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The study sought to test the feasibility of using Twitter data to assess determinants of consumers' health behavior toward human papillomavirus (HPV) vaccination informed by the Integrated Behavior Model (IBM).

This case report applied principles from the data visualization (DV) literature and feedback from nurses to develop an effective report to display adherence with an evidence-based fall prevention program. We tested the usability of the original and revised reports using a Health Information Technology Usability Evaluation Scale (Health-ITUES) customized for this project. Items were rated on a 5-point Likert scale, strongly disagree (1) to strongly agree (5). The literature emphasized [...]

Research to date focused on quantifying team collaboration has relied on identifying shared patients but does not incorporate the major role of communication patterns. The goal of this study was to describe the patterns and volume of communication among care team members involved in treating breast cancer patients.

The study sought to design symptom reports of longitudinal patient-reported outcomes data that are understandable and meaningful to end users.

Initiatives to reduce neighborhood-based health disparities require access to meaningful, timely, and local information regarding health behavior and its determinants. We examined the validity of Twitter as a source of information for neighborhood-level analysis of dietary choices and attitudes.

To assess if the amount of time a pharmacist spends verifying medication orders increases as medication orders become more complex.

The ability to identify novel risk factors for health outcomes is a key strength of electronic health record (EHR)-based research. However, the validity of such studies is limited by error in EHR-derived phenotypes. The objective of this study was to develop a novel procedure for reducing bias in estimated associations between risk factors and phenotypes in EHR data.

To summarize the research literature about safety concerns with consumer-facing health apps and their consequences.

Audio-enhanced computer-assisted self-interviews (ACASIs) are useful adjuncts for clinical care but are rarely integrated into the electronic health record (EHR). We created a flexible framework for integrating an ACASIs with clinical decision support (CDS) into the EHR. We used this program to identify adolescents at risk for sexually transmitted infections (STIs) in the emergency department (ED). We provide an overview of the software platform and qualitative user acceptance.

To investigate the relationship between emotion sharing and technically troubled dialysis (TTD) in a remote patient monitoring (RPM) setting.