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Open Access Research article

Quality of family history collection with use of a patient facing family history assessment tool

R Ryanne Wu123*, Tiffany L Himmel2, Adam H Buchanan4, Karen P Powell5, Elizabeth R Hauser67, Geoffrey S Ginsburg2, Vincent C Henrich5 and Lori A Orlando23

Author Affiliations

1 Health Services Research and Development, Department of Veteran Affairs Medical Center, 411 W. Chapel Hill St., Ste 600, Durham, NC 27701, USA

2 Duke Center for Personalized and Precision Medicine, Institute of Genome Science & Policy, Duke University, 2111 Ciemas, 101 Science Dr., DUMC Box 3382, Durham, NC 27708, USA

3 Duke Department of Internal Medicine, Duke University Health System, Durham, NC, USA

4 Duke Cancer Institute, Duke University Health System, Seeley Mudd Building, 10 Bryan Searle Drive, DUMC Box 3917, Durham, NC 27710, USA

5 Center for Biotechnology, Genomics and Health Research, UNC-Greensboro, 3701 Moore Humanities and Research Administration Building, 1111 Spring Garden Street, Greensboro, NC 27412, USA

6 CSP Epidemiology Center, Department of Veteran Affairs Medical Center, 411 W. Chapel Hill St., Ste 700, Durham, NC 27701, USA

7 Center for Human Genetics, DUMC, Duke University, Box 3445, Durham, NC 27710, USA

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BMC Family Practice 2014, 15:31  doi:10.1186/1471-2296-15-31

Published: 13 February 2014

Abstract

Background

Studies have shown that the quality of family health history (FHH) collection in primary care is inadequate to assess disease risk. To use FHH for risk assessment, collected data must have adequate detail. To address this issue, we developed a patient facing FHH assessment tool, MeTree. In this paper we report the content and quality of the FHH collected using MeTree.

Methods

Design: A hybrid implementation-effectiveness study. Patients were recruited from 2009 to 2012. Setting: Two community primary care clinics in Greensboro, NC. Participants: All non-adopted adult English speaking patients with upcoming appointments were invited to participate. Intervention: Education about and collection of FHH with entry into MeTree. Measures: We report the proportion of pedigrees that were high-quality. High-quality pedigrees are defined as having all the following criteria: (1) three generations of relatives, (2) relatives’ lineage, (3) relatives’ gender, (4) an up-to-date FHH, (5) pertinent negatives noted, (6) age of disease onset in affected relatives, and for deceased relatives, (7) the age and (8) cause of death (Prim Care31:479–495, 2004.).

Results

Enrollment: 1,184. Participant demographics: age range 18-92 (mean 58.8, SD 11.79), 56% male, and 75% white. The median pedigree size was 21 (range 8-71) and the FHH entered into MeTree resulted in a database of 27,406 individuals. FHHs collected by MeTree were found to be high quality in 99.8% (N = 1,182/1,184) as compared to <4% at baseline. An average of 1.9 relatives per pedigree (range 0-50, SD 4.14) had no data reported. For pedigrees where at least one relative has no data (N = 497/1,184), 4.97 relatives per pedigree (range 1-50, SD 5.44) had no data. Talking with family members before using MeTree significantly decreased the proportion of relatives with no data reported (4.98% if you talked to your relative vs. 10.85% if you did not, p-value < 0.001.).

Conclusion

Using MeTree improves the quantity and quality of the FHH data that is collected and talking with relatives prior to the collection of FHH significantly improves the quantity and quality of the data provided. This allows more patients to be accurately risk stratified and offered appropriate preventive care guided by their risk level.

Trial number

NCT01372553

Keywords:
Family history; Data quality; Patient-centered