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

We sought to assess the current state of risk prediction and segmentation models (RPSM) that focus on whole populations.

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 [...]

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 [...]

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

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.

Data modeling for electronic health records (EHRs) is complex, requiring technological and cognitive sophistication. The openEHR approach leverages the tacit knowledge of domain experts made explicit in a model development process aiming at interoperability and data reuse.

Usability of electronic health records (EHRs) remains challenging, and poor EHR design has patient safety implications. Heuristic evaluation detects usability issues that can be classified by severity. The National Institute of Standards and Technology provides a safety scale for EHR usability. Our objectives were to investigate the relationship between heuristic severity ratings and safety scale ratings in an effort to analyze EHR safety.

The implementation of an electronic health record (EHR) with structured and standardized recording of patient data can improve data quality and reusability. Whether and how users perceive these advantages may depend on the preimplementation situation.