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Given that electronic clinical quality measures (eCQMs) are playing a central role in quality improvement applications nationwide, a stronger evidence base demonstrating their reliability is critically needed. To assess the reliability of electronic health record-extracted data elements and measure results for the Elective Delivery and Exclusive Breast Milk Feeding measures (vs manual abstraction) among a national sample of US acute care hospitals, as well as common sources of discrepancies and [...]

The study sought to investigate the disease state-dependent risk profiles of patient demographics and medical comorbidities associated with adverse outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections.

Over the next decade, many health care organizations (HCOs) will transition from one electronic health record (EHR) to another; some forced by hospital acquisition and others by choice in search of better EHRs. Herein, we apply principles of Requisite Imagination, or the ability to imagine key aspects of the future one is planning, to offer 6 recommendations on how to proactively safeguard these transitions. First, HCOs should implement a proactive [...]

To evaluate the potential for machine learning to predict medication alerts that might be ignored by a user, and intelligently filter out those alerts from the user's view.

After deploying a clinical prediction model, subsequently collected data can be used to fine-tune its predictions and adapt to temporal shifts. Because model updating carries risks of over-updating/fitting, we study online methods with performance guarantees.

Evidence synthesis teams, physicians, policy makers, and patients and their families all have an interest in following the outcomes of clinical trials and would benefit from being able to evaluate both the results posted in trial registries and in the publications that arise from them. Manual searching for publications arising from a given trial is a laborious and uncertain process. We sought to create a statistical model to automatically identify [...]

Electronic health records (EHRs) contain a large quantity of machine-readable data. However, institutions choose different EHR vendors, and the same product may be implemented differently at different sites. Our goal was to quantify the interoperability of real-world EHR implementations with respect to clinically relevant structured data.

Our study documented communication workflows across adult day care centers (ADCs) and primary care providers (PCPs) around complex needs of persons living with dementia (PLWD). We also identified barriers and facilitators to productive communication in clinical decision support and clinical information systems.

Electronic health records (EHRs) enable investigation of the association between phenotypes and risk factors. However, studies solely relying on potentially error-prone EHR-derived phenotypes (ie, surrogates) are subject to bias. Analyses of low prevalence phenotypes may also suffer from poor efficiency. Existing methods typically focus on one of these issues but seldom address both. This study aims to simultaneously address both issues by developing new sampling methods to select an optimal [...]

Problem lists represent an integral component of high-quality care. However, they are often inaccurate and incomplete. We studied the effects of alerts integrated into the inpatient and outpatient computerized provider order entry systems to assist in adding problems to the problem list when ordering medications that lacked a corresponding indication.