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Natural language processing (NLP) of symptoms from electronic health records (EHRs) could contribute to the advancement of symptom science. We aim to synthesize the literature on the use of NLP to process or analyze symptom information documented in EHR free-text narratives.

Clinical research data warehouses are largely populated from information extracted from electronic health records (EHRs). While these data provide information about a patient's medications, laboratory results, diagnoses, and history, her social, economic, and environmental determinants of health are also major contributing factors in readmission, morbidity, and mortality and are often absent or unstructured in the EHR. Details about a patient's socioeconomic status may be found in the U.S. census. To [...]

Social media use has become ubiquitous in the United States, providing unprecedented opportunities for research. However, the rapidly evolving research landscape has far outpaced federal regulations for the protection of human subjects. Recent highly publicized scandals have raised legitimate concerns in the media about how social media data are being used. These circumstances combined with the absence of ethical standards puts even the best intentioned scientists at risk of possible [...]

The US CDC identified prescription drug monitoring programs (PDMPs) as a tool to address the contemporary opioid crisis, but few studies have investigated PDMP usability and effectiveness from the users' perspective. Even fewer have considered how practices differ across medical domains. In this study, we aimed to address these gaps, soliciting perspectives on PDMPs from providers contending with the opioid crisis: physicians working in emergency departments (EDs) and pain management [...]

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.

Usable tools to support individual primary care clinicians in their diagnostic processes could help to reduce preventable harm from diagnostic errors. We conducted a formative study with primary care providers to identify key requisites to optimize the acceptability of 1 online collective intelligence platform (Human Diagnosis Project; Human Dx).

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 illustrate key contextual factors that may have effects on clinical decision support (CDS) adoption and, ultimately, success.

The objective of this article is to examine consumer perceptions of health information technology (health IT) utilization and benefits through an integrated conceptual framework.

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.