ABSTRACT
OBJECTIVE: In response to COVID-19, the informatics community united to aggregate as much clinical data as possible to characterize this new disease and reduce its impact through collaborative analytics. The National COVID Cohort Collaborative (N3C) is now the largest publicly available HIPAA limited dataset in US history with over 6.4 million patients and is a testament to a partnership of over 100 organizations. MATERIALS AND METHODS: We developed a pipeline for ingesting, harmonizing, and centralizing data from 56 contributing data partners using 4 federated Common Data Models. N3C data quality (DQ) review involves both automated and manual procedures. In the process, several DQ heuristics were discovered in our centralized context, both within the pipeline and during downstream project-based analysis. Feedback to the sites led to many local and centralized DQ improvements. RESULTS: Beyond well-recognized DQ findings, we discovered 15 heuristics relating to source Common Data Model conformance, demographics, COVID tests, conditions, encounters, measurements, observations, coding completeness, and fitness for use. Of 56 sites, 37 sites (66%) demonstrated issues through these heuristics. These 37 sites demonstrated improvement after receiving feedback. DISCUSSION: We encountered site-to-site differences in DQ which would have been challenging to discover using federated checks alone. We have demonstrated that centralized DQ benchmarking reveals unique opportunities for DQ improvement that will support improved research analytics locally and in aggregate. CONCLUSION: By combining rapid, continual assessment of DQ with a large volume of multisite data, it is possible to support more nuanced scientific questions with the scale and rigor that they require.
Subject(s)
COVID-19 , Cohort Studies , Data Accuracy , Health Insurance Portability and Accountability Act , Humans , United StatesABSTRACT
BACKGROUND: Preclinical and clinical research suggest that the α1 receptor antagonist prazosin reduces alcohol consumption. Furthermore, clinical studies indicate a role for prazosin in treating Post-Traumatic Stress Disorder (PTSD) symptoms and a recent trial suggested that pre-treatment blood pressure (BP) predicts therapeutic response for prazosin in PTSD patients. Whether pre-treatment BP may predict response to α1 blockers in alcohol-dependent (AD) patients is unknown. We previously reported a randomized controlled trial (RCT) where doxazosin, an α1 receptor antagonist with a more favorable pharmacokinetic profile than prazosin, reduced drinks per week (DPW) and heavy drinking days (HDD) in AD patients with a high family history density of alcoholism. In this study, we tested pre-treatment BP as another potentially valuable clinical moderator of doxazosin's response on alcohol consumption. METHODS: This was a double-blind placebo-controlled RCT testing doxazosin up to 16mg/day in AD treatment-seeking patients (N=41). The hypothesized moderator effect of baseline standing systolic and diastolic BP on DPW and HDD was tested. RESULTS: With pre-treatment standing diastolic BP as a moderator, there were significant BP x medication interactions for both DPW [**p=0.009, d=0.80] and HDD [*p=0.018, d=1.11]. Post-hoc analyses indicated significant doxazosin effects in patients with higher standing BP in reducing both DPW and HDD. CONCLUSION: These findings suggest that higher standing diastolic BP at baseline (pre-treatment) may represent a predictor of doxazosin's response on alcohol consumption in AD patients. These results further elucidate the possible efficacy and mechanisms of action of α1 receptor antagonism in AD individuals.