Bayliss, Elizabeth A.; Albers, Kathleen; Gleason, Kathy; Pieper, Lisa E.; Boyd, Cynthia M.; Campbell, Noll L.; Ensrud, Kristine E.; Gray, Shelly L.; Linsky, Amy M.; Mangin, Derelie; Min, Lillian; Rich, Michael W.; Steinman, Michael A.; Turner, Justin; Vasilevskis, Eduard E.;
Suls, Jerry; Salive, Marcel E.; Koroukian, Siran M.; Alemi, Farrokh; Silber, Jeffrey H.; Kastenmüller, Gabi; Klabunde, Carrie N.
doi: 10.1111/jgs.17914pmid: 35699153
Older adults experience a higher prevalence of multiple chronic conditions (MCCs). Establishing the presence and pattern of MCCs in individuals or populations is important for healthcare delivery, research, and policy. This report describes four emerging approaches and discusses their potential applications for enhancing assessment, treatment, and policy for the aging population. The National Institutes of Health convened a 2‐day panel workshop of experts in 2018. Four emerging models were identified by the panel, including classification and regression tree (CART), qualifying comorbidity sets (QCS), the multimorbidity index (MMI), and the application of omics to network medicine. Future research into models of multiple chronic condition assessment may improve understanding of the epidemiology, diagnosis, and treatment of older persons.
Showing 1 to 10 of 42 Articles
doi: 10.1111/jgs.17894pmid: 35648465
Interpreting results from deprescribing interventions to generate actionable evidence is challenging owing to inconsistent and heterogeneous outcome definitions between studies. We sought to characterize deprescribing intervention outcomes and recommend approaches to measure outcomes for future studies. A scoping literature review focused on deprescribing interventions for polypharmacy and informed a series of expert panel discussions and recommendations. Twelve experts in deprescribing research, policy, and clinical practice interventions participating in the Measures Workgroup of the US Deprescribing Research Network sought to characterize deprescribing outcomes and recommend approaches to measure outcomes for future studies. The scoping review identified 125 papers reflecting 107 deprescribing studies. Common outcomes included medication discontinuation, medication appropriateness, and a broad range of clinical outcomes potentially resulting from medication reduction. Panel recommendations included clearly defining clinically meaningful medication outcomes (e.g., number of chronic medications, dose reductions), ensuring adequate sample size and follow‐up time to capture clinical outcomes resulting from medication discontinuation (e.g., quality of life [QOL]), and selecting appropriate and feasible data sources. A new conceptual model illustrates how downstream clinical outcomes (e.g., reduction in falls) should be interpreted in the context of initial changes in medication measures (e.g., reduction in mean total medications). Areas needing further development include implementation outcomes specific to deprescribing interventions and measures of adverse drug withdrawal events. Generating evidence to guide deprescribing is essential to address patient, caregiver, and clinician concerns about the benefits and harms of medication discontinuation. This article provides recommendations and an initial conceptual framework for selecting and applying appropriate intervention outcomes to support deprescribing research.