President's column: interoperability--the 30% solution: from dialog and rhetoric to reality.
Author(s): Fickenscher, Kevin M
DOI: 10.1136/amiajnl-2013-001768
Author(s): Fickenscher, Kevin M
DOI: 10.1136/amiajnl-2013-001768
To extract drug indications from structured drug labels and represent the information using codes from standard medical terminologies.
Author(s): Fung, Kin Wah, Jao, Chiang S, Demner-Fushman, Dina
DOI: 10.1136/amiajnl-2012-001291
Social networks have been used in the study of outbreaks of infectious diseases, including in small group settings such as individual hospitals. Collecting the data needed to create such networks, however, can be time consuming, costly, and error prone. We sought to create a social network of hospital inpatients using electronic medical record (EMR) data already collected for other purposes, for use in simulating outbreaks of nosocomial infections.
Author(s): Cusumano-Towner, Marco, Li, Daniel Y, Tuo, Shanshan, Krishnan, Gomathi, Maslove, David M
DOI: 10.1136/amiajnl-2012-001401
To summarize the literature describing computer-based interventions aimed at improving bidirectional communication between clinical and public health.
Author(s): Dixon, Brian E, Gamache, Roland E, Grannis, Shaun J
DOI: 10.1136/amiajnl-2012-001514
Adverse drug events cause substantial morbidity and mortality and are often discovered after a drug comes to market. We hypothesized that Internet users may provide early clues about adverse drug events via their online information-seeking. We conducted a large-scale study of Web search log data gathered during 2010. We pay particular attention to the specific drug pairing of paroxetine and pravastatin, whose interaction was reported to cause hyperglycemia after the [...]
Author(s): White, Ryen W, Tatonetti, Nicholas P, Shah, Nigam H, Altman, Russ B, Horvitz, Eric
DOI: 10.1136/amiajnl-2012-001482
With increasing use electronic health records (EHR) in the USA, we looked at the predictive values of the International Classification of Diseases, 9th revision (ICD-9) coding system for surveillance of chronic hepatitis B virus (HBV) infection.
Author(s): Mahajan, Reena, Moorman, Anne C, Liu, Stephen J, Rupp, Loralee, Klevens, R Monina, ,
DOI: 10.1136/amiajnl-2012-001558
Self-monitoring of physical activity (PA) and diet are key components of behavioral weight loss programs. The purpose of this study was to assess the relationship between diet (mobile app, website, or paper journal) and PA (mobile app vs no mobile app) self-monitoring and dietary and PA behaviors.
Author(s): Turner-McGrievy, Gabrielle M, Beets, Michael W, Moore, Justin B, Kaczynski, Andrew T, Barr-Anderson, Daheia J, Tate, Deborah F
DOI: 10.1136/amiajnl-2012-001510
Medication errors in hospitals are common, expensive, and sometimes harmful to patients. This study's objective was to derive a nationally representative estimate of medication error reduction in hospitals attributable to electronic prescribing through computerized provider order entry (CPOE) systems.
Author(s): Radley, David C, Wasserman, Melanie R, Olsho, Lauren Ew, Shoemaker, Sarah J, Spranca, Mark D, Bradshaw, Bethany
DOI: 10.1136/amiajnl-2012-001241
To determine whether indication-based computer order entry alerts intercept wrong-patient medication errors.
Author(s): Galanter, William, Falck, Suzanne, Burns, Matthew, Laragh, Marci, Lambert, Bruce L
DOI: 10.1136/amiajnl-2012-001555
A sizable fraction of patients experiences adverse drug events or lack of drug efficacy. A part of this variability in drug response can be explained by genetic differences between patients. However, pharmacogenomic data as well as computational clinical decision support systems for interpreting such data are still unavailable in most healthcare settings. We address this problem by introducing the medicine safety code (MSC), which captures compressed pharmacogenomic data in a [...]
Author(s): Samwald, Matthias, Adlassnig, Klaus-Peter
DOI: 10.1136/amiajnl-2012-001275