Health Services Research & Development

Veterans Crisis Line Badge
Go to the ORD website
Go to the QUERI website

HSR&D Citation Abstracts

Search | Search by Center | Search by Source | Keywords in Title

Wu RR, Myers RA, Buchanan AH, Dimmock D, Fulda KG, Haller IV, Haga SB, Harry ML, McCarty C, Neuner J, Rakhra-Burris T, Sperber N, Voils CI, Ginsburg GS, Orlando LA. Effect of Sociodemographic Factors on Uptake of a Patient-Facing Information Technology Family Health History Risk Assessment Platform. Applied clinical informatics. 2019 Mar 13; 10(2):180-188.
PubMed logo Search for Abstract from PubMed
(This link leaves the website of VA HSR&D.)


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 (-value?=?0.005), more educated (-value?=?0.004), non-Asian (-value?=?0.009), and female (-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.