The specific aims are to develop interventions to improve function and independence in older adults with balance disorders, integrate studies of physiologic, biomechanical, and psychosocial mechanisms affecting balance with clinical studies, and foster multidisciplinary research and research training.
Pilot study to determine the feasibility of using telemedicine to assist nurse practitioners with managing acute change in condition and palliative care assessments of nursing home residents
The primary goal of this quality improvement project is to determine the feasibility of using telemedicine to assist nurse practitioners with managing acute change in condition and palliative care assessments of UPMC nursing home patients. To assess feasibility, we intend to utilize web-based surveys to quantify the perception of these services in terms of quality of the medical care provided, quality of the equipment used, and perceived barriers to implementation, both before and following each telemedicine encounter.
Reduce AVoidable hospitalizations using Evidence-based interventions for Nursing facilities in Western Pennsylvania (RAVEN).
UPMC will implement an intervention in 19 nursing facilities in the western region of Pennsylvania. UPMC Community Provider Services has created a program called “RAVEN” (Reduce AVoidable hospitalizations using Evidence-based interventions for Nursing facilities in western Pennsylvania).
Transforming the role of the hospital pharmacist to improve patients’ access, adherence, and self-management of medication after discharge
The goal of this quality improvement initiative is to enhance and evaluate a recently implemented pharmacy patient-care model at UPMC-Presbyterian Shadyside using a tool that will enable the pharmacist to engage the patient in the process of shared decision-making for medication self-management.
Improving the Identification of Actionable Adverse Drug Events Associated with Acute Kidney Injury in Nursing Homes
The goal of this study is to determine if the addition of patient characteristics (i.e., clinical context) to a clinical surveillance system can improve identification of actionable adverse drug events caused by acute kidney injury and reduce alert burden/fatigue in nursing homes.
The Vis Lab is focused on the application of artificial intelligence and machine learning to problems in the Learning Health System (LHS) that include: 1) development of a learning Electronic Medical Record (LEMR) system, 2) precision medicine and personalized modeling, 3) reuse of Electronic Medical Record (EMR) data for clinical, translational, and informatics research, 4) data mining and causal discovery from biomedical data, and 5) automated visual analytics.
Critical Care Medication Safety Officer
Department of Pharmacy
University of Pittsburgh Medical Center
School of Pharmacy
Health Policy and Management
Department of Biomedical Informatics, School of Medicine
Intelligent Systems Program, Kenneth P. Dietrich School of Arts and Sciences
Associate Director, RFID Center of Excellence