Variation in Intraoperative Opioid Administration by Patient, Clinician, and Hospital Contribution.

Importance: The opioid crisis has led to scrutiny of opioid exposures before and after surgical procedures. However, the extent of intraoperative opioid variation and the sources and contributing factors associated with it are unclear.

Objective: To analyze attributable variance of intraoperative opioid administration for patient-, clinician-, and hospital-level factors across surgical and analgesic categories.

Classification of Current Procedural Terminology Codes from Electronic Health Record Data Using Machine Learning.

Background: Accurate anesthesiology procedure code data are essential to quality improvement, research, and reimbursement tasks within anesthesiology practices. Advanced data science techniques, including machine learning and natural language processing, offer opportunities to develop classification tools for Current Procedural Terminology codes across anesthesia procedures.

Methods: Models were created using a Train/Test dataset including 1,164,343 procedures from 16 academic and private hospitals.

Alerting thresholds for the prevention of intraoperative awareness with explicit recall: a secondary analysis of the Michigan Awareness Control Study.

Background: Intraoperative awareness with explicit recall is a potentially devastating complication of surgery that has been attributed to low anaesthetic concentrations in the vast majority of cases. Past studies have proposed the determination of an adequate dose for general anaesthetics that could be used to alert providers of potentially insufficient anaesthesia. However, there have been no systematic analyses of appropriate thresholds to develop population-based alerting algorithms for preventing intraoperative awareness.

Prevention of intraoperative awareness with explicit recall in an unselected surgical population: a randomized comparative effectiveness trial.

Background: Intraoperative awareness with explicit recall occurs in approximately 0.15% of all surgical cases. Efficacy trials based on the Bispectral Index® (BIS) monitor (Covidien, Boulder, CO) and anesthetic concentrations have focused on high-risk patients, but there are no effectiveness data applicable to an unselected surgical population.

A novel electronic algorithm for detecting potentially insufficient anesthesia: implications for the prevention of intraoperative awareness.

Objective: A recent clinical trial compared a minimum alveolar concentration (MAC)-based protocol to an electroencephalography (EEG)-based protocol for the prevention of intraoperative awareness. One limitation of this study design is that MAC-based protocols are not sensitive to the use of intravenous agents, while EEG-based protocols are. Our objective was to develop a MAC alert that incorporates intravenous agents.

A retrospective study of intraoperative awareness with methodological implications.

Background: Awareness during general anesthesia is a problem receiving increased attention from physicians and patients. Large multicentered studies have established an accepted incidence of awareness during general anesthesia as approximately 1-2 per 1000 cases or 0.15%.