Grants Awarded and Case Studies

Learn more about the Foundation's work to support patient safety research and educational training in these case studies:

• Identifying and Mitigating Patient Safety Risks Associated With Telehealth Referrals
• Using Artificial Intelligence to Assess Surgeon Performance in Cataract Procedures
• Rescuing Patients From Operating Room Complications
• Engaging Patients, Families, and Caregivers in Safety Reporting
• Training the Next Generation of Patient Safety Leaders
• Teaching Medical Students to Reduce Diagnostic Error
• Taking Action to Improve Root Cause Analysis
• Improving Care Through Physicians’ Communication Skills

Foundation Grant Recipients

2023 Grants

• Firearm Storage Maps as a Clinical Tool to Prevent Suicide: To support the creation of maps indicating temporary gun storage options in regions surrounding four Minnesota primary care clinics and incorporate these maps into physician firearm safety counseling to at-risk patients at each site (Protect Minnesota, Minneapolis)
• Forum on Advancing Diagnostic Excellence: To develop, implement, disseminate, and monitor innovations to improve diagnosis in healthcare, with emphasis on conditions and populations at highest risk of harm from diagnostic errors (National Academies of Sciences, Engineering, and Medicine, Washington, DC)
• Improving Pediatric Emergency Care Access With an Integrated Telemedicine Solution: To support the initial efforts, starting with one hospital, to understand the feasibility of implementing a pediatric telehealth platform integrating a telemedicine intervention into community emergency departments (UCSF Benioff Children’s Hospitals, San Francisco)
• Is There an Increased Incidence of Lymphedema After IV Placement? A Prospective Analysis Utilizing ICG Fluoroscopy in Patients at Risk for Arm Lymphedema: To provide objective data to contest the long-standing belief that patients who are at risk for upper extremity lymphedema should not receive blood draws or IV access from that arm or hand (City of Hope, Duarte, California)
• Reducing Medication Ordering Errors Through Indications-Based Prescribing: To develop a randomized controlled trial to assess the effectiveness of indications-based order set for reducing antimicrobial ordering errors (Columbia University, City of New York)
• The Obvious Solution Is the Midline: To collect real-time occurrence of complications, including local extravasations, infections, and deep venous thrombosis on all patients with CVCs or midline catheters, allowing a safety comparison of midline catheter to CVC use (University of Maryland, Baltimore)

2022 Grants

• Reinventing Fall Risk Assessment Tools and Clinical Decision Making Through Data: To develop a tool that is automated, standardized, individualized, dynamic, and can be integrated into nursing and physician workflows (Johns Hopkins University)
• Reducing Infections in Post-Surgical Events (RISE): To support the creation of a tool that will increase the efficiency of infection preventionists who are working to detect surgical site infection events (UMass Memorial Health Care)
• OR Crisis Checklists, Second Generation: To support the improved capacity of clinicians to rescue patients from complications and to minimize the resultant harm (Ariadne Labs, a joint center for health systems innovation at Brigham and Women’s Hospital and the Harvard T.H. Chan School of Public Health)
• Immersive Medical and Nursing Education and Simulation for Trainees: Using a HoloPatient to teach bedside procedures to support the development of a procedural training platform that will drive hands-on skill development (University of Michigan)

2021 Grants

• Assessing Surgical Competency Through Automated AI-Powered Surgical Video Analysis: To develop and implement an artificial intelligence (AI) system that evaluates cataract surgeon performance through automated analysis (University of Michigan)
• Enhanced Diagnostic Reasoning (eDRx): To address the need to boost emergency department trainee diagnostic reasoning skills through ambient and artificial intelligence (University of Michigan)
• Identifying and Mitigating Patient Safety Risks Associated with Referrals from Telehealth to In-Person Care: To support a comprehensive analysis to identify telehealth referral risks and develop a rigorous assessment tool to help facilities mitigate risks during the referral process (MedStar Health Research Institute)
• Implementation of an All-Cause Deterioration Model for Adult Inpatients: To support the implementation of PICTURE (Predicting Inpatient Acute Care Transfers and Other UnfoReseen Events), an early warning system that predicts patient deterioration, into the clinical workflow (University of Michigan)

2020 Grants

• An intuitive, nonintrusive approach to reduce patient harm from inappropriate dosing of high-risk drugs in older adult patients across an urban safety net hospital system (Icahn School of Medicine at Mount Sinai and NYC Health + Hospitals)
• Immersive Virtual Reality Environment for Training Acute Care Teams (iREACT) (Department of Emergency Medicine, University of Michigan Medical School)
• Perioperative Deterioration: Early Recognition, Rapid Response, and the End of Failure-to-Rescue (Anesthesia Patient Safety Foundation)