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Personal health records (PHRs) offer patients a portal to view lab results, communicate with their doctors, and refill medications. Expanding PHR access to mobile devices could increase patients' engagement with their PHRs. We examined whether access to a mobile-optimized PHR changed the frequency and timeliness of PHR use among adult patients with diabetes in an integrated delivery system. Among patients originally using the PHR only by computer, PHR use frequency [...]

To identify who were social media active e-cigarette users, to compare the use patterns from both survey and social media data for data triangulation, and to jointly use both datasets to conduct a comprehensive analysis on e-cigarette future use intentions.

Blockchain-based platforms are emerging to provide solutions for technical and governance challenges associated with genomic data sharing. Providing capabilities for distributed data stewardship and participatory access control along with effective ways for enforcement of the data access agreements and data ownership are among the major promises of these platforms.

Connected medical devices and electronic health records have added important functionality to patient care, but have also introduced a range of cybersecurity concerns. When a healthcare organization suffers from a cybersecurity incident, its incident response strategies are critical to the success of its recovery.

Quantify physiologically acceptable PICU-discharge vital signs and develop machine learning models to predict these values for individual patients throughout their PICU episode.

Parents routinely access young children's medical records, but medical societies strongly recommend confidential care during adolescence, and most medical centers restrict parental records access during the teen years. We sought to assess public opinion about adolescent medical privacy.

Scoring laboratory polysomnography (PSG) data remains a manual task of visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb movements. Attempts to automate this process have been hampered by the complexity of PSG signals and physiological heterogeneity between patients. Deep neural networks, which have recently achieved expert-level performance for other complex medical tasks, are ideally suited to PSG scoring, given sufficient training data.

This systematic review aims to analyze current capabilities, challenges, and impact of self-directed mobile health (mHealth) research applications such as those based on the ResearchKit platform.