Use of an algorithm for identifying hidden drug–drug interactions in adverse event reports.
Author(s): Gooden, Kyna McCullough, Pan, Xianying, Kawabata, Hugh, Heim, Jean-Marie
DOI: 10.1136/amiajnl-2012-001234
Author(s): Gooden, Kyna McCullough, Pan, Xianying, Kawabata, Hugh, Heim, Jean-Marie
DOI: 10.1136/amiajnl-2012-001234
Patient portal use has been associated with favorable outcomes, but we know less about how patients use and benefit from specific patient portal features.
Author(s): Wade-Vuturo, Ashley E, Mayberry, Lindsay Satterwhite, Osborn, Chandra Y
DOI: 10.1136/amiajnl-2012-001253
Privacy-preserving data publishing addresses the problem of disclosing sensitive data when mining for useful information. Among existing privacy models, ε-differential privacy provides one of the strongest privacy guarantees and makes no assumptions about an adversary's background knowledge. All existing solutions that ensure ε-differential privacy handle the problem of disclosing relational and set-valued data in a privacy-preserving manner separately. In this paper, we propose an algorithm that considers both relational and [...]
Author(s): Mohammed, Noman, Jiang, Xiaoqian, Chen, Rui, Fung, Benjamin C M, Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2012-001027
To evaluate an online disease management system supporting patients with uncontrolled type 2 diabetes.
Author(s): Tang, Paul C, Overhage, J Marc, Chan, Albert Solomon, Brown, Nancy L, Aghighi, Bahar, Entwistle, Martin P, Hui, Siu Lui, Hyde, Shauna M, Klieman, Linda H, Mitchell, Charlotte J, Perkins, Anthony J, Qureshi, Lubna S, Waltimyer, Tanya A, Winters, Leigha J, Young, Charles Y
DOI: 10.1136/amiajnl-2012-001263
Medication safety requires that each drug be monitored throughout its market life as early detection of adverse drug reactions (ADRs) can lead to alerts that prevent patient harm. Recently, electronic medical records (EMRs) have emerged as a valuable resource for pharmacovigilance. This study examines the use of retrospective medication orders and inpatient laboratory results documented in the EMR to identify ADRs.
Author(s): Liu, Mei, McPeek Hinz, Eugenia Renne, Matheny, Michael Edwin, Denny, Joshua C, Schildcrout, Jonathan Scott, Miller, Randolph A, Xu, Hua
DOI: 10.1136/amiajnl-2012-001119
Data-mining algorithms that can produce accurate signals of potentially novel adverse drug reactions (ADRs) are a central component of pharmacovigilance. We propose a signal-detection strategy that combines the adverse event reporting system (AERS) of the Food and Drug Administration and electronic health records (EHRs) by requiring signaling in both sources. We claim that this approach leads to improved accuracy of signal detection when the goal is to produce a highly [...]
Author(s): Harpaz, Rave, Vilar, Santiago, Dumouchel, William, Salmasian, Hojjat, Haerian, Krystl, Shah, Nigam H, Chase, Herbert S, Friedman, Carol
DOI: 10.1136/amiajnl-2012-000930
There is limited capacity to assess the comparative risks of medications after they enter the market. For rare adverse events, the pooling of data from multiple sources is necessary to have the power and sufficient population heterogeneity to detect differences in safety and effectiveness in genetic, ethnic and clinically defined subpopulations. However, combining datasets from different data custodians or jurisdictions to perform an analysis on the pooled data creates significant [...]
Author(s): El Emam, Khaled, Samet, Saeed, Arbuckle, Luk, Tamblyn, Robyn, Earle, Craig, Kantarcioglu, Murat
DOI: 10.1136/amiajnl-2011-000735
Author(s): Fickenscher, Kevin M
DOI: 10.1136/amiajnl-2013-001768
Author(s): Tatonetti, Nicholas P, Denny, Joshua C, Altman, Russ B
DOI: 10.1136/amiajnl-2012-001603
The term informatics is currently enveloped in chaos. One way to clarify the meaning of informatics is to identify the competencies associated with training in the field, but this approach can conceal the whole that the competencies atomistically describe. This work takes a different approach by offering three higher-level visions of what characterizes the field, viewing informatics as: (1) cross-training between basic informational sciences and an application domain, (2) the [...]
Author(s): Friedman, Charles P
DOI: 10.1136/amiajnl-2012-001206