Johnie Rose1,2, Weichuan Dong3,4, Uriel Kim5,4, Joseph Hnath5, Abby Statler3,6, Paola Saroufim7, Sunah Song7, Mustafa Ascha4,7, Harry Menegay7, Ye Tian7, Mark Beno7, Siran M Koroukian3,4. 1. Case Western Reserve University Center for Community Health Integration, 11000 Cedar Ave., Ste. 402, Cleveland, OH, 44106-7136, USA. Johnie.rose@case.edu. 2. Case Comprehensive Cancer Center, Cleveland, OH, USA. Johnie.rose@case.edu. 3. Case Comprehensive Cancer Center, Cleveland, OH, USA. 4. Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA. 5. Case Western Reserve University Center for Community Health Integration, 11000 Cedar Ave., Ste. 402, Cleveland, OH, 44106-7136, USA. 6. Taussig Cancer Institute, The Cleveland Clinic Foundation, Cleveland, OH, USA. 7. Cleveland Institute for Computational Biology, Case Western Reserve University/University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
Abstract
PURPOSE: A disconnect often exists between those with the expertise to manage and analyze complex, multi-source data sets, and the clinical, social services, advocacy, and public health professionals who can pose the most relevant questions and best apply the answers. We describe development and implementation of a cancer informatics infrastructure aimed at broadening the usability of community cancer data to inform cancer control research and practice; and we share lessons learned. METHODS: We built a multi-level database known as The Ohio Cancer Assessment and Surveillance Engine (OH-CASE) to link data from Ohio's cancer registry with community data from the U.S. Census and other sources. Space-and place-based characteristics were assigned to individuals according to residential address. Stakeholder input informed development of an interface for generating queries based on geographic, demographic, and disease inputs and for outputting results aggregated at the state, county, municipality, or zip code levels. RESULTS: OH-CASE contains data on 791,786 cancer cases diagnosed from 1/1/2006 to 12/31/2018 across 88 Ohio counties containing 1215 municipalities and 1197 zip codes. Stakeholder feedback from cancer center community outreach teams, advocacy organizations, public health, and researchers suggests a broad range of uses of such multi-level data resources accessible via a user interface. CONCLUSION: OH-CASE represents a prototype of a transportable model for curating and synthesizing data to understand cancer burden across communities. Beyond supporting collaborative research, this infrastructure can serve the clinical, social services, public health, and advocacy communities by enabling targeting of outreach, funding, and interventions to narrow cancer disparities.
PURPOSE: A disconnect often exists between those with the expertise to manage and analyze complex, multi-source data sets, and the clinical, social services, advocacy, and public health professionals who can pose the most relevant questions and best apply the answers. We describe development and implementation of a cancer informatics infrastructure aimed at broadening the usability of community cancer data to inform cancer control research and practice; and we share lessons learned. METHODS: We built a multi-level database known as The Ohio Cancer Assessment and Surveillance Engine (OH-CASE) to link data from Ohio's cancer registry with community data from the U.S. Census and other sources. Space-and place-based characteristics were assigned to individuals according to residential address. Stakeholder input informed development of an interface for generating queries based on geographic, demographic, and disease inputs and for outputting results aggregated at the state, county, municipality, or zip code levels. RESULTS: OH-CASE contains data on 791,786 cancer cases diagnosed from 1/1/2006 to 12/31/2018 across 88 Ohio counties containing 1215 municipalities and 1197 zip codes. Stakeholder feedback from cancer center community outreach teams, advocacy organizations, public health, and researchers suggests a broad range of uses of such multi-level data resources accessible via a user interface. CONCLUSION: OH-CASE represents a prototype of a transportable model for curating and synthesizing data to understand cancer burden across communities. Beyond supporting collaborative research, this infrastructure can serve the clinical, social services, public health, and advocacy communities by enabling targeting of outreach, funding, and interventions to narrow cancer disparities.
Authors: Blase N Polite; Lucile L Adams-Campbell; Otis W Brawley; Nina Bickell; John M Carethers; Christopher R Flowers; Margaret Foti; Scarlett Lin Gomez; Jennifer J Griggs; Christopher S Lathan; Christopher I Li; J Leonard Lichtenfeld; Worta McCaskill-Stevens; Electra D Paskett Journal: CA Cancer J Clin Date: 2017-07-24 Impact factor: 508.702
Authors: Lucinda P Dalzell; Florence K L Tangka; David S Powers; Brett J O'Hara; Walter Holmes; Kristy Joseph; Janet Royalty Journal: Cancer Causes Control Date: 2015-04-28 Impact factor: 2.506