BackgroundDespite a demanding work environment, information on stress and burnout of critical care fellows is limited.ObjectivesTo assess 1) levels of burnout, perceived stress, and quality of life in critical care fellows, and 2) the impact of a brief stress management training on these outcomes.MethodsIn a tertiary care academic medical center, 58 critical care fellows of varying subspecialties and training levels were surveyed to assess baseline levels of stress and burnout. Twenty-one of the 58 critical care fellows who were in the first year of training at the time of this initial survey participated in a pre-test and 1-year post-test to determine the effects of a brief, 90-min stress management intervention.ResultsBased on responses (n=58) to the abbreviated Maslach Burnout Inventory, reported burnout was significantly lower in Asian fellows (p=0.04) and substantially higher among graduating fellows (versus new and transitioning fellows) (p=0.02). Among the intervention cohort, burnout did not significantly improve – though two-thirds of fellows reported using the interventional techniques to deal with stressful situations. Fellows who participated in the intervention rated the effectiveness of the course as 4 (IQR=3.75–5) using the 5-point Likert scale.ConclusionsIn comparison with the new and transitioning trainees, burnout was highest among graduating critical care fellows. Although no significant improvements were found in first-year fellows’ burnout scores following the single, 90-min training intervention, participants felt the training did provide them with tools to apply during stressful situations.

BackgroundThe development and validation of automated electronic medical record (EMR) search strategies are important for establishing the timing of mechanical ventilation initiation in the intensive care unit (ICU).Thus, we sought to develop and validate an automated EMR search algorithm (strategy) for time zero, the moment of mechanical ventilation initiation in the critically ill patient.MethodsThe EMR search algorithm was developed on the basis of several mechanical ventilation parameters, with the final parameter being positive end-expiratory pressure (PEEP), and was applied to a comprehensive institutional EMR database. The search algorithm was derived from a secondary retrospective analysis of a subset of 450 patients from a cohort of 2,684 patients admitted to a medical ICU and a surgical ICU from January 1, 2010, through December 31, 2011. It was then validated in an independent subset of 450 patients from the same period. The overall percent of agreement between our search algorithm and a comprehensive manual medical record review in the derivation and validation subsets, using peak inspiratory pressure (PIP) as the reference standard, was compared to assess timing of mechanical ventilation initiation.ResultsIn the derivation subset, the automated electronic search strategy achieved an 87% (κ = 0.87) perfect agreement, with 94% agreement to within one minute. In validating this search algorithm, perfect agreement was found in 92% (κ = 0.92) of patients, with 99% agreement occurring within one minute.ConclusionsThe use of an electronic search strategy resulted in highly accurate extraction of mechanical ventilation initiation in the ICU. The search algorithm of mechanical ventilation initiation is highly efficient and reliable and can facilitate both clinical research and patient care management in a timely manner.

KeywordsElectronic medical record, emergent, endotracheal intubation, intensive care unit, search algorithm SummaryBackground: The development and validation of automated electronic medical record (EMR) search strategies are important in identifying emergent endotracheal intubations in the intensive care unit (ICU). Objective: To develop and validate an automated search algorithm (strategy) for emergent endotracheal intubation in the critically ill patient. Methods: The EMR search algorithm was created through sequential steps with keywords applied to an institutional EMR database. The search strategy was derived retrospectively through a secondary analysis of a 450-patient subset from the 2,684 patients admitted to either a medical or surgical ICU from January 1, 2010, through December 31, 2011. This search algorithm was validated against an additional 450 randomly selected patients. Sensitivity, specificity, and negative and positive predictive values of the automated search algorithm were compared with a manual medical record review (the reference standard) for data extraction of emergent endotracheal intubations. Results: In the derivation subset, the automated electronic note search strategy achieved a sensitivity of 74% (95% CI, 69%-79%) and a specificity of 98% (95% CI, 92%-100%). With refinements in the search algorithm, sensitivity increased to 95% (95% CI, 91%-97%) and specificity decreased to 96% (95% CI, 92%-98%) in this subset. After validation of the algorithm through a separate patient subset, the final reported sensitivity and specificity were 95% (95% CI, 86%-99%) and 100% (95% CI, 98%-100%). Conclusions: Use of electronic search algorithms allows for correct extraction of emergent endotracheal intubations in the ICU, with high degrees of sensitivity and specificity. Such search algorithms are a reliable alternative to manual chart review for identification of emergent endotracheal intubations.

BackgroundTraditional electronic medical record (EMR) interfaces mark laboratory tests as abnormal based on standard reference ranges derived from healthy, middle-aged adults. This yields many false positive alerts with subsequent alert-fatigue when applied to complex populations like hospitalized, critically ill patients. Novel EMR interfaces using adjusted reference ranges customized for specific patient populations may ameliorate this problem.ObjectiveTo compare accuracy of abnormal laboratory value indicators in a novel vs traditional EMR interface.MethodsLaboratory data from intensive care unit (ICU) patients consecutively admitted during a two-day period were recorded. For each patient, available laboratory results and the problem list were sent to two mutually blinded critical care experts, who marked the values about which they would like to be alerted. All disagreements were resolved by an independent super-reviewer. Based on this gold standard, we calculated and compared the sensitivity, specificity, positive and negative predictive values (PPV, NPV) of customized vs traditional abnormal value indicators.ResultsThirty seven patients with a total of 1341 laboratory results were included. Experts’ agreement was fair (kappa = 0.39). Compared to the traditional EMR, custom abnormal laboratory value indicators had similar sensitivity (77% vs 85%, P = 0.22) and NPV (97.1% vs 98.6%, P = 0.06) but higher specificity (79% vs 61%, P<0.001) and PPV (28% vs 11%, P<0.001).ConclusionsReference ranges for laboratory values customized for an ICU population decrease false positive alerts. Disagreement among clinicians about which laboratory values should be indicated as abnormal limits the development of customized reference ranges.

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