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The purpose of this research is to collect blood and urine from adult patients admitted to an intensive care unit. This is to assess the performance of the ProNephro AKI (NGAL) assay (lab test) as an aid to identify patients at risk for acute kidney injury.
Emergency Medicine Cardiovascular Risk Assessment for Lipid Disorders (EMERALD) is a protocolized intervention based on American College of Cardiology/American Heart Association and US Preventive Services Task Force guidelines designed to initiate preventive cardiovascular care for emergency department patients being evaluated for acute coronary syndrome. The overarching goals of this proposal are to (1) determine the efficacy of EMERALD at lowering low-density lipoprotein cholesterol (LDL-C) and non high-density lipoprotein cholesterol (non-HDL-C) among at-risk Emergency Department (ED) patients who are not already receiving guideline-directed outpatient preventive care and (2) inform our understanding of patient adherence and determinants of implementation for ED-based cardiovascular disease prevention strategies.
This clinical trial evaluates the usefulness of various risk assessment tests, including Helicobacter pylori (H. pylori) breath testing, questionnaires, and endoscopies for identifying participants at high risk for stomach cancer. H. pylori is a bacteria that causes stomach inflammation and ulcers in the stomach. People with H. pylori infections may be more likely to develop cancer in the stomach. H. pylori breath testing can help identify the presence of H. pylori infection in a participant and help identify if the participant may be at a higher risk of developing stomach cancer. An endoscopy uses a thin, flexible lighted tube that is inserted inside the esophagus, stomach, and first part of the small intestine. This allows the doctor to see and look for abnormal areas that may need to be biopsied. Risk assessment including H. pylori evaluation, questionnaires, and endoscopies may help identify participants at high risk for stomach cancer and may be a useful screening tool for earlier stomach cancer diagnosis.
Electronic health records (EHRs) are an increasingly common source for populating risk models, but whether used to populate validated risk assessment models or to de-facto build risk prediction models, EHR data presents several challenges. The purpose of this study is to assess how the integration of patient generated health data (PGHD) and EHR data can generate more accurate risk prediction models, advance personalized cancer prevention, improve digital access to health data in an equitable manner, and advance policy goals for Patient Generated Health Data (PGHD) and EHR interoperability.
This study evaluates whether adding a polygenic risk score evaluation to standard breast cancer risk assessment tools helps African American and Hispanic women make more informed decisions about accepting additional breast cancer screening and prevention strategies. Traditional breast cancer risk assessments rely mostly on the presence of standard clinical risk factors including family history, reproductive history, and mammographic breast density. This information can be combined with validated risk estimation models to provide a measure of a patient's 10 year and lifetime risk for breast cancer. A polygenic risk score helps to estimate breast cancer risk in a more individualized way by evaluating a patient's genetics. Adding a polygenic risk score evaluation to traditional screening techniques may help minority women make more informed decisions about screening and prevention strategies for breast cancer.
This goal of this observational study is to develop and test the Opioid Risk Reduction Clinical Decision Support (ORRCDS) tool. The tool will be an opioid medication risk screener and decision support platform that will be used by pharmacists upon dispensing prescription opioid medication. Once the Opioid Risk Reduction has been developed, we will examine the impact of the ORRCDS within two divisions of a large chain retail pharmacy. Pharmacies will be randomized to using the Opioid Risk Reduction Clinical Decision Support (ORRCDS) tool or standard of care opioid dispensation. We hypothesize that patients at pharmacies randomized to the ORRCDS tool will be more likely to reduce their risk status to low or moderate compared to the patients at standard of care pharmacies.
To learn whether a new imaging technology, Contrast-Enhanced Mammography (CEM), compared to standard mammography, can better detect breast cancers in women with dense breasts
In this study, the investigators aim to compare a mobile health platform, known as a 'chatbot,' that leverages artificial intelligence and natural language processing to scale communication, to 'usual care' that patients would receive. This comparison will enable the investigators to determine if the chatbot system can improve rates of recommendation for genetic testing among patients at elevated risk of harboring a familial cancer syndrome in an all-Medicaid gynecology clinic. Furthermore, the investigators aim to evaluate facilitators of inequity in regard to patient access to and utilization of genetic testing services.
The purpose of this study is to develop and validate methods to use hearing aids equipped with embedded sensors and artificial intelligence to assist in the assessment of fall risk and in the implementation of interventions aimed at reducing the risk of falling, as well as to improve speech intelligibility in quiet and in background noise, track physical activity, and social engagement. The investigators hope is that the knowledge that is generated through this study will ultimately translate to the clinical setting and will help reduce the likelihood that individuals experience a fall, and improve the quality of hearing in individuals who wear hearing aids.
Condition: Prostate cancer Intervention: Biopsy and inherited risk assessment