PHILADELPHIA — Two Penn Medicine researchers have received $3.1 million in research funding contracts from the Patient-Centered Outcomes Research Institute (PCORI) to develop tools that will help patients understand the addiction risks associated with opioid prescription drugs, and allow researchers to harness data from electronic health records (EHR) to better predict disease patterns. PCORI is an independent, nonprofit organization that funds research intended to provide patients, their caregivers, and clinicians with the evidence-based information needed to make better-informed healthcare decisions.

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Perelman School of Medicine at the University of Pennsylvania

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Amid a devastating public health crisis, in which 19,000 overdose deaths per year in the United States are due to prescription opioids, Zachary Meisel, MD, an assistant professor of Emergency Medicine, aims to use his three-year, $2.1 million award to conduct the first large-scale multi-center randomized clinical trial aimed at improving communication between physicians and patients with acute pain in order to improve education about individual risks of opioid misuse. The trial, which will enroll 1,100 patients who are set to discharge from acute care settings after being treated for acute back or acute kidney stone pain, will compare the effectiveness of different tools used to inform patients about pain management strategies, opioid use and addiction risk. Tools might include fact sheets, video narrative vignettes, interactive questions, and a pain scoring system that will allow patients to calculate their own level of addiction risk.

Health care providers, Meisel says, need more effective ways to understand their patients’ pain, and patients need tools that will help them better understand the risks associated with opioid prescriptions and more accurately communicate with care providers about their preferences for pain management.

“Patients with kidney stones, back pain, or pain resulting from other acute conditions, may benefit from opioids, but also respond to non-opioid alternatives. We also know that these powerful and addictive medications are being over prescribed, perhaps in part because of a lack of education and communication on both sides of the conversation,” Meisel said. “Conversations between physicians and patients will always be of the utmost importance, but having easy to use tools will help patients understand their risks and also inform physicians about best practices with opioid prescribing, will ultimately help tackle what is now widely recognized as a national epidemic.”

In a second PCORI grant, Rebecca A. Hubbard, PhD, an associate professor of biostatistics in Biostatistics and Epidemiology, and colleagues will undertake a three-year $1 million grant to support creation of new statistical techniques and software to estimate latent, or hidden phenotypes – the observable characteristics including health conditions that describe an individual – using data from electronic health records (EHR). The objective of these methods is to yield new insights into the association between phenotypes and health outcomes using messy and incomplete data from EHR.

As an example of the use of these new methods, Hubbard and her team will study EHR for children and adolescents to attempt to identify individuals with type II diabetes before a clinical diagnosis has been made. Using EHR data from eight children’s hospital health systems participating in the PEDSnet federation, they will develop a pediatric diabetes latent phenotype using the unique set of measures available for each individual patient. This phenotype can be used in research to assess an individual’s risk of specific health outcomes and offers insight into a person’s true disease profile that may otherwise be only hinted at by the measurements available in a patient’s EHR.

“Electronic health records can provide rich data on an individual’s health and disease risk factors but the incomplete and inconsistent nature of the information available across patients makes it difficult to discern a pattern,” said Hubbard. “By creating these statistical methods, we’re pooling relevant data in a new way that can more accurately and precisely pinpoint an individual’s disease profile. In doing so, we can advance research and support improved patient care.”

Co-investigators on Hubbard’s study are Penn colleagues Yong Chen, PhD, and Jinbo Chen, PhD, as well as L. Charles Bailey, MD, from Penn and the Children’s Hospital of Philadelphia. More information on this project is available on the PCORI site.

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