In 2017, 43.9% of US physicians reported symptoms of burnout. Poor electronic health record (EHR) usability and time-consuming data entry contribute to burnout. However, less is known about how modifiable dimensions of EHR use relate to burnout and how these associations vary by medical specialty. Using the KLAS Arch Collaborative’s large-scale nationwide physician (MD/DO) data, we used ordinal logistic regression to analyze associations between self-reported burnout and after-hours charting and organizational EHR support. We examined how these relationships differ by medical specialty, adjusting for confounders. Physicians reporting ≤ 5 hours weekly of after-hours charting were twice as likely to report lower burnout scores compared to those charting ≥6 hours (aOR: 2.43, 95% CI: 2.30, 2.57). Physicians who agree that their organization has done a great job with EHR implementation, training, and support (aOR: 2.14, 95% CI: 2.01, 2.28) were also twice as likely to report lower scores on the burnout survey question compared to those who disagree. Efforts to reduce after-hours charting and improve organizational EHR support could help address physician burnout.

SummaryBackgroundThe 2013 American College of Cardiology / American Heart Association Guidelines for the Treatment of Blood Cholesterol emphasize treatment based on cardiovascular risk. But finding time in a primary care visit to manually calculate cardiovascular risk and prescribe treatment based on risk is challenging. We developed an informatics-based clinical decision support tool, MayoExpertAdvisor, to deliver automated cardiovascular risk scores and guideline-based treatment recommendations based on patient-specific data in the electronic heath record.ObjectiveTo assess the impact of our clinical decision support tool on the efficiency and accuracy of clinician calculation of cardiovascular risk and its effect on the delivery of guideline-consistent treatment recommendations.MethodsClinicians were asked to review the EHR records of selected patients. We evaluated the amount of time and the number of clicks and keystrokes needed to calculate cardiovascular risk and provide a treatment recommendation with and without our clinical decision support tool. We also compared the treatment recommendation arrived at by clinicians with and without the use of our tool to those recommended by the guidelines.ResultsClinicians saved 3 minutes and 38 seconds in completing both tasks with MayoExpertAdvisor, used 94 fewer clicks and 23 fewer key strokes, and improved accuracy from the baseline of 60.61% to 100% for both the risk score calculation and guideline-consistent treatment recommendation.ConclusionInformatics solution can greatly improve the efficiency and accuracy of individualized treatment recommendations and have the potential to increase guideline compliance.

The use of living donation is an important option for patients in need of liver transplant. We retrospectively reviewed the preoperative Model for End-Stage Liver Disease (MELD) score, baseline coagulation laboratory results, and intraoperative transfusion of red blood cells and component therapy for 27 living donation transplants and 69 cadaveric donation transplants during a 3-yr period (2001-2004). Patients undergoing living donation transplantation had significantly lower MELD scores and preserved coagulation function compared with cadaveric donation transplantation recipients (P < 0.001). The living donation transplant patients also received significantly fewer transfusions of red blood cells and component therapy compared with the cadaveric donation transplant patients (P < 0.001). For the combined population of both cadaveric donation transplant and living donation transplant patients, there were significant associations between MELD score and preoperative coagulation tests (P < 0.001) and intraoperative transfusion of blood and component therapy. MELD score and preoperative fibrinogen concentration were identified as independent predictors of transfusion exposure. In conclusion, we detected significant differences in severity of disease at time of transplantation, degree of impairment of coagulation function, and need for transfusion of red blood cells and component therapy between patients undergoing living donation transplantation compared with patients undergoing cadaveric donation transplantation.

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