Background: Intubation is both an important outcome measure along the spectrum of all respiratory illnesses and a marker of disease severity. Time of intubation (TOI) is an important point to identify in the electronic health record (EHR) as it allows researchers to study the association of pre and post-intubation variables with mortality and other relevant patient-centered outcomes. The purpose of this study is to develop and validate an improved reference standard for determining TOI across the emergency, internal medicine and critical care settings of a large health system during a time of resource strain, the COVID-19 pandemic.

Methods: A retrospective study of all admitted internal medicine patients who tested positive for SARS-CoV-2 by nasopharyngeal PCR, 18 years or older, intubated with ARDS, within 12 hospitals between March 1, 2020 and April 30, 2020, to determine whether a new search query (Ti) would more accurately identify the correct TOI compared to a previous query using only ventilator parameters (Tv). First, charts were manually reviewed to determine TOI and the data points that most accurately identified this time point were recorded. Next, the effect of Ti on peri-intubation patient parameters, compared to Tv, was evaluated.

Results: The following surrogates were found to be the most accurate in retrospectively identifying TOI in the EHR and, therefore, were used to construct Ti: TOI authored in an endotracheal intubation procedure note (from the ED or as an inpatient); “Start Time” from the mechanical ventilation record; time of first documentation of mechanical ventilation parameters in the mechanical ventilation record; time of first completed injection of medications used for intubation such as etomidate, succinylcholine, cisatracurium, rocuronium, vecuronium; time of initiation of continuous infusion propofol or fentanyl (minimum duration of 5 minutes); and documentation in nursing ED and inpatient notes regarding use of “ventilator” in the oxygen delivery method for each patient. Ti identified an earlier TOI for 84.8% (n=1,666) of cases with a mean (SD) of 3.5 hours (15.5), resulting in alternate values for: PaO2 in 18.4% of patients [mean 43.95 mmHg (54.24)]; PaO2/FiO2 in 17.8% of patients [mean 48.29 (69.81)], and SpO2/FiO2 in 62.7% [mean 16.75 (34.14)], using the absolute difference in mean values within the first four hours of intubation. Differences in PaO2/FiO2 using Ti versus Tv resulted in the reclassification of 7.3% of patients into different ARDS severity categories.

Conclusions: In addition to identifying a more accurate time of intubation, our new query allows for more accurate analyses of peri-intubation changes in patient parameters. The logic behind Ti can serve as a guiding template for other institutions to follow for identifying time of intubation, using their own unique EHR. Further, our logic works across multiple hospital settings- ED, medical wards and ICUs- during a time of significant resource strain, the COVID-19 pandemic.

IMAGE 1: Components used to create Ti and a summary of results after Ti was deployed, compared to Tv

IMAGE 2: Summary of impact of Ti on the mean of all recorded values of different variables within 4 hours after intubation (|∆ ̅X|).