What Big Data means to me.
Author(s): Bourne, Philip E
DOI: 10.1136/amiajnl-2014-002651
Author(s): Bourne, Philip E
DOI: 10.1136/amiajnl-2014-002651
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2014-002666
To compare the agreement of electronic health record (EHR) data versus Medicaid claims data in documenting adult preventive care. Insurance claims are commonly used to measure care quality. EHR data could serve this purpose, but little information exists about how this source compares in service documentation. For 13 101 Medicaid-insured adult patients attending 43 Oregon community health centers, we compared documentation of 11 preventive services, based on EHR versus Medicaid claims [...]
Author(s): Heintzman, John, Bailey, Steffani R, Hoopes, Megan J, Le, Thuy, Gold, Rachel, O'Malley, Jean P, Cowburn, Stuart, Marino, Miguel, Krist, Alex, DeVoe, Jennifer E
DOI: 10.1136/amiajnl-2013-002333
To examine how patient portals contribute to health service delivery and patient outcomes. The specific aims were to examine how outcomes are produced, and how variations in outcomes can be explained.
Author(s): Otte-Trojel, Terese, de Bont, Antoinette, Rundall, Thomas G, van de Klundert, Joris
DOI: 10.1136/amiajnl-2013-002501
To design, build, and evaluate a storage model able to manage heterogeneous digital imaging and communications in medicine (DICOM) images. The model must be simple, but flexible enough to accommodate variable content without structural modifications; must be effective on answering query/retrieval operations according to the DICOM standard; and must provide performance gains on querying/retrieving content to justify its adoption by image-related projects.
Author(s): Savaris, Alexandre, Härder, Theo, von Wangenheim, Aldo
DOI: 10.1136/amiajnl-2013-002337
Data-driven risk stratification models built using data from a single hospital often have a paucity of training data. However, leveraging data from other hospitals can be challenging owing to institutional differences with patients and with data coding and capture.
Author(s): Wiens, Jenna, Guttag, John, Horvitz, Eric
DOI: 10.1136/amiajnl-2013-002162
As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it.
Author(s): Heath, Allison P, Greenway, Matthew, Powell, Raymond, Spring, Jonathan, Suarez, Rafael, Hanley, David, Bandlamudi, Chai, McNerney, Megan E, White, Kevin P, Grossman, Robert L
DOI: 10.1136/amiajnl-2013-002155
Physician awareness of the results of tests pending at discharge (TPADs) is poor. We developed an automated system that notifies responsible physicians of TPAD results via secure, network email. We sought to evaluate the impact of this system on self-reported awareness of TPAD results by responsible physicians, a necessary intermediary step to improve management of TPAD results.
Author(s): Dalal, Anuj K, Roy, Christopher L, Poon, Eric G, Williams, Deborah H, Nolido, Nyryan, Yoon, Cathy, Budris, Jonas, Gandhi, Tejal, Bates, David W, Schnipper, Jeffrey L
DOI: 10.1136/amiajnl-2013-002030
Quality indicators for the treatment of type 2 diabetes are often retrieved from a chronic disease registry (CDR). This study investigates the quality of recording in a general practitioner's (GP) electronic medical record (EMR) compared to a simple, web-based CDR.
Author(s): Barkhuysen, Pashiera, de Grauw, Wim, Akkermans, Reinier, Donkers, José, Schers, Henk, Biermans, Marion
DOI: 10.1136/amiajnl-2012-001479
Biomedical researchers share a common challenge of making complex data understandable and accessible as they seek inherent relationships between attributes in disparate data types. Data discovery in this context is limited by a lack of query systems that efficiently show relationships between individual variables, but without the need to navigate underlying data models. We have addressed this need by developing Harvest, an open-source framework of modular components, and using it [...]
Author(s): Pennington, Jeffrey W, Ruth, Byron, Italia, Michael J, Miller, Jeffrey, Wrazien, Stacey, Loutrel, Jennifer G, Crenshaw, E Bryan, White, Peter S
DOI: 10.1136/amiajnl-2013-001825