Anesthesia and analgesia
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Anesthesia and analgesia · May 2020
Observational StudyIntraoperative Electronic Alerts Improve Compliance With National Quality Program Measure for Perioperative Temperature Management.
Reimbursement for anesthesia services has been shifting from a fee-for-service model to a value-based model that ties payment to quality metrics. The Centers for Medicare & Medicaid Service's (CMS) value-based payment program includes a quality measure for perioperative temperature management (Measure #424, Perioperative Temperature Management). Compliance may impose new challenges in clinical practice, data collection, and reporting. We investigated the impact of an electronic decision-support tool on adherence to this emerging standard. ⋯ Implementation of an intraoperative decision-support tool was associated with statistically significant improvement in the maintenance of normothermia in cases eligible for reporting to CMS. This led to improved compliance with Measure #424 and suggests that electronic alerts can help practices improve their performance and payment bonus eligibility.
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Anesthesia and analgesia · May 2020
Novel Imaging Revealing Inner Dynamics for Cardiovascular Waveform Analysis via Unsupervised Manifold Learning.
Cardiovascular waveforms contain information for clinical diagnosis. By learning and organizing the subtle change of waveform morphology from large amounts of raw waveform data, unsupervised manifold learning helps delineate a high-dimensional structure and display it as a novel 3-dimensional (3D) image. We hypothesize that the shape of this structure conveys clinically relevant inner dynamics information. ⋯ The DMap and the generated 3D image of ECG or ABP waveforms provides clinically relevant inner dynamics information. It provides clues of acute coronary syndrome diagnosis, shows clinical course in myocardial ischemic episode, and reveals underneath physiological mechanism under stress or vasodilators.
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Anesthesia and analgesia · May 2020
Motherhood and Anesthesiology: A Survey of the American Society of Anesthesiologists.
The proportion of women medical school graduates in the United States has grown substantially; however, representation of women in anesthesiology lags behind. We sought to investigate factors associated with women recommending against a career in anesthesiology due to obstacles related to motherhood. ⋯ In this study of 1827 women anesthesiologists, approximately 1 in 10 would counsel a student against a career in anesthesiology due to obstacles pertaining to motherhood, and this was associated with altering one's timing and number of children due to job demands. Further research is needed to understand how women's perception of a career in anesthesiology is related to factors influencing personal choices. Understanding women's perceptions of motherhood in anesthesiology may help leaders support career longevity and personal satisfaction in this growing cohort of anesthesiologists.
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Anesthesia and analgesia · May 2020
An Automated Algorithm Incorporating Poincaré Analysis Can Quantify the Severity of Opioid-Induced Ataxic Breathing.
Opioid-induced respiratory depression (OIRD) is traditionally recognized by assessment of respiratory rate, arterial oxygen saturation, end-tidal CO2, and mental status. Although an irregular or ataxic breathing pattern is widely recognized as a manifestation of opioid effects, there is no standardized method for assessing ataxic breathing severity. The purpose of this study was to explore using a machine-learning algorithm for quantifying the severity of opioid-induced ataxic breathing. We hypothesized that domain experts would have high interrater agreement with each other and that a machine-learning algorithm would have high interrater agreement with the domain experts for ataxic breathing severity assessment. ⋯ We concluded it may be feasible for a machine-learning algorithm to quantify ataxic breathing severity in a manner consistent with a panel of domain experts. This methodology may be helpful in conjunction with traditional measures to identify patients experiencing OIRD.