University of Pennsylvania Perelman School of Medicine
Determination of Cognitive Status in NH Residents: The Utility of EHR Data
Real World Data
LTC Data Cooperative
Dr. White is a health services researcher with a long-standing interest in the quality of health care provided to older adults living with serious illness. Dr. White completed her postdoctoral fellowship at the University of Washington focused on estimating the costs of caring for people living with dementia. She was previously a research economist at RTI International on the implementation of a Center for Medicare & Medicaid Innovation (CMMI) primary care-focused alternative payment model. Dr. White recently returned to full-time research so that she could have a greater impact on policy development and design. As a senior research investigator in the University of Pennsylvania’s Policy and Economics of Disability, Aging, and Long-Term Care (PEDAL) lab within the Department of Medical Ethics & Health Policy, she hopes to generate the evidence base for policies that facilitate high quality, equitable, and efficient care for people as they age.
Cognitive impairment is extremely common in the nursing home (NH) setting, impacting approximately two-thirds of NH residents, and is associated with an elevated risk of low-quality care and poor outcomes of care. Information on cognitive impairment in existing data sources on NH residents, such as Medicare claims and the Minimum Data Set (MDS), is limited in terms of diagnostic accuracy, capture of impairment severity, and impairment assessment frequency. This project will examine whether and under what circumstances the LTC Data Cooperative EHR data provides useful cognitive status information above and beyond what is available through Medicare claims and MDS. The Real World Data Scholar Award will provide Dr. White with the necessary training and experience using the LTC Data Cooperative EHR data to: 1) Describe the EHR cognitive assessment data across time, facilities, and resident populations; 2) Examine the validity of the EHR cognitive assessment data; and 3) Examine within-resident variation in cognitive status over time. Findings from this study will demonstrate the type, frequency, and validity of cognitive status information available in the LTC Data Cooperative EHR data, providing valuable evidence of whether and under what circumstances the information may be useful to clinicians and researchers. Training and findings from this award will establish the validity of key cognitive measures and further the Scholar's independent line of research to help build the much-needed evidence base to improve care delivery in the NH setting for people living with dementia.