Research
Current Research
Funding Source: NIH/NIA
The objective of this K23 grant, awarded to Dr. Radomski, is to develop, validate, and apply a metric that will characterize specific low-value prescribing (LVP) practices using administrative data and reflect the perspectives of patients, prescribers, and payers as they relate to healthcare value. Dr. Walid Gellad is the Primary Mentor for this project, and RAND and Pitt faculty will serve as collaborators.
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Funding Source: Gordon and Betty Moore Foundation
This project aims to develop and test new metrics of conservative prescribing; examine differences in conservative prescribing practices among 4 healthcare organizations; correlate conservative prescribing metrics with process and outcome measures; and develop and implement an educational campaign related to conservative prescribing principles. This project is in collaboration with Brigham and Women's Hospital.
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Funding Source: VA Health Services Research and Development (HSR&D) Merit Award
Funding Period May 2016 - July 2019
This project will examine determinants and outcomes of intense vs. de-intensified treatment of common chronic conditions in VA nursing home residents with limited life expectancy or advanced dementia.
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Funding Source: NIH/NHLBI
Improved outcomes for patients with cardiovascular diseases is the focus of this K01 grant, awarded to Dr. Inma Hernandez. Dr. Hernandez will apply advanced methods to describe current trends in use of oral anticoagulation therapy among patients with atrial fibrillation in order to provide guidance for interventions targeting optimal oral anticoagulation use.
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Funding Source: Alzheimer's Association
This study, led by Inmaculada Hernandez, PharmD, PhD, examines factors that increases side effects from anti-dementia drugs. It also compares safety of anti-dementia drugs.
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Funding Source: R.K. Mellon Foundation
This project leverages data from Allegheny County’s Department of Human Services and Department of Health to develop algorithms using machine learning to predict opioid overdose. These algorithms can be modified in the future to predict risk of other consequences of opioid addiction, such as loss of child custody, housing instability, and criminal justice contact.
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Funding Source: NIH/NIDA
This R01 project improves on traditional methods for predicting risk of overdose from prescription opioids by applying machine learning techniques. The study team, led by Dr. Gellad, will develop prediction algorithms to identify patients who are at risk of opioid overdose, and after testing and refining the algorithm, will compare the accuracy of an approach integrating Medicaid claims data with clinical data to an approach using claims data alone.
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Funding Source: US Department of Veterans Affairs
Dr. Gellad is co-leading a qualitative evaluation of the randomized roll out across VA facilities of a tool that predicts the risk of opioid overdose or suicide related events among Veterans receiving opioid medications.
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Funding Source: US Department of Veterans Affairs
In 2015, Dr. Gellad received a three year grant to study opioid use in the veteran population, specifically those receiving care from multiple health systems.
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Completed Research
Funding Source: NIH/NHLBI
This study, led by Julie Donohue, examined how physicians learn from their peers about new drugs and the extent of peer influence on prescribing behavior.
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Funding Source: CDC
Drug formularies are potentially valuable tools to manage and improve prescription opioid use and overdose prevention. Through a grant with the CDC, Drs. Cochran and Donohue lead a project to evaluate patterns of problematic opioid consumption and overdose in Medicaid, and test the effects of formulary tools on slowing or reducing problematic opioid consumption and overdose.
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CP3 and affiliated faculty are helping the state of Pennsylvania develop educational materials and programs to increase utilization of the state's new prescription drug monitoring program. Read more
Expanding veterans' access to providers outside of the VA may increase the risk for unsafe prescribing practices, particularly in persons with dementia. Read more
The use of buprenorphine - an effective treatment for opioid use disorders (OUDs) - has increased rapidly in recent years and is often financed by Medicaid. CP3 and MRC researchers investigated. Read more