Grid-Enabled Measures
Grid-Enabled Measures (GEM) is an initiative of the National Institutes of Health (NIH) National Cancer Institute (NCI). GEM is a web-based collaborative platform and database enabling researchers to exchange harmonized data about behavioral constructs, measures, and datasets.[1][2]
GEM has two goals: 1) "Promote use of standardized measures which are tied to theoretically based constructs" and 2) "Facilitate sharing of harmonized data resulting from the use of standardized measures".[1] GEM has been proposed as part of the solution to the problem of tracking constructs in electronic medical records[3] and for control of construct proliferation.[4]
GEM has been recognized in the academic literature as an instantiation of cyberinfrastructure for research standardization,[5] a tool for dialogue and consensus building,[6] a tool to facilitate use of linked data and interoperable data systems,[7] and in case reports of expert panel measure categorizations.[8] The GEM database, uses “web 2.0” functionality to solicit, comment, vet, and select measures from the behavioral and population science communities in open and transparent ways.[1] Scientists are taking advantage of information sharing and collaboration made possible by networking technologies. This new phenomenon is referred to by some as Science 2.0.[1] As Science 2.0[9] gains momentum in the science community, giving a glimpse of future scientific publishing and data sharing, the GEM database is distinct in that it uses these functionalities to help scientists facilitate discovery in a massively connected and participative environment.
References
- 1 2 3 4 Moser, Richard P.; Hesse, Bradford W.; Shaikh, Abdul R.; Courtney, Paul; Morgan, Glen; Augustson, Erik, Kobrin, Sarah; Levin, Kerry; Helba, Christina; Garner, David; Dunn, Marsha; Coa, Kisha (2011). "Grid-Enabled Measures: Using Science 2.0 to Standardize Measures and Share Data". American Journal of Preventative Medicine 40 (5): 1532–1534.
- ↑ Rabin, Borsika A.; Purcell, Peyton; Naveed, Sana; Moser, Richard P.; Henton, Michelle D.; Proctor, Enola K.; Brownson, Ross C.; Glasgow, Rusell. "Advancing the application, quality and harmonization of implementation science measures". Implementation Science 7: 1–11. doi:10.1186/1748-5908-7-119.
- ↑ Glasgow, Russell E.; Kaplan, Robert M.; Ockene, Judith K.; Fisher, Edwin B.; Emmons, Karen M. (March 2012). "Patient-Reported Measures Of Psychosocial Issues And Health Behavior Should Be Added To Electronic Health Records". Health Affairs 31 (3): 497–504. doi:10.1377/hlthaff.2010.1295.
- ↑ Larsen, Kai R.; Voronovich, Zoya A.; Cook, Paul F.; Pedro, Leli W. (2013). "Addicted to constructs: science in reverse?". Addiction 108 (9): 1532–1534. doi:10.1111/add.12227.
- ↑ Shaikh, Abdul R.; Prabhu Das, Irene; Vinson, Cynthia A.; Spring, Bonnie. "Cyberinfrastructure for consumer health". American Journal of Preventive Medicine 40 (5): S91–S96. doi:10.1016/j.amepre.2011.02.012.
- ↑ Parry, Carla; Kent, Erin E.; Forsythe, Laura P.; Alfano, Cathering M.; Rowland, Julia H. "Can't see the forest for the care plan: a call to revisit the context of care planning". Journal of Clinical Oncology 31 (21): 2651–2653. doi:10.1200/jco.2012.48.4618.
- ↑ Aberethy, Amy P.; Wheeler, Jane L.; Courtney, Paul K.; Keefe, Francies J. "Supporting implementation of evidence-based behavioral interventions: the role of data liquidity in facilitating translational behavioral medicine". Translational Behavioral Medicine 1 (1): 45–52. doi:10.1007/s13142-011-0024-4.
- ↑ Tai, Betty; Boyle, Maureen; Ghitza, Udi; Kaplan, Robert M.; Clark, H. Wesley; Gersing, Kenneth. "Meaningful Use of Electronic Behavioral Health data in Primary Health Care". Science Translational Medicine 4 (119): 1–3. doi:10.1126/scitranslmed.3003324.
- ↑ Burke, Adrienne. "From open-access journals to research-review blogs, networked knowledge has made science more accessible to more people around the globe than we could have imagined 20 years ago". Seedmagazine.com. Retrieved 10 February 2015.