Crafting the third century of the National Library of Medicine.
Author(s): Brennan, Patricia Flatley
DOI: 10.1093/jamia/ocw122
Author(s): Brennan, Patricia Flatley
DOI: 10.1093/jamia/ocw122
Author(s): Fridsma, Douglas B, Smith, Jeffery
DOI: 10.1093/jamia/ocw120
Author(s): Ohno-Machado, Lucila, ,
DOI: 10.1093/jamia/ocw129
Experts suggest that formulary alerts at the time of medication order entry are the most effective form of clinical decision support to automate formulary management.
Author(s): Her, Qoua L, Amato, Mary G, Seger, Diane L, Beeler, Patrick E, Slight, Sarah P, Dalleur, Olivia, Dykes, Patricia C, Gilmore, James F, Fanikos, John, Fiskio, Julie M, Bates, David W
DOI: 10.1093/jamia/ocv181
Quantify the variability of patients' problem lists - in terms of the number, type, and ordering of problems - across multiple physicians and assess physicians' criteria for organizing and ranking diagnoses.
Author(s): Krauss, John C, Boonstra, Philip S, Vantsevich, Anna V, Friedman, Charles P
DOI: 10.1093/jamia/ocv211
Describe the change in mobile technology used by an urban Latino population between 2011 and 2014, and compare findings with national estimates.
Author(s): Arora, Sanjay, Ford, Kelsey, Terp, Sophie, Abramson, Tiffany, Ruiz, Ryan, Camilon, Marissa, Coyne, Christopher J, Lam, Chun Nok, Menchine, Michael, Burner, Elizabeth
DOI: 10.1093/jamia/ocv203
In early 2010, Harvard Medical School and Boston Children's Hospital began an interoperability project with the distinctive goal of developing a platform to enable medical applications to be written once and run unmodified across different healthcare IT systems. The project was called Substitutable Medical Applications and Reusable Technologies (SMART).
Author(s): Mandel, Joshua C, Kreda, David A, Mandl, Kenneth D, Kohane, Isaac S, Ramoni, Rachel B
DOI: 10.1093/jamia/ocv189
Natural language processing methods for medical auto-coding, or automatic generation of medical billing codes from electronic health records, generally assign each code independently of the others. They may thus assign codes for closely related procedures or diagnoses to the same document, even when they do not tend to occur together in practice, simply because the right choice can be difficult to infer from the clinical narrative.
Author(s): Subotin, Michael, Davis, Anthony R
DOI: 10.1093/jamia/ocv201
The metadata reflecting the location of the infected host (LOIH) of virus sequences in GenBank often lacks specificity. This work seeks to enhance this metadata by extracting more specific geographic information from related full-text articles and mapping them to their latitude/longitudes using knowledge derived from external geographical databases.
Author(s): Tahsin, Tasnia, Weissenbacher, Davy, Rivera, Robert, Beard, Rachel, Firago, Mari, Wallstrom, Garrick, Scotch, Matthew, Gonzalez, Graciela
DOI: 10.1093/jamia/ocv172
The use of risk prediction models grows as electronic medical records become widely available. Here, we develop and validate a model to identify individuals at increased risk for colorectal cancer (CRC) by analyzing blood counts, age, and sex, then determine the model's value when used to supplement conventional screening.
Author(s): Kinar, Yaron, Kalkstein, Nir, Akiva, Pinchas, Levin, Bernard, Half, Elizabeth E, Goldshtein, Inbal, Chodick, Gabriel, Shalev, Varda
DOI: 10.1093/jamia/ocv195