Elizabeth S Chen1, Elizabeth W Carter2, Tamara J Winden3, Indra Neil Sarkar4, Yan Wang5, Genevieve B Melton6. 1. Center for Clinical and Translational Science-Biomedical Informatics Unit, University of Vermont, Burlington, Vermont, USA Department of Medicine-Division of General Internal Medicine, University of Vermont, Burlington, Vermont, USA Department of Computer Science, University of Vermont, Burlington, Vermont, USA. 2. Center for Clinical and Translational Science-Biomedical Informatics Unit, University of Vermont, Burlington, Vermont, USA. 3. Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA Division of Applied Research, Allina Health, Minneapolis, Minnesota, USA. 4. Center for Clinical and Translational Science-Biomedical Informatics Unit, University of Vermont, Burlington, Vermont, USA Department of Computer Science, University of Vermont, Burlington, Vermont, USA Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, Vermont, USA. 5. Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA. 6. Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.
Abstract
OBJECTIVE: To integrate data elements from multiple sources for informing comprehensive and standardized collection of family health history (FHH). MATERIALS AND METHODS: Three types of sources were analyzed to identify data elements associated with the collection of FHH. First, clinical notes from multiple resources were annotated for FHH information. Second, questions and responses for family members in patient-facing FHH tools were examined. Lastly, elements defined in FHH-related specifications were extracted for several standards development and related organizations. Data elements identified from the notes, tools, and specifications were subsequently combined and compared. RESULTS: In total, 891 notes from three resources, eight tools, and seven specifications associated with four organizations were analyzed. The resulting Integrated FHH Model consisted of 44 data elements for describing source of information, family members, observations, and general statements about family history. Of these elements, 16 were common to all three source types, 17 were common to two, and 11 were unique. Intra-source comparisons also revealed common and unique elements across the different notes, tools, and specifications. DISCUSSION: Through examination of multiple sources, a representative and complementary set of FHH data elements was identified. Further work is needed to create formal representations of the Integrated FHH Model, standardize values associated with each element, and inform context-specific implementations. CONCLUSIONS: There has been increased emphasis on the importance of FHH for supporting personalized medicine, biomedical research, and population health. Multi-source development of an integrated model could contribute to improving the standardized collection and use of FHH information in disparate systems.
OBJECTIVE: To integrate data elements from multiple sources for informing comprehensive and standardized collection of family health history (FHH). MATERIALS AND METHODS: Three types of sources were analyzed to identify data elements associated with the collection of FHH. First, clinical notes from multiple resources were annotated for FHH information. Second, questions and responses for family members in patient-facing FHH tools were examined. Lastly, elements defined in FHH-related specifications were extracted for several standards development and related organizations. Data elements identified from the notes, tools, and specifications were subsequently combined and compared. RESULTS: In total, 891 notes from three resources, eight tools, and seven specifications associated with four organizations were analyzed. The resulting Integrated FHH Model consisted of 44 data elements for describing source of information, family members, observations, and general statements about family history. Of these elements, 16 were common to all three source types, 17 were common to two, and 11 were unique. Intra-source comparisons also revealed common and unique elements across the different notes, tools, and specifications. DISCUSSION: Through examination of multiple sources, a representative and complementary set of FHH data elements was identified. Further work is needed to create formal representations of the Integrated FHH Model, standardize values associated with each element, and inform context-specific implementations. CONCLUSIONS: There has been increased emphasis on the importance of FHH for supporting personalized medicine, biomedical research, and population health. Multi-source development of an integrated model could contribute to improving the standardized collection and use of FHH information in disparate systems.
Authors: Jyotishman Pathak; Kent R Bailey; Calvin E Beebe; Steven Bethard; David C Carrell; Pei J Chen; Dmitriy Dligach; Cory M Endle; Lacey A Hart; Peter J Haug; Stanley M Huff; Vinod C Kaggal; Dingcheng Li; Hongfang Liu; Kyle Marchant; James Masanz; Timothy Miller; Thomas A Oniki; Martha Palmer; Kevin J Peterson; Susan Rea; Guergana K Savova; Craig R Stancl; Sunghwan Sohn; Harold R Solbrig; Dale B Suesse; Cui Tao; David P Taylor; Les Westberg; Stephen Wu; Ning Zhuo; Christopher G Chute Journal: J Am Med Inform Assoc Date: 2013-11-04 Impact factor: 4.497
Authors: Sripriya Rajamani; Elizabeth S Chen; Elizabeth Lindemann; Ranyah Aldekhyyel; Yan Wang; Genevieve B Melton Journal: J Am Med Inform Assoc Date: 2018-02-01 Impact factor: 4.497
Authors: Elizabeth S Chen; Genevieve B Melton; Richard C Wasserman; Paul T Rosenau; Diantha B Howard; Indra Neil Sarkar Journal: AMIA Annu Symp Proc Date: 2015-11-05
Authors: Genevieve B Melton; Yan Wang; Elliot Arsoniadis; Serguei V S Pakhomov; Terrence J Adam; Mary R Kwaan; David A Rothenberger; Elizabeth S Chen Journal: Stud Health Technol Inform Date: 2015