PCORnet: turning a dream into reality.
Author(s): Collins, Francis S, Hudson, Kathy L, Briggs, Josephine P, Lauer, Michael S
DOI: 10.1136/amiajnl-2014-002864
Author(s): Collins, Francis S, Hudson, Kathy L, Briggs, Josephine P, Lauer, Michael S
DOI: 10.1136/amiajnl-2014-002864
The Mid-South Clinical Data Research Network (CDRN) encompasses three large health systems: (1) Vanderbilt Health System (VU) with electronic medical records for over 2 million patients, (2) the Vanderbilt Healthcare Affiliated Network (VHAN) which currently includes over 40 hospitals, hundreds of ambulatory practices, and over 3 million patients in the Mid-South, and (3) Greenway Medical Technologies, with access to 24 million patients nationally. Initial goals of the Mid-South CDRN include [...]
Author(s): Rosenbloom, S Trent, Harris, Paul, Pulley, Jill, Basford, Melissa, Grant, Jason, DuBuisson, Allison, Rothman, Russell L
DOI: 10.1136/amiajnl-2014-002745
The Kaiser Permanente & Strategic Partners Patient Outcomes Research To Advance Learning (PORTAL) network engages four healthcare delivery systems (Kaiser Permanente, Group Health Cooperative, HealthPartners, and Denver Health) and their affiliated research centers to create a new national network infrastructure that builds on existing relationships among these institutions. PORTAL is enhancing its current capabilities by expanding the scope of the common data model, paying particular attention to incorporating patient-reported data [...]
Author(s): McGlynn, Elizabeth A, Lieu, Tracy A, Durham, Mary L, Bauck, Alan, Laws, Reesa, Go, Alan S, Chen, Jersey, Feigelson, Heather Spencer, Corley, Douglas A, Young, Deborah Rohm, Nelson, Andrew F, Davidson, Arthur J, Morales, Leo S, Kahn, Michael G
DOI: 10.1136/amiajnl-2014-002746
The Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN) represents an unprecedented collaboration across diverse healthcare institutions including private, county, and state hospitals and health systems, a consortium of Federally Qualified Health Centers, and two Department of Veterans Affairs hospitals. CAPriCORN builds on the strengths of our institutions to develop a cross-cutting infrastructure for sustainable and patient-centered comparative effectiveness research in Chicago. Unique aspects include collaboration with the University HealthSystem Consortium [...]
Author(s): Kho, Abel N, Hynes, Denise M, Goel, Satyender, Solomonides, Anthony E, Price, Ron, Hota, Bala, Sims, Shannon A, Bahroos, Neil, Angulo, Francisco, Trick, William E, Tarlov, Elizabeth, Rachman, Fred D, Hamilton, Andrew, Kaleba, Erin O, Badlani, Sameer, Volchenboum, Samuel L, Silverstein, Jonathan C, Tobin, Jonathan N, Schwartz, Michael A, Levine, David, Wong, John B, Kennedy, Richard H, Krishnan, Jerry A, Meltzer, David O, Collins, John M, Mazany, Terry, ,
DOI: 10.1136/amiajnl-2014-002827
Understanding population-level health trends is essential to effectively monitor and improve public health. The Office of the National Coordinator for Health Information Technology (ONC) Query Health initiative is a collaboration to develop a national architecture for distributed, population-level health queries across diverse clinical systems with disparate data models. Here we review Query Health activities, including a standards-based methodology, an open-source reference implementation, and three pilot projects.
Author(s): Klann, Jeffrey G, Buck, Michael D, Brown, Jeffrey, Hadley, Marc, Elmore, Richard, Weber, Griffin M, Murphy, Shawn N
DOI: 10.1136/amiajnl-2014-002707
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2014-002666
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
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
Electronic health records (EHRs) must support primary care clinicians and patients, yet many clinicians remain dissatisfied with their system. This article presents a consensus statement about gaps in current EHR functionality and needed enhancements to support primary care. The Institute of Medicine primary care attributes were used to define needs and meaningful use (MU) objectives to define EHR functionality. Current objectives remain focused on disease rather than the whole person [...]
Author(s): Krist, Alex H, Beasley, John W, Crosson, Jesse C, Kibbe, David C, Klinkman, Michael S, Lehmann, Christoph U, Fox, Chester H, Mitchell, Jason M, Mold, James W, Pace, Wilson D, Peterson, Kevin A, Phillips, Robert L, Post, Robert, Puro, Jon, Raddock, Michael, Simkus, Ray, Waldren, Steven E
DOI: 10.1136/amiajnl-2013-002229
To evaluate factors affecting performance of influenza detection, including accuracy of natural language processing (NLP), discriminative ability of Bayesian network (BN) classifiers, and feature selection.
Author(s): Ye, Ye, Tsui, Fuchiang Rich, Wagner, Michael, Espino, Jeremy U, Li, Qi
DOI: 10.1136/amiajnl-2013-001934