Clinical trials: Electronic Medical Records, open to volunteers
Acute Kidney Injury, Surgery Complications
Real-Time Acute Kidney Injury Perioperative Prediction Clinical Trial
This investigator-initiated, pragmatic trial evaluates whether displaying a machine learning (ML)- derived perioperative AKI risk score-alone or paired with an interruptive Best/Our Practice Advisory (BPA/OPA)-improves…
- Conditions
- Acute Kidney Injury, Surgery Complications, Anesthesia
- Trial name
- ML-AKI (NCT07604662)
- Testing
- EHR-Embedded AKI Risk Score, EHR-Embedded AKI Risk Score with Best Practice Advisory
- Where
- United States
- Volunteers
- 25,518 people, healthy volunteers welcome
- Sponsor
- University of California, San Francisco
Medical Errors, Electronic Medical Records
Pictographs for Preventing Wrong-Patient Errors in NICUs
Newborns in the neonatal intensive care unit (NICU) are at high risk for wrong-patient errors. Effective 2019, The Joint Commission requires that health systems adopt distinct methods of newborn identification as part of its…
- Trial name
- NCT03960099
- Testing
- Pictograph in Banner and Verification Alert
- Where
- 4 sites in United States
- Volunteers
- 6,250 people
- Sponsor
- Columbia University
Health Related
PCOS (Polycystic Ovarian Syndrome) Patients
The Prospective Cohort Study for PCOS Patients was set up to investigate the short- and long-term health consequences in Reproductive Medical Center, First Affiliated Hospital of Zhengzhou University, China.
- Trial name
- NCT03991507
- Where
- China
- Volunteers
- 10,000 people
- Sponsor
- The First Affiliated Hospital of Zhengzhou University
Pre Diabetes, Diabetes (DM)
Preventing Diabetes: Impact of an EMR-Based Intervention for Enhanced Pre-Diabetes Management in Primary Care
The goal of this study is to find out if adding electronic medical record (EMR) prompts helps prevent people with pre-diabetes from developing diabetes. It will also look at how these prompts affect doctor and patient behaviors.
- Trial name
- NCT07252700
- Testing
- Electronic Medical Record-Based Clinical Decision Support
- Where
- Singapore
- Volunteers
- 6,000 people
- Sponsor
- Lynette Goh
Continuity of Care, Patient Safety
Automatic Feedback Indicator to Enhance the Hospital Discharge Communication Between Acute Care and Primary Care.
This study, titled "Automated Indicator Feedback for Improving the Quality of Discharge Letters: A Cluster-Randomized Controlled Trial" (FIAQ-LS), aims to evaluate whether continuous real-time feedback to hospital teams can…
- Conditions
- Continuity of Care, Patient Safety, Hospital Discharge Communication Processes, Communication
- Trial name
- FIAQLS (NCT06835153)
- Testing
- Monthly Performance Feedback with Dashboards (Automated Audit and Feedback)
- Where
- France
- Volunteers
- 132,000 people
- Sponsor
- University Hospital, Grenoble
HIV Infections
Getting to Zero Among HHI MSM in the American South
This study will evaluate a status-neutral integrated strategy to improve access to and uptake of HIV prevention and treatment services for the highest HIV incidence (HHI) men who have sex with men (MSM) in participating…
- Trial name
- NCT05075967
- Testing
- Health Access Coalitions, Social Media, Peer Support
- Where
- United States
- Volunteers
- 2,700 people, healthy volunteers welcome
- Sponsor
- HIV Prevention Trials Network
Health Related
Newborns From Patients Treated With ART (Assisted Reproductive Technology)
The Prospective Cohort Study for Newborns from patients treated with ART was set up to investigate the short- and long-term health consequences in Reproductive Medical Center, First Affiliated Hospital of Zhengzhou University…
- Trial name
- NCT03993158
- Where
- China
- Volunteers
- 10,000 people
- Sponsor
- The First Affiliated Hospital of Zhengzhou University
Hypertension, Reproductive Behavior
The REACH-OUT Trial
Test the effectiveness of a technology-enabled strategy to optimize blood pressure among reproductive-aged women with hypertension receiving care in Federally Qualified Health Centers.
- Conditions
- Hypertension, Reproductive Behavior, Primary Health Care, Electronic Health Record
- Trial name
- NCT07540143
- Testing
- Health literacy-informed patient education materials, BP monitor, brief orientation, and portal tools, The MeDS assessment
- Where
- United States
- Volunteers
- 350 people
- Sponsor
- Northwestern University
Cancer
ACTIVATE: AI-driven Clinical-trial Trial-Information and Viability Assessment Tool for EHRs
This study aims to develop and evaluate ACTIVATE, an AI-driven tool for clinical trial information and viability assessment using electronic health records (EHRs).
- Trial name
- ACTIVATE (NCT07232043)
- Testing
- MatchMiner-AI Artificial Intelligence Tool
- Where
- United States
- Volunteers
- 70,000 people
- Sponsor
- Dana-Farber Cancer Institute
Electronic Health Records
The Role of Framing and Choice Architecture in Patients' Reactions and EHR Error Discovery and Reporting
The first goal of our research is to understand the effects of different wordings of certain messages on patients' engagement in reviewing their electronic health records (EHRs).
- Trial name
- NCT07206550
- Testing
- Framing
- Where
- United States
- Volunteers
- 3,000 people, healthy volunteers welcome
- Sponsor
- The University of Texas at Dallas
Code Status Discussions With Medical In-patients
Use of the Electronic Medical Record to Screen Code Status Preference Using Death Language
In order to systematically improve code status communication and documentation while clarifying how providers understand code status decisions, we propose the Choice of Diction's Effect Electronic Measures of Resuscitation Study…
- Trial name
- CODE-EMRS (NCT07405710)
- Testing
- Death language
- Where
- United States
- Volunteers
- 118 people, healthy volunteers welcome
- Sponsor
- Rutgers, The State University of New Jersey
Hepatitis C Virus (HCV), Hepatitis C Virus (HCV) Infection
Assessing Performance of a Hepatitis C Emergency Department (HepC-EnD) Screening Tool: IT Integration Process for Electronic Health Record System
The goal of this observational study is to develop, implement, and evaluate a machine learning algorithm-based Hepatitis C Emergency Department (HepC-EnD) screening tool for use in emergency departments (EDs) to identify patients…
- Conditions
- Hepatitis C Virus (HCV), Hepatitis C Virus (HCV) Infection, HIV (Human Immunodeficiency Virus)
- Trial name
- HepC-EnD (NCT07406490)
- Testing
- Physician-Initiated Screening (Conventional Screening), FOCUS (Universal Screening), HepC-EnD (Targeted Screening)
- Where
- 3 sites in United States
- Volunteers
- 6,466 people, healthy volunteers welcome
- Sponsor
- University of Florida
Lung Cancer, Health Screening
Deep Learning Using Chest X-Rays to Identify High Risk Patients for Lung Cancer Screening CT
The goal of this clinical trial is to evaluate whether an AI tool that alerts providers to patients at high 6-year risk of lung cancer based on their chest x-ray images will improve lung cancer screening CT participation.
- Conditions
- Lung Cancer, Health Screening, Early Cancer Detection, Deep Learning
- Trial name
- NCT06910956
- Testing
- CXR-LC
- Where
- United States
- Volunteers
- 1,500 people
- Sponsor
- Massachusetts General Hospital
Pediatric ALL, Sepsis
Evaluation of Pediatric eCART Implementation
This is a study comparing 3 years of retrospective data (pre-implementation) to 2 years of prospective data after the implementation of a pediatric version of Electronic Cardiac Arrest Risk Triage (pediatric eCART), a clinical…
- Trial name
- NCT06771830
- Testing
- Pediatric eCART
- Where
- United States
- Volunteers
- 30,000 people
- Sponsor
- University of Wisconsin, Madison
Genotype
AI-Driven Genotype Prediction Using EHR and Multimodal Data
The goal of this clinical study is to explore the potential of using electronic health records (EHR) and multimodal data (such as imaging, lab results, and clinical history) to predict a patient's genotype.
- Trial name
- NCT06791421
- Testing
- AI-Predictng Model
- Where
- 4 sites in China
- Volunteers
- 100,000 people, healthy volunteers welcome
- Sponsor
- The Eye Hospital of Wenzhou Medical University
Dialysis Patients
AI-Driven Prediction of Dialysis Outcome With EHR
This is a multi-center, clinical study designed to evaluate the application and effectiveness of an AI-assisted predictive model for outcome of dialysis patients, leveraging multimodal health data.
- Trial name
- NCT06791447
- Testing
- AI-assisted Predictive Model for Dialysis Outcomes
- Where
- China
- Volunteers
- 1,000,000 people
- Sponsor
- The Eye Hospital of Wenzhou Medical University
Human Immunodeficiency Virus, Treatment Adherence
Data Science and Qualitative Research for Decision Support in the HIV Care Cascade
The goal of this study is to determine whether clinical prediction algorithms derived using statistical machine learning methods can be used to improve patient outcomes in large HIV care programs in sub-Saharan Africa and…
- Conditions
- Human Immunodeficiency Virus, Treatment Adherence, Treatment Compliance, Patient No Show
- Trial name
- CASCADE (NCT06604663)
- Testing
- Activation of the CDSS system
- Where
- Kenya
- Volunteers
- 80,000 people
- Sponsor
- Brown University
Structural Heart Abnormality, Valve Heart Disease
Capitalizing on AI to CapTure Undiagnosed Structural Heart Disease
Doctors are testing a new tool called EchoNext to see if it can help find heart problems earlier. EchoNext looks at the heart's electrical test, called an ECG, and uses artificial intelligence (AI) to check for signs of…
- Conditions
- Structural Heart Abnormality, Valve Heart Disease, Heart Diseases, Cardiovascular Diseases
- Trial name
- CACTUS (NCT07843004)
- Testing
- EHR Alert
- Where
- United States
- Volunteers
- 4,000 people
- Sponsor
- Pierre Elias
Maternal Sepsis, Infections
EnCoRe MoMS: Engaging Communities to Reduce Morbidity From Maternal Sepsis (Aim 1)
Sepsis is the second leading cause of maternal death in the U.S. Labor and postpartum are particularly vulnerable risk periods. The goal of this multi-center, multidisciplinary study is to evaluate a maternal sepsis safety bundle.
- Trial name
- NCT06145724
- Testing
- Maternal Sepsis Safety Bundle
- Where
- 4 sites in United States
- Volunteers
- 33,183 people, healthy volunteers welcome
- Sponsor
- Columbia University
Biological Age
AI-Driven Prediction of Biological Age With EHR
This is a multi-center, retrospective clinical study designed to evaluate the application and effectiveness of an AI-assisted predictive model for predicting biological age using electronic health records (EHR).
- Trial name
- NCT06791486
- Testing
- AI-assisted predictive model
- Where
- 4 sites in China
- Volunteers
- 1,000,000 people, healthy volunteers welcome
- Sponsor
- The Eye Hospital of Wenzhou Medical University