Networking the country to promote health and scientific discovery.
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2014-003005
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2014-003005
To assess the effects of librarian-provided services in healthcare settings on patient, healthcare provider, and researcher outcomes.
Author(s): Perrier, Laure, Farrell, Ann, Ayala, A Patricia, Lightfoot, David, Kenny, Tim, Aaronson, Ellen, Allee, Nancy, Brigham, Tara, Connor, Elizabeth, Constantinescu, Teodora, Muellenbach, Joanne, Epstein, Helen-Ann Brown, Weiss, Ardis
DOI: 10.1136/amiajnl-2014-002825
mHealth interventions have shown promise for helping people sustain healthy behaviors such as weight loss. However, few have assessed treatment fidelity, that is, the accurate delivery, receipt, and enactment of the intervention. Treatment fidelity is critical because the valid interpretation and translation of intervention studies depend on treatment fidelity assessments. We describe strategies used to assess treatment fidelity in mobile health (mHealth) interventions aimed at sustaining healthy behaviors in weight [...]
Author(s): Shaw, Ryan J, Steinberg, Dori M, Zullig, Leah L, Bosworth, Hayden B, Johnson, Constance M, Davis, Linda L
DOI: 10.1136/amiajnl-2013-002610
This research investigated the use of SNOMED CT to represent diagnostic tissue morphologies and notable tissue architectures typically found within a pathologist's microscopic examination report to identify gaps in expressivity of SNOMED CT for use in anatomic pathology.
Author(s): Campbell, Walter S, Campbell, James R, West, William W, McClay, James C, Hinrichs, Steven H
DOI: 10.1136/amiajnl-2013-002456
The Patient-Centered Outcomes Research Institute (PCORI) has launched PCORnet, a major initiative to support an effective, sustainable national research infrastructure that will advance the use of electronic health data in comparative effectiveness research (CER) and other types of research. In December 2013, PCORI's board of governors funded 11 clinical data research networks (CDRNs) and 18 patient-powered research networks (PPRNs) for a period of 18 months. CDRNs are based on the electronic [...]
Author(s): Fleurence, Rachael L, Curtis, Lesley H, Califf, Robert M, Platt, Richard, Selby, Joe V, Brown, Jeffrey S
DOI: 10.1136/amiajnl-2014-002747
The ADVANCE (Accelerating Data Value Across a National Community Health Center Network) clinical data research network (CDRN) is led by the OCHIN Community Health Information Network in partnership with Health Choice Network and Fenway Health. The ADVANCE CDRN will 'horizontally' integrate outpatient electronic health record data for over one million federally qualified health center patients, and 'vertically' integrate hospital, health plan, and community data for these patients, often under-represented in [...]
Author(s): DeVoe, Jennifer E, Gold, Rachel, Cottrell, Erika, Bauer, Vance, Brickman, Andrew, Puro, Jon, Nelson, Christine, Mayer, Kenneth H, Sears, Abigail, Burdick, Tim, Merrell, Jonathan, Matthews, Paul, Fields, Scott
DOI: 10.1136/amiajnl-2014-002744
A learning health system (LHS) integrates research done in routine care settings, structured data capture during every encounter, and quality improvement processes to rapidly implement advances in new knowledge, all with active and meaningful patient participation. While disease-specific pediatric LHSs have shown tremendous impact on improved clinical outcomes, a national digital architecture to rapidly implement LHSs across multiple pediatric conditions does not exist. PEDSnet is a clinical data research network [...]
Author(s): Forrest, Christopher B, Margolis, Peter A, Bailey, L Charles, Marsolo, Keith, Del Beccaro, Mark A, Finkelstein, Jonathan A, Milov, David E, Vieland, Veronica J, Wolf, Bryan A, Yu, Feliciano B, Kahn, Michael G
DOI: 10.1136/amiajnl-2014-002743
We describe the architecture of the Patient Centered Outcomes Research Institute (PCORI) funded Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS, http://www.SCILHS.org) clinical data research network, which leverages the $48 billion dollar federal investment in health information technology (IT) to enable a queryable semantic data model across 10 health systems covering more than 8 million patients, plugging universally into the point of care, generating evidence and discovery, and thereby [...]
Author(s): Mandl, Kenneth D, Kohane, Isaac S, McFadden, Douglas, Weber, Griffin M, Natter, Marc, Mandel, Joshua, Schneeweiss, Sebastian, Weiler, Sarah, Klann, Jeffrey G, Bickel, Jonathan, Adams, William G, Ge, Yaorong, Zhou, Xiaobo, Perkins, James, Marsolo, Keith, Bernstam, Elmer, Showalter, John, Quarshie, Alexander, Ofili, Elizabeth, Hripcsak, George, Murphy, Shawn N
DOI: 10.1136/amiajnl-2014-002727
Existing risk adjustment models for intensive care unit (ICU) outcomes rely on manual abstraction of patient-level predictors from medical charts. Developing an automated method for abstracting these data from free text might reduce cost and data collection times.
Author(s): Marafino, Ben J, Davies, Jason M, Bardach, Naomi S, Dean, Mitzi L, Dudley, R Adams
DOI: 10.1136/amiajnl-2014-002694
We validated an algorithm designed to identify new or prevalent users of antidepressant medications via population-based drug prescription records.
Author(s): Bobo, William V, Pathak, Jyotishman, Kremers, Hilal Maradit, Yawn, Barbara P, Brue, Scott M, Stoppel, Cynthia J, Croarkin, Paul E, St Sauver, Jennifer, Frye, Mark A, Rocca, Walter A
DOI: 10.1136/amiajnl-2014-002699