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Growing recognition that health is shaped by social and economic circumstances has resulted in a rapidly expanding set of clinical activities related to identifying, diagnosing, and intervening around patients' social risks in the context of health care delivery. The objective of this exploratory analysis was to identify existing documentation tools in common US medical coding systems reflecting these emerging clinical practices to improve patients' social health.

We describe the creation and evaluation of a personal audit and feedback (A&F) tool for anesthesiologists.

The widespread adoption and use of electronic health records and their use to enable learning health systems (LHS) holds great promise to accelerate both evidence-generating medicine (EGM) and evidence-based medicine (EBM), thereby enabling a LHS. In 2016, AMIA convened its 10th annual Policy Invitational to discuss issues key to facilitating the EGM-EBM paradigm at points-of-care (nodes), across organizations (networks), and to ensure viability of this model at scale (sustainability). In [...]

Chronic diseases often have long durations with slow, nonlinear progression and complex, and multifaceted manifestation. Modeling the progression of chronic diseases based on observational studies is challenging. We developed a framework to address these challenges by building probabilistic disease progression models to enable better understanding of chronic diseases and provide insights that could lead to better disease management.

To evaluate end-user acceptance and the effect of a commercial handheld decision support device in pediatric intensive care settings. The technology, pac2, was designed to assist nurses in calculating medication dose volumes and infusion rates at the bedside.

Systematic reviews of clinical trials could be updated faster by automatically monitoring relevant trials as they are registered, completed, and reported. Our aim was to provide a public interface to a database of curated links between systematic reviews and trial registrations.

To identify factors impacting physician use of information charted by others.

Alzheimer's disease (AD) is a severe neurodegenerative disorder and has become a global public health problem. Intensive research has been conducted for AD. But the pathophysiology of AD is still not elucidated. Disease comorbidity often associates diseases with overlapping patterns of genetic markers. This may inform a common etiology and suggest essential protein targets. US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) collects large-scale postmarketing surveillance data [...]

Electronic health record (EHR) data are increasingly used for biomedical discoveries. The nature of the data, however, requires expertise in both data science and EHR structure. The Observational Medical Out-comes Partnership (OMOP) common data model (CDM) standardizes the language and structure of EHR data to promote interoperability of EHR data for research. While the OMOP CDM is valuable and more attuned to research purposes, it still requires extensive domain knowledge [...]

The population-based assessment of patient-centered outcomes (PCOs) has been limited by the efficient and accurate collection of these data. Natural language processing (NLP) pipelines can determine whether a clinical note within an electronic medical record contains evidence on these data. We present and demonstrate the accuracy of an NLP pipeline that targets to assess the presence, absence, or risk discussion of two important PCOs following prostate cancer treatment: urinary incontinence [...]