Transforming consumer health informatics: connecting CHI applications to the health-IT ecosystem.
Author(s): Marceglia, Sara, Fontelo, Paul, Ackerman, Michael J
DOI: 10.1093/jamia/ocu030
Author(s): Marceglia, Sara, Fontelo, Paul, Ackerman, Michael J
DOI: 10.1093/jamia/ocu030
To integrate data elements from multiple sources for informing comprehensive and standardized collection of family health history (FHH).
Author(s): Chen, Elizabeth S, Carter, Elizabeth W, Winden, Tamara J, Sarkar, Indra Neil, Wang, Yan, Melton, Genevieve B
DOI: 10.1136/amiajnl-2014-003092
This research identifies specific care coordination activities used by Aging in Place (AIP) nurse care coordinators and home healthcare (HHC) nurses when coordinating care for older community-dwelling adults and suggests a method to quantify care coordination.
Author(s): Popejoy, Lori L, Khalilia, Mohammed A, Popescu, Mihail, Galambos, Colleen, Lyons, Vanessa, Rantz, Marilyn, Hicks, Lanis, Stetzer, Frank
DOI: 10.1136/amiajnl-2014-002702
We developed and implemented a 'CPOE-QT Alert' system, that is, clinical decision support integrated in the computerized physician order entry system (CPOE), in 2011. The system identifies any attempts to order medications with risk of torsade de pointes (TdP) for patients with a history of significant QT prolongation (QTc ≥500 ms) and alerts the provider entering the order. We assessed its impact by comparing orders and subsequent medication administration before [...]
Author(s): Sorita, Atsushi, Bos, J Martijn, Morlan, Bruce W, Tarrell, Robert F, Ackerman, Michael J, Caraballo, Pedro J
DOI: 10.1136/amiajnl-2014-002896
The high level of stress associated with caring for others with medical conditions has been recognized for some time. Reducing caregiver stress can improve caregiver quality of life as well as improve the care they provide to loved ones. This systematic review assesses the effectiveness of internet-based interventions to decrease caregiver stress.
Author(s): Hu, Chunling, Kung, Simon, Rummans, Teresa A, Clark, Matthew M, Lapid, Maria I
DOI: 10.1136/amiajnl-2014-002817
To direct online users searching for gynecologic cancer information to accurate content, the Centers for Disease Control and Prevention's (CDC) 'Inside Knowledge: Get the Facts About Gynecologic Cancer' campaign sponsored search engine advertisements in English and Spanish. From June 2012 to August 2013, advertisements appeared when US Google users entered search terms related to gynecologic cancer. Users who clicked on the advertisements were directed to relevant content on the CDC [...]
Author(s): Cooper, Crystale Purvis, Gelb, Cynthia A, Vaughn, Alexandra N, Smuland, Jenny, Hughes, Alexandra G, Hawkins, Nikki A
DOI: 10.1136/amiajnl-2014-002701
Despite effective therapies for many conditions, patients find it difficult to adhere to prescribed treatments. Technology-mediated interventions (TMIs) are increasingly being used with the hope of improving adherence.
Author(s): Mistry, Niraj, Keepanasseril, Arun, Wilczynski, Nancy L, Nieuwlaat, Robby, Ravall, Manthan, Haynes, R Brian, ,
DOI: 10.1093/jamia/ocu047
Author(s): Valdez, Rupa S, Holden, Richard J, Novak, Laurie L, Veinot, Tiffany C
DOI: 10.1093/jamia/ocu031
In alignment with a major shift toward patient-centered care as the model for improving care in our health system, informatics is transforming patient-provider relationships and overall care delivery. AMIA's 2013 Health Policy Invitational was focused on examining existing challenges surrounding full engagement of the patient and crafting a research agenda and policy framework encouraging the use of informatics solutions to achieve this goal. The group tackled this challenge from educational [...]
Author(s): Brennan, Patti Flatley, Valdez, Rupa, Alexander, Greg, Arora, Shifali, Bernstam, Elmer V, Edmunds, Margo, Kirienko, Nikolai, Martin, Ross D, Sim, Ida, Skiba, Diane, Rosenbloom, Trent
DOI: 10.1136/amiajnl-2014-003176
Radiology reports are usually narrative, unstructured text, a format which hinders the ability to input report contents into decision support systems. In addition, reports often describe multiple lesions, and it is challenging to automatically extract information on each lesion and its relationships to characteristics, anatomic locations, and other information that describes it. The goal of our work is to develop natural language processing (NLP) methods to recognize each lesion in [...]
Author(s): Bozkurt, Selen, Lipson, Jafi A, Senol, Utku, Rubin, Daniel L
DOI: 10.1136/amiajnl-2014-003009