Multi-source development of an integrated model for family health history

Author:

Chen Elizabeth S123,Carter Elizabeth W1,Winden Tamara J45,Sarkar Indra Neil136,Wang Yan4,Melton Genevieve B47

Affiliation:

1. Center for Clinical and Translational Science—Biomedical Informatics Unit, University of Vermont, Burlington, Vermont, USA

2. Department of Medicine—Division of General Internal Medicine, University of Vermont, Burlington, Vermont, USA

3. Department of Computer Science, University of Vermont, Burlington, Vermont, USA

4. Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA

5. Division of Applied Research, Allina Health, Minneapolis, Minnesota, USA

6. Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, Vermont, USA

7. Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA

Abstract

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.

Funder

National Library of Medicine of the National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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