EHR Implementation Guide – Identifying Frailty Using Existing Health Data
Challenges and Opportunities for Health Systems
Published in: Office of the Assistant Secretary for Planning and Evaluation website (2023)
Posted on RAND.org on November 06, 2023
To support the project, Validating and Expanding Claims-based Algorithms of Frailty and Functional Disability for Value-Based Care and Payment funded by the Patient-Centered Outcomes Research Trust Fund (OS-PCORTF), the Office of the Assistant Secretary for Planning and Evaluation (ASPE) requested that RAND Health Care ASPE engage health systems, health care providers and researchers through an EHR Learning Network to share learnings on leading-edge frailty identification practices using EHR data, how the information is used in clinical care to identify and manage high-risk patients, factors that facilitate or prevent EHR data from being used, and to identify potential use cases from interviews. This EHR Implementation Guide – Identifying Frailty using Existing Health Data is designed for use by health systems, shares learnings from this EHR Learning Network and a separate AHRQ-funded study evaluating a claims-based frailty index using EHR across health systems with varying degrees of delivery network open/closed-ness. It offers guidance to health systems on using EHR data to identify patients with frailty or functional impairment. The guide describes the range of ways that EHRs are being used to capture data on frailty and functional impairment from primary to specialist care, and best practices for implementing algorithms using EHR data for population management and in support of patient-centered care. Key considerations are offered for providers and health systems as well as algorithm developers, researchers, practitioners and policymakers in using claims and EHR data to identify frailty and persons at risk of frailty. The report concludes frailty indexes that are based on EHR data—EFIs—are promising and practical for health systems, but require considering data quality and completeness. Future research could explore tapping into unstructured EHR data, using standardized data on patient function and increased use of patient functional assessments.