This cohort study compares 30-day mortality and inpatient intensive care unit (ICU) admissions before and after the implementation of a novel emergency department–based ICU.
The high rate of relevant sentences is desirable, given that clinicians' lack of time is one of the main barriers to using knowledge resources at the point of care. Sentence rank was not significantly associated with relevancy, possibly due to most sentences being highly relevant. Sentences located closer to the end of the abstract and sentences with treatment and comparative predications were likely to be conclusive sentences. Our proposed technical approach to helping clinicians meet their information needs is promising. The approach can be extended for other knowledge resources and information need types.
doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.
Background: COVID-19 has led to an unprecedented strain on health care facilities across the United States. Accurately identifying patients at an increased risk of deterioration may help hospitals manage their resources while improving the quality of patient care. Here, we present the results of an analytical model, Predicting Intensive Care Transfers and Other Unforeseen Events (PICTURE), to identify patients at high risk for imminent intensive care unit transfer, respiratory failure, or death, with the intention to improve the prediction of deterioration due to COVID-19.Objective: This study aims to validate the PICTURE model's ability to predict unexpected deterioration in general ward and COVID-19 patients, and to compare its performance with the Epic Deterioration Index (EDI), an existing model that has recently been assessed for use in patients with COVID-19.
Methods:The PICTURE model was trained and validated on a cohort of hospitalized non-COVID-19 patients using electronic health record data from 2014 to 2018. It was then applied to two holdout test sets: non-COVID-19 patients from 2019 and patients testing positive for COVID-19 in 2020. PICTURE results were aligned to EDI and NEWS scores for head-to-head comparison via area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve. We compared the models' ability to predict an adverse event (defined as intensive care unit transfer, mechanical ventilation use, or death). Shapley values were used to provide explanations for PICTURE predictions.
OBJECTIVES
To estimate the proportion of older adults in the emergency department (ED) who are willing and able to use a tablet computer to answer questions.
DESIGN
Prospective, ED-based cross-sectional study.
SETTING
Two U.S. academic EDs.
PARTICIPANTS
Individuals aged 65 and older.
MEASUREMENTS
As part of screening for another study, potential study participants were asked whether they would be willing to use a tablet computer to answer eight questions instead of answering questions orally. A custom user interface optimized for older adults was used. Trained research assistants observed study participants as they used the tablets. Ability to use the tablet was assessed based on need for assistance and number of questions answered correctly.
RESULTS
Of 365 individuals approached, 248 (68%) were willing to answer screening questions, 121 of these (49%) were willing to use a tablet computer; of these, 91 (75%) were able to answer at least six questions correctly, and 35 (29%) did not require assistance. Only 14 (12%) were able to answer all eight questions correctly without assistance. Individuals aged 65 to 74 and those reporting use of a touchscreen device at least weekly were more likely to be willing and able to use the tablet computer. Of individuals with no or mild cognitive impairment, the percentage willing to use the tablet was 45%, and the percentage answering all questions correctly was 32%.
CONCLUSION
Approximately half of this sample of older adults in the ED was willing to provide information using a tablet computer, but only a small minority of these were able to enter all information correctly without assistance. Tablet computers may provide an efficient means of collecting clinical information from some older adults in the ED, but at present, it will be ineffective for a significant portion of this population.
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