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The diabetes healthcare provider plays a key role in interpreting blood glucose trends, but few institutions have successfully integrated patient home glucose data in the electronic health record (EHR). Published implementations to date have required custom interfaces, which limit wide-scale replication. We piloted automated integration of continuous glucose monitor data in the EHR using widely available consumer technology for 10 pediatric patients with insulin-dependent diabetes. Establishment of a passive data [...]

To investigate how individuals with diabetes and diabetes educators reason about data collected through self-monitoring and to draw implications for the design of data-driven self-management technologies.

To evaluate the feasibility of automatically assessing the Social Rhythm Metric (SRM), a clinically-validated marker of stability and rhythmicity for individuals with bipolar disorder (BD), using passively-sensed data from smartphones.

To understand self-monitoring strategies used independently of clinical treatment by individuals with bipolar disorder (BD), in order to recommend technology design principles to support mental health management.

We aimed to explore and examine how and in what ways the use of social network sites (SNSs) can improve health outcomes, specifically better psychological well-being, for cancer-affected people.

Electronic health record content is created by clinicians and is driven largely by intermittent and brief encounters with patients. Collecting data directly from patients in the form of patient-generated data (PGD) provides an unprecedented opportunity to capture personal, contextual patient information that can supplement clinical data and enhance patients' self-care. The US Department of Veterans Affairs (VA) is striving to implement the enterprise-wide capability to collect and use PGD in [...]

Electronic medical records (EMRs) are being increasingly utilized to conduct clinical and epidemiologic research in numerous fields. To monitor and improve care of HIV-infected patients in Washington, DC, one of the most severely affected urban areas in the United States, we developed a city-wide database across 13 clinical sites using electronic data abstraction and manual data entry from EMRs.

Back pain is a global health problem. Recent research has shown that risk factors that are proximal to the onset of back pain might be important targets for preventive interventions. Rapid communication through social media might be useful for delivering timely interventions that target proximal risk factors. Identifying individuals who are likely to discuss back pain on Twitter could provide useful information to guide online interventions.

Measurement of patient race/ethnicity in electronic health records is mandated and important for tracking health disparities.