remote medical educational programs.

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