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The rise of clinician burnout has been correlated with the increased adoption of electronic health records (EHRs). Some vendors have used data entry logs to measure the amount of time spent using the EHR and have developed metrics of provider efficiency. Initial attempts to utilize these data have proven difficult as it is not always apparent whether variations reflect provider behavior or simply the metric definitions. Metric definitions are also [...]

The study sought to determine whether objective measures of electronic health record (EHR) use-related to time, volume of work, and proficiency-are associated with either or both components of clinician burnout: exhaustion and cynicism.

Although patient-peer support technologies have demonstrated effectiveness in a variety of health contexts-including diabetes, weight loss, and cancer-less is known about how hospitalized patients can benefit from this support. We investigated the nature of peer support in the hospital and the impact this support had on patients' hospital stays.

While there has been a substantial increase in health information exchange, levels of outside records use by frontline providers are low. We assessed whether integration between outside data and local data results in increased viewing of outside records, overall and by encounter, provider, and patient type.

The study sought to determine the dependence of the Electronic Medical Records and Genomics (eMERGE) rheumatoid arthritis (RA) algorithm on both RA and electronic health record (EHR) duration.

Implementation of machine learning (ML) may be limited by patients' right to "meaningful information about the logic involved" when ML influences healthcare decisions. Given the complexity of healthcare decisions, it is likely that ML outputs will need to be understood and trusted by physicians, and then explained to patients. We therefore investigated the association between physician understanding of ML outputs, their ability to explain these to patients, and their willingness [...]

Our primary objective is to provide the clinical informatics community with an introductory tutorial on calibration measurements and calibration models for predictive models using existing R packages and custom implemented code in R on real and simulated data. Clinical predictive model performance is commonly published based on discrimination measures, but use of models for individualized predictions requires adequate model calibration. This tutorial is intended for clinical researchers who want to [...]

The biomedical research and healthcare delivery communities have increasingly come to focus their attention on the role of data and computation in order to improve the quality, safety, costs, and outcomes of both wellness promotion and care delivery. Depending on the scale of such efforts, and the environments in which they are situated, they are referred to variably as personalized or precision medicine, population health, clinical transformation, value-driven care, or [...]