Browsing by Author "Dublin, Sascha"

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    Recommendations for outcome measurement for deprescribing intervention studies
    (Wiley, 2022) 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.; Dublin, Sascha; Medicine, School of Medicine
    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.
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    The electronic health record Risk of Alzheimer’s and Dementia Assessment Rule (eRADAR) brain health trial: Protocol for an embedded, pragmatic clinical trial of a low-cost dementia detection algorithm
    (Elsevier, 2023-12) Dublin, Sascha; Greenwood-Hickman, Mikael Anne; Karliner, Leah; Hsu, Clarissa; Coley , R. Yates; Colemon, Leonardo; Carrasco, Anna; King, Deborah; Grace, Andrea; Lee , Sei J.; Walsh, Judith M. E.; Barrett, Tyler; Broussard, Jia; Singh, Umesh; Idu, Abisola; Yaffe, Kristine; Boustani, Malaz; Barnes, Deborah E.; Medicine, School of Medicine
    Background About half of people living with dementia have not received a diagnosis, delaying access to treatment, education, and support. We previously developed a tool, eRADAR, which uses information in the electronic health record (EHR) to identify patients who may have undiagnosed dementia. This paper provides the protocol for an embedded, pragmatic clinical trial (ePCT) implementing eRADAR in two healthcare systems to determine whether an intervention using eRADAR increases dementia diagnosis rates and to examine the benefits and harms experienced by patients and other stakeholders. Methods We will conduct an ePCT within an integrated healthcare system and replicate it in an urban academic medical center. At primary care clinics serving about 27,000 patients age 65 and above, we will randomize primary care providers (PCPs) to have their patients with high eRADAR scores receive targeted outreach (intervention) or usual care. Intervention patients will be offered a “brain health” assessment visit with a clinical research interventionist mirroring existing roles within the healthcare systems. The interventionist will make follow-up recommendations to PCPs and offer support to newly-diagnosed patients. Patients with high eRADAR scores in both study arms will be followed to identify new diagnoses of dementia in the EHR (primary outcome). Secondary outcomes include healthcare utilization from the EHR and patient, family member and clinician satisfaction assessed through surveys and interviews. Conclusion If this pragmatic trial is successful, the eRADAR tool and intervention could be adopted by other healthcare systems, potentially improving dementia detection, patient care and quality of life.