Frailty increases a person鈥檚 risk for functional impairment and cognitive decline, and poor health outcomes such as hospitalizations and institutionalization. Identifying frailty and functional disability plays an important role in informing clinical care, risk-adjustment in patient-centered outcomes research, and evaluating performance and payments in value-based care programs. Multiple claims-based frailty indexes (CFIs) have been developed and validated over the past few years; however, healthcare providers often do not have access to the insurance claims records of their entire population of patients, thus necessitating the development of reliable EHR-based frailty indexes (EFI).
大象视频conducted a study to address the operational gap between CFIs and EFIs. This project focused on validating an established CFI using linked claims-EHR databases of multiple large health systems. The project provides a systematic approach that health systems can use to examine the quality of the EHR data and prepare it for the application of EFI measures.
The findings demonstrated that structured EHR data can be used by healthcare providers to identify frail patients using validated EFIs; however, claims data can identify additional frailty cases compared to EHR data. EFIs can also be used to improve the prediction of various healthcare utilization outcomes. Risk stratification developers may integrate EFI in their model development process, and population health managers may incorporate EFI in disease management efforts.
