July 12, 2023
For oncology patients, emergency visits and unplanned hospital stays are common. Those who have been marginalized because of race, ethnicity, income or other factors are even more likely to experience one of these acute care events.
As part of the University’s North Carolina Translational and Clinical Sciences Insititute (NCTraCS) renewal, the UNC Eshelman School of Pharmacy’s Jennifer Elston Lafata, Ph.D., professor in the Division of Pharmaceutical Outcomes and Policy and her colleague, Jake Stein, M.D., MPH, assistant professor at the UNC School of Medicine, have received funding as co-principal investigators for a project focused on developing and identifying a process for addressing this issue.
NCTraCS is a grant-funded institute founded as a service to the research community. Translational research takes discoveries made in the laboratory, in the clinic or out in the field and transforms them into new treatments and approaches to medical care.
Lafata and Stein’s project is using a partnership between statistical modelers and cancer care team members to not only predict which patients undergoing cancer treatments are likely to land in the hospital or need care in an emergency room, but also to develop ways to prevent them from needing this care to begin with.
“Emergency departments are busy and crowded places that are usually neither comfortable nor safe places for immunocompromised cancer patients to be,” said Lafata.
The goal for their project is to prospectively identify and group cancer patients together who have similar care needs. Once groups of patients with similar care needs are identifiable, they can create service bundles and care processes that are targeted specifically to each group’s needs.
“Our hope is that we will not only help our patients who are undergoing cancer treatment avoid preventable hospital stays and trips to the emergency room, but also help cancer care teams to more easily and efficiently deliver target services to those most in need,” said Lafata.
This will lead to the development of an oncology risk-stratified intervention system (OR-SIS) that is acceptable to clinicians and patient users and realistic to implement. Ultimately it will result in fewer acute care events, facilitate care equity and serve as a translational science process prototype for prognostic modeling in other clinical contexts.
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