Wake Forest University School of Medicine
Pragmatic EHR Tool to Identify High-Risk Hospitalized Dementia Patients
Wake Forest University School of Medicine
Dr. Frechman is an assistant professor at Wake Forest University School of Medicine. She is a board-certified adult gerontological nurse practitioner who specializes in palliative care. Her research is informed by her clinical experiences caring for people living with serious illness across all care settings from the community to the hospital and to long-term care. Dr. Frechman’s research focuses on identifying hospitalized high-risk people living with dementia (PLWD) through an electronic health record risk prediction modeling. She aims to develop transitional care interventions to ensure PLWD and care partners (CPs) are provided needed resources and support. She is committed to improving health and quality of life for PLWD and their CPs through care delivery transformation. Dr. Frechman is seeking to develop skills in applied clinical informatics, pragmatic clinical trial design, and implementation science through this Career Development Award.
Prognostic heterogeneity within illness progression places people living with dementia (PLWD) at risk for incident acute care, uncertainty in care trajectory, and growing caregiving demands for CPs. Pragmatic and accessible mortality risk prediction models for hospitalized PLWD can provide an opportunity to identify high-risk PLWD, while providing their CPs with needed resources and support across transitions of care. This Career Development Award will provide Dr. Frechman with the necessary experience and training in applied clinical informatics and pragmatic tool development, implementation science, and design of embedded pragmatic clinical trials (ePCTs) to become an independent clinician-investigator conducting translational research. This training will support the following Specific Aims: (1) Test the prognostic accuracy of the End-of-Life Care Index (EOL-CI) in hospitalized PLWD and in those with a high likelihood of cognitive impairment and (2) Examine the value of combining frailty status and other risk factors with the EOL-CI for predicting one-year morality in these populations. This work will lay the foundation for a future ePCT of a dementia-friendly transitional care intervention by utilizing an electronic health record prognostic model to identify high-risk PLWD.