Appl Clin Inform 2019; 10(02): 180-188
DOI: 10.1055/s-0039-1679926
Research Article
Georg Thieme Verlag KG Stuttgart · New York

Effect of Sociodemographic Factors on Uptake of a Patient-Facing Information Technology Family Health History Risk Assessment Platform

R. Ryanne Wu
1  Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
2  Durham VA Cooperative Studies Program Epidemiology Center, Durham, North Carolina, United States
,
Rachel A. Myers
1  Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
,
Adam H. Buchanan
3  Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, United States
,
David Dimmock
4  Rady Children's Institute for Genomic Medicine, San Diego, California, United States
,
Kimberly G. Fulda
5  The North Texas Primary Care Practice-Based Research Network and Family Medicine, University of North Texas Health Science Center, Fort Worth, Texas, United States
,
Irina V. Haller
6  Essentia Institute of Rural Health, Essentia, Duluth, Minnesota, United States
,
Susanne B. Haga
1  Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
,
Melissa L. Harry
6  Essentia Institute of Rural Health, Essentia, Duluth, Minnesota, United States
,
Catherine McCarty
7  University of Minnesota Medical School, Duluth Campus, Duluth, Minnesota, United States
,
Joan Neuner
8  Department of Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin, United States
9  Center for Patient Care and Outcomes Research, Medical College of Wisconsin, Milwaukee, Wisconsin, United States
,
Teji Rakhra-Burris
1  Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
,
Nina Sperber
1  Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
10  Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, United States
11  Durham VA Health Services & Development Service, Durham, North Carolina, United States
,
Corrine I. Voils
12  William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin, United States
13  Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States
,
Geoffrey S. Ginsburg
1  Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
,
Lori A. Orlando
1  Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
› Institutsangaben
Funding This study was funded by NIH (NCT01956773). The funder had no involvement in the design, conduct, data collection, analysis, or manuscript preparation. C. Voils' effort on this study was supported by a Research Career Scientist award from the Department of Veterans Affairs (RCS 14–443). This study was approved by the IRBs of all four participating institutions and the funders.
Weitere Informationen

Publikationsverlauf

07. November 2018

18. Januar 2019

Publikationsdatum:
13. März 2019 (online)

Abstract

Objective Investigate sociodemographic differences in the use of a patient-facing family health history (FHH)-based risk assessment platform.

Methods In this large multisite trial with a diverse patient population, we evaluated the relationship between sociodemographic factors and FHH health risk assessment uptake using an information technology (IT) platform. The entire study was administered online, including consent, baseline survey, and risk assessment completion. We used multivariate logistic regression to model effect of sociodemographic factors on study progression. Quality of FHH data entered as defined as relatives: (1) with age of onset reported on relevant conditions; (2) if deceased, with cause of death and (3) age of death reported; and (4) percentage of relatives with medical history marked as unknown was analyzed using grouped logistic fixed effect regression.

Results A total of 2,514 participants consented with a mean age of 57 and 10.4% minority. Multivariate modeling showed that progression through study stages was more likely for younger (p-value = 0.005), more educated (p-value = 0.004), non-Asian (p-value = 0.009), and female (p-value = 0.005) participants. Those with lower health literacy or information-seeking confidence were also less likely to complete the study. Most significant drop-out occurred during the risk assessment completion phase. Overall, quality of FHH data entered was high with condition's age of onset reported 87.85%, relative's cause of death 85.55% and age of death 93.76%, and relative's medical history marked as unknown 19.75% of the time.

Conclusion A demographically diverse population was able to complete an IT-based risk assessment but there were differences in attrition by sociodemographic factors. More attention should be given to ensure end-user functionality of health IT and leverage electronic medical records to lessen patient burden.

Note

The views are those of the authors and do not reflect the Department of Veterans Affairs or United States Government.


Protection of Human and Animal Subjects

This study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects, and was reviewed by the institutional review boards of all four participating health care systems (Duke, Essentia, MCW, and UNTHSC).