Health IT and clinical decision support systems: human factors and successful adoption.
Author(s): Ohno-Machado, L
DOI: 10.1136/amiajnl-2014-003279
Author(s): Ohno-Machado, L
DOI: 10.1136/amiajnl-2014-003279
Author(s): Singleton, Kyle W, Bui, Alex A T, Hsu, William
DOI: 10.1136/amiajnl-2014-002968
The Secretary of Health and Human Services (HHS) acting through the Food and Drug Administration (FDA), and in collaboration with the Federal Communications Commission (FCC) and Office of the National Coordinator for Health IT (ONC) was tasked with delivering a report on an appropriate, risk-based regulatory framework for health information technology (IT). An expert stakeholder group was established under the auspices of the Health IT Policy Committee to help provide [...]
Author(s): Slight, Sarah P, Bates, David W
DOI: 10.1136/amiajnl-2014-002638
To evaluate attitudes regarding privacy of genomic data in a sample of patients with breast cancer.
Author(s): Rogith, Deevakar, Yusuf, Rafeek A, Hovick, Shelley R, Peterson, Susan K, Burton-Chase, Allison M, Li, Yisheng, Meric-Bernstam, Funda, Bernstam, Elmer V
DOI: 10.1136/amiajnl-2013-002579
Author(s): Bernstam, Elmer V, Tenenbaum, Jessica D, Kuperman, Gilad J
DOI: 10.1136/amiajnl-2013-002262
There is little evidence that readability formula outcomes relate to text understanding. The potential cause may lie in their strong reliance on word and sentence length. We evaluated word familiarity rather than word length as a stand-in for word difficulty. Word familiarity represents how well known a word is, and is estimated using word frequency in a large text corpus, in this work the Google web corpus. We conducted a [...]
Author(s): Leroy, Gondy, Kauchak, David
DOI: 10.1136/amiajnl-2013-002172
Electronic health records possess critical predictive information for machine-learning-based diagnostic aids. However, many traditional machine learning methods fail to simultaneously integrate textual data into the prediction process because of its high dimensionality. In this paper, we present a supervised method using Laplacian Eigenmaps to enable existing machine learning methods to estimate both low-dimensional representations of textual data and accurate predictors based on these low-dimensional representations at the same time.
Author(s): Perry, Thomas Ernest, Zha, Hongyuan, Zhou, Ke, Frias, Patricio, Zeng, Dadan, Braunstein, Mark
DOI: 10.1136/amiajnl-2013-001792
To optimize a new visit-independent, population-based cancer screening system (TopCare) by using operations research techniques to simulate changes in patient outreach staffing levels (delegates, navigators), modifications to user workflow within the information technology (IT) system, and changes in cancer screening recommendations.
Author(s): Zai, Adrian H, Kim, Seokjin, Kamis, Arnold, Hung, Ken, Ronquillo, Jeremiah G, Chueh, Henry C, Atlas, Steven J
DOI: 10.1136/amiajnl-2013-001681
Few ambulatory medication reconciliation tools exist. Transitions between inpatient and outpatient care can result in medication discrepancies. An interdisciplinary team designed a new 'Secure Messaging for Medication Reconciliation Tool' (SMMRT) within a patient web portal and piloted it among 60 patients at a Veterans Affairs hospital, an integrated system with a shared electronic health record. Recently discharged patients used SMMRT to view their medications in a secure email message and [...]
Author(s): Heyworth, Leonie, Paquin, Allison M, Clark, Justice, Kamenker, Victor, Stewart, Max, Martin, Tracey, Simon, Steven R
DOI: 10.1136/amiajnl-2013-001995
The purpose of this integrative review based on the published literature was to identify information systems currently being used by local health departments and to determine the extent to which standard terminology was used to communicate data, interventions, and outcomes to improve public health informatics at the local health department (LHD) level and better inform research, policy, and programs.
Author(s): Olsen, Jeanette, Baisch, Mary Jo
DOI: 10.1136/amiajnl-2013-001714