Zickmund SL et al, Journal of General Internal Medicine, 23(S1)
Bioinformatics experts are developing interactive patient portals to help those living with diabetes and other chronic diseases to better manage their conditions. However, little is known about what influences patients’ desires to use this technology.
To discern the impact of the provider–patient relationship on interest in using a web-based patient portal.
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Friedman CP et al. J Am Med Inform Assoc, 11(3)
In 2002-2003, the American College of Medical Informatics (ACMI) undertook a study of the future of informatics training. This project capitalized on the rapidly expanding interest in the role of computation in basic biological research, well characterized in the National Institutes of Health (NIH) Biomedical Information Science and Technology Initiative (BISTI) report. The defining activity of the project was the three-day 2002 Annual Symposium of the College. A committee, comprised of the authors of this report, subsequently carried out activities, including interviews with a broader informatics and biological sciences constituency, collation and categorization of observations, and generation of recommendations. The committee viewed biomedical informatics as an interdisciplinary field, combining basic informational and computational sciences with application domains, including health care, biological research, and education.
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Sethi, Prerna, and Kimberly Theodos, Perspectives in Health Information Management, 6(Fall 2009)
Exponentially growing biological and bioinformatics data sets present a challenge and an opportunity for researchers to contribute to the understanding of the genetic basis of phenotypes. Due to breakthroughs in microarray technology, it is possible to simultaneously monitor the expressions of thousands of genes, and it is imperative that researchers have access to the clinical data to understand the genetics and proteomics of the diseased tissue. This technology could be a landmark in personalized medicine, which will provide storage for clinical and genetic data in electronic health records (EHRs).
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