期刊
IMPLEMENTATION SCIENCE
卷 16, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s13012-020-01078-9
关键词
Deprescribing; Older adults; Decision support; Pragmatic trial; Prescribing; Adaptive trial
资金
- National Institute on Aging (NIA) of the National Institutes of Health (NIH) [R33AG057388]
Efforts to reduce inappropriate prescribing of high-risk medications to older adults have had limited success. This study aims to determine whether designing EHR tools using behavioral science principles can effectively reduce inappropriate prescribing and improve clinical outcomes in older adults. The NUDGE-EHR project utilizes a two-stage, 16-arm adaptive randomized pragmatic trial to identify the most effective EHR tool among primary care providers and their patients aged 65 years and older.
BackgroundThe prescribing of high-risk medications to older adults remains extremely common and results in potentially avoidable health consequences. Efforts to reduce prescribing have had limited success, in part because they have been sub-optimally timed, poorly designed, or not provided actionable information. Electronic health record (EHR)-based tools are commonly used but have had limited application in facilitating deprescribing in older adults. The objective is to determine whether designing EHR tools using behavioral science principles reduces inappropriate prescribing and clinical outcomes in older adults.MethodsThe Novel Uses of Designs to Guide provider Engagement in Electronic Health Records (NUDGE-EHR) project uses a two-stage, 16-arm adaptive randomized pragmatic trial with a pick-the-winner design to identify the most effective of many potential EHR tools among primary care providers and their patients >= 65years chronically using benzodiazepines, sedative hypnotic (Z-drugs), or anticholinergics in a large integrated delivery system. In stage 1, we randomized providers and their patients to usual care (n = 81 providers) or one of 15 EHR tools (n = 8 providers per arm) designed using behavioral principles including salience, choice architecture, or defaulting. After 6months of follow-up, we will rank order the arms based upon their impact on the trial's primary outcome (for both stages): reduction in inappropriate prescribing (via discontinuation or tapering). In stage 2, we will randomize (a) stage 1 usual care providers in a 1:1 ratio to one of the up to 5 most promising stage 1 interventions or continue usual care and (b) stage 1 providers in the unselected arms in a 1:1 ratio to one of the 5 most promising interventions or usual care. Secondary and tertiary outcomes include quantities of medication prescribed and utilized and clinically significant adverse outcomes.DiscussionStage 1 launched in October 2020. We plan to complete stage 2 follow-up in December 2021. These results will advance understanding about how behavioral science can optimize EHR decision support to improve prescribing and health outcomes. Adaptive trials have rarely been used in implementation science, so these findings also provide insight into how trials in this field could be more efficiently conducted.Trial registrationClinicaltrials.gov (NCT04284553, registered: February 26, 2020)
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