This Beeson award seeks to equip the candidate, Dr. Kathryn E. Callahan, with the expertise to become an independent investigator to advance use of aging-related metrics and interventions to promote health, function, and quality of life in frail and at-risk older adults. Frailty is prevalent among older adults, and associated with negative outcomes, including hospitalizations, mobility disability, admission to skilled nursing facilities, and mortality. Despite efforts to define and quantify frailty, time and resource constraints limit the feasibility of frailty measures in clinical practice. Dr. Callahan's preliminary work supports the feasibility of translating anEMR- based Frailty Index, or eFI ? into the Wake Forest Baptist Health (WFBH) EMR, and demonstrates an initial association between eFI score and hospitalizations and mortality. The proposed research project represents critical next steps: (1) to adapt and refine the eFI using ambulatory care data, (2) assess its predictive value for healthcare outcomes for older adults, and (3) conduct a pilot of implementation in Medicare Shared Savings Program/Next Generation Accountable Care Organization primary care practices, to collect critical data regarding feasibility, acceptability, and effectiveness. The scientific goal is to develop and implement an index to define a population of frail older adults who would benefit from personalized evidence-based interventions. This work is essential to inform larger-scale implementation trials of interventions to mediate negative and costly health outcomes for frail older adults. We hypothesize that self-report and functional data from Annual Wellness Visits (AWVs) in the EMR will further refine the predictive value of the eFI; and that implementation of the eFI will be feasible and acceptable. This project is supported by engaged mentors (Drs. Williamson and Boustani) and a highly interactive, inter-disciplinary advisory committee (Drs. Foley, Rejeski, and Pajewski) whose expertise and complementary skills are a noteworthy asset to this project. We propose the adaptation and refinement of the eFI within the WFBH EMR, using data from older adults enrolled in the WFBH MSSP/ Next Gen ACO (Aim 1): we will integrate AWV data, and refine the predictive value of eFI scores in this population. We will then conduct a pilot study implementing the adapted eFI score in six MSSP/Next Gen ACO primary care practices, and follow health outcomes. The research proposed aligns with an NIA priority to improve the health, well-being, and independence of adults as they age. It will also provide essential training for the candidate, who will establish expertise in implementation science, achieve fluency in clinical informatics, and develop competencies in leading implementation trials. This approach provides the ideal platform to advance the candidate's career as an independent investigator and provides the foundation to establish frailty metrics in practice, leveraging the learning health system to implement interventions to improve health and function.
Frailty is prevalent among older adults, and predicts poor health outcomes such as hospitalizations, loss of independence, and death; yet measures of frailty are not included in routine primary care practice. Building on our pilot work to generate an electronic frailty index (eFI) in the electronic medical record for older adults, we will adapt and refine an eFI, using already existing data from patients served by primary care practices in our partner Next Generation Accountable Care Organization. We will then test whether primary care providers (a) find value in the eFI when caring for frail and at-risk older adults, (b) change their medical advice and support based on the eFI score, and (c) whether this change improves health outcomes for older adults as a consequence.
| Callahan, Kathryn E; Lovato, Laura; Miller, Michael E et al. (2018) Self-Reported Physical Function As a Predictor of Hospitalization in the Lifestyle Interventions and Independence for Elders Study. J Am Geriatr Soc 66:1927-1933 |
