Why clinicians use or don't use health information exchange.
Author(s): Rudin, Robert S
DOI: 10.1136/amiajnl-2011-000288
Author(s): Rudin, Robert S
DOI: 10.1136/amiajnl-2011-000288
To describe a system for determining the assertion status of medical problems mentioned in clinical reports, which was entered in the 2010 i2b2/VA community evaluation 'Challenges in natural language processing for clinical data' for the task of classifying assertions associated with problem concepts extracted from patient records.
Author(s): Clark, Cheryl, Aberdeen, John, Coarr, Matt, Tresner-Kirsch, David, Wellner, Ben, Yeh, Alexander, Hirschman, Lynette
DOI: 10.1136/amiajnl-2011-000164
Evidence suggests that the medication lists of patients are often incomplete and could negatively affect patient outcomes. In this article, the authors propose the application of collaborative filtering methods to the medication reconciliation task. Given a current medication list for a patient, the authors employ collaborative filtering approaches to predict drugs the patient could be taking but are missing from their observed list.
Author(s): Hasan, Sharique, Duncan, George T, Neill, Daniel B, Padman, Rema
DOI: 10.1136/amiajnl-2011-000106
The field of Biomedical and Health Informatics (BMHI) continues to define itself, and there are many educational programs offering 'informatics' degrees with varied foci. The goal of this study was to develop a scheme for systematic comparison of programs across the entire BMHI spectrum and to identify commonalities among informatics curricula.
Author(s): Kampov-Polevoi, Julia, Hemminger, Bradley M
DOI: 10.1136/jamia.2010.004259
There is controversy over the impact of electronic health record (EHR) systems on cost of care and safety. The authors studied the effects of an inpatient EHR system with computerized provider order entry on selected measures of cost of care and safety. Laboratory tests per week per hospitalization decreased from 13.9 to 11.4 (18%; p 0.001). Radiology examinations per hospitalization decreased from 2.06 to 1.93 (6.3%; p 0.009). Monthly transcription [...]
Author(s): Zlabek, Jonathan A, Wickus, Jared W, Mathiason, Michelle A
DOI: 10.1136/jamia.2010.007229
Studies of the doctor-patient relationship have focused on the elaboration of power and/or authority using a range of techniques to study the encounter between doctor and patient. The widespread adoption of computers by doctors brings a third party into the consultation. While there has been some research into the way doctors view and manage this new relationship, the behavior of patients in response to the computer is rarely studied. In [...]
Author(s): Pearce, Christopher, Arnold, Michael, Phillips, Christine, Trumble, Stephen, Dwan, Kathryn
DOI: 10.1136/jamia.2010.006486
To provide an overview and tutorial of natural language processing (NLP) and modern NLP-system design.
Author(s): Nadkarni, Prakash M, Ohno-Machado, Lucila, Chapman, Wendy W
DOI: 10.1136/amiajnl-2011-000464
Expert authorities recommend clinical decision support systems to reduce prescribing error rates, yet large numbers of insignificant on-screen alerts presented in modal dialog boxes persistently interrupt clinicians, limiting the effectiveness of these systems. This study compared the impact of modal and non-modal electronic (e-) prescribing alerts on prescribing error rates, to help inform the design of clinical decision support systems.
Author(s): Scott, Gregory P T, Shah, Priya, Wyatt, Jeremy C, Makubate, Boikanyo, Cross, Frank W
DOI: 10.1136/amiajnl-2011-000199
The aim of this study was to measure the effect of an electronic heparin-induced thrombocytopenia (HIT) alert on provider ordering behaviors and on patient outcomes.
Author(s): Austrian, Jonathan S, Adelman, Jason S, Reissman, Stan H, Cohen, Hillel W, Billett, Henny H
DOI: 10.1136/amiajnl-2011-000138
The US Vaccine Adverse Event Reporting System (VAERS) collects spontaneous reports of adverse events following vaccination. Medical officers review the reports and often apply standardized case definitions, such as those developed by the Brighton Collaboration. Our objective was to demonstrate a multi-level text mining approach for automated text classification of VAERS reports that could potentially reduce human workload.
Author(s): Botsis, Taxiarchis, Nguyen, Michael D, Woo, Emily Jane, Markatou, Marianthi, Ball, Robert
DOI: 10.1136/amiajnl-2010-000022