We provide an efficient solution for mining homelessness and ACE information from EHRs, which can facilitate large clinical and genetic studies of these social determinants of health.

SUMMARY Objective Gestational diabetes (GDM) is characterized by maternal glucose intolerance that manifests during pregnancy. Because GDM resembles type 2 diabetes (T2DM), shared genetic predisposition is likely but has not been established. We tested the hypothesis that a genetic risk score (GRS) that included variants known to be associated with T2DM is associated with GDM. Study design We conducted a case-control study using the Vanderbilt Medical Center biobank (BioVU), and calculated a simple-count GRS using 34 variants previously associated with T2DM or fasting glucose in the general population, or with GDM or glucose intolerance in pregnancy. We assessed the association of the GRS with GDM adjusting for maternal age, parity, and body mass index (BMI) and calculated the area under the curve for the receiver-operating characteristic curve (c-statistic). Study population Among Caucasian women, we identified 458 cases of GDM and 1538 pregnant controls with normal glucose tolerance. Results Cases of GDM had a higher number of risk alleles compared to controls (38.9±4.0 vs. 37.4 ± 4.0 risk alleles, P=1.6x10−11). The GRS was significantly associated with GDM; the adjusted odds ratio associated with each additional risk allele was 1.10 (95% CI, 1.07-1.13, P=6x10−11). Clinical variables predicted the risk for GDM (c-statistic 0.67, 95% CI: 0.64 - 0.70), and adding the GRS modestly improved prediction (0.70, 95% CI: 0.67 - 0.73). Conclusions Among Caucasian women, a GRS that included common T2DM genetic risk variants was associated with increased risk of GDM but showed limited utility in the identification of GDM cases.

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Our findings demonstrated a strong desire among healthy people, patients with chronic diseases, and healthcare providers for a self-assessment portal that can collect patient-reported outcome metrics and deliver personalized feedback.

Objectives: To compare patient-reported social determinants of health (SDOH) to the Brokamp Area Deprivation Index (ADI), and evaluate the association of patient-reported SDOH and ADI with mortality in patients with cardiovascular disease (CVD).Design: Prospective cohort.Setting: Academic medical center.Participants: Adults with acute coronary syndrome (ACS) and/or acute exacerbation of heart failure (HF) hospitalized between 2011 and 2015.Methods: Patient-reported SDOH included: income range, education, health insurance, and household size. ADI was calculated using census tract level variables of poverty, median income, high school completion, lack of health insurance, assisted income, and vacant housing.Primary outcome: All-cause mortality, up to 5 years follow-up.Results: The sample was 60% male, 84% White, and 93% insured; mean patient-reported household income was $48,000 (SD $34,000). ADI components were significantly associated with corresponding patient-report­ed variables. In age, sex, and race adjusted Cox regression models, ADI was associated with mortality for ACS (HR 1.23, 95% CI 1.06, 1.42), but not HF (HR 1.09, 95% CI .99, 1.21). Mortality models for ACS improved with consideration of social determinants data (C-statistics: base demographic model=.612; ADI added=.644; patient-reported SDOH added=.675; both ADI and patient-reported SDOH added=.689). HF mortality models improved only slightly (C-statistics: .600, .602, .617, .620, respectively).Conclusions: The Brokamp ADI is associated with mortality in hospitalized patients with CVD. In the absence of available patient-reported data, hospitals could implement the Brokamp ADI as an approximation for patient-reported data to enhance risk stratification of patients with CVD. Ethn Dis. 2021;31(1):9-22; doi:10.18865/ed.31.1.9