The last decade has seen an exponential growth in the quantity of clinical data collected nationwide, triggering an increase in opportunities to reuse the data for biomedical research. The Vanderbilt research data warehouse framework consists of identified and de-identified clinical data repositories, fee-for-service custom services, and tools built atop the data layer to assist researchers across the enterprise. Providing resources dedicated to research initiatives benefits not only the research community, but also clinicians, patients and institutional leadership. This work provides a summary of our approach in the secondary use of clinical data for research domain, including a description of key components and a list of lessons learned, designed to assist others assembling similar services and infrastructure.

Background Acute kidney injury (AKI) has been characterized in young high-risk inpatients, in whom AKI is frequent and associated with increased mortality, morbidity, and length of stay. The incidence of AKI among patients not requiring intensive care is unknown. Study Design Retrospective cohort study Setting & Participants 13,914 noncritical admissions during 2011–2012 at our tertiary referral pediatric hospital were evaluated. Patients <28 days or >21 years of age, or with chronic kidney disease (CKD), were excluded. Admissions with ≥2 serum creatinine measurements were evaluated. Factors Demographic features, laboratory measurements, medication exposures, and length of stay. Outcome AKI defined by increased serum creatinine in accordance with KDIGO (Kidney Disease: Improving Global Outcomes) criteria. Based on time of admission, time interval requirements were met in 97% of cases, but KDIGO time window criteria were not strictly enforced to allow implementation using clinically-obtained data. Results Two or more creatinine measurements (one baseline before or during admission, and a second during admission) in 2,374 of 13,914 (17%) patients allowed for AKI evaluation. A serum creatinine difference of ≥0.3 mg/dL or ≥1.5 times baseline was seen in 722 of 2,374 (30%) patients. A minimum of 5% of all noncritical inpatients without CKD in pediatric wards have an episode of AKI during routine hospital admission. Limitations Urine output, glomerular filtration rate, and time interval criteria for AKI were not applied secondary to study design and available data. The evaluated cohort was restricted to patients with ≥2 clinically obtained serum creatinine measurements, and baseline creatinine may have been measured after the AKI episode. Conclusions AKI occurs in at least 5% of all non-critically ill hospitalized children, adolescents, and young adults without known CKD. Physicians should increase their awareness of AKI and improve surveillance strategies with serum creatinine measurements in this population so that exacerbating factors such as nephrotoxic medication exposures may be modified as indicated.

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.

The promise of drug repurposing is to accelerate the translation of knowledge to treatment of human disease, bypassing common challenges associated with drug development to be more time- and cost-efficient. Repurposing has an increased chance of success due to the previous validation of drug safety and allows for the incorporation of omics. Hypothesis-generating omics processes inform drug repurposing decision-making methods on drug efficacy and toxicity. This review summarizes drug repurposing strategies and methodologies in the context of the following omics fields: genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, phenomics, pregomics, and personomics. While each omics field has specific strengths and limitations, incorporating omics into the drug repurposing landscape is integral to its success.

Background Acute kidney injury (AKI) is common in pediatric inpatients and associated with increased morbidity, mortality, and length of stay. Early identification can reduce severity. Methods To create and validate an electronic health record (EHR)-based AKI screening tool, we generated temporally distinct development and validation cohorts using retrospective data from our tertiary care children’s hospital, including children 28 days through 21 years old with sufficient serum creatinine measurements to determine AKI status. AKI was defined as 1.5-fold or 0.3 mg/dL increase in serum creatinine. Age, medication exposures, platelet count, red blood cell distribution width, serum phosphorus, serum transaminases, hypotension (ICU only), and pH (ICU only) were included in AKI risk prediction models. Results For ICU patients, 791/1332 (59%) of the development cohort and 470/866 (54%) of the validation cohort had AKI. In external validation, the ICU prediction model had C-statistic=0.74 (95% confidence interval 0.71–0.77). For non-ICU patients, 722/2337 (31%) and 469/1474 (32%) had AKI, and the prediction model had C-statistic=0.69 (0.66–0.72). Conclusions AKI screening can be performed using EHR data. The AKI screening tool can be incorporated into EHR systems to identify high risk patients without serum creatinine data, enabling targeted laboratory testing, early AKI identification, and modification of care.