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Reducing High Risk Polypharmacy Using Behavioral Economics through Electronic Health Records

Reducing High Risk Polypharmacy Using Behavioral Economics through Electronic Health Records
通过电子健康记录利用行为经济学减少高风险的多重用药
批准号:
10672251
负责人:
Stephen Persell
金额:
$42.82万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-08-01 至 2026-05-31

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中文摘要
翻译
项目摘要/摘要 高风险多药在美国老年人中很常见,并与以下危害有关 随着药物不良反应、下降,以及更高的护理成本。认知障碍或痴呆症患者 可能尤其面临多药联用的不良后果的风险。到目前为止,降低死亡率的努力 由于每个临床医生的费用和他们适中的费用,高风险多药联用的吸收有限 在帮助临床医生停止可能不适当的药物方面的有效性。这些先前的努力依赖于 合理的临床医生行为模式。然而,像普通人一样,临床医生也容易受到非理性的影响。 偏见和认知捷径,可能使不适当的高风险多药制永久化。因此, 不假设理性决策的行为经济学推动,可能很好地定位于 减少这种高风险的多药联用。此外,这样的提示可以嵌入电子健康记录中 (EHR),以每位临床医生的低成本增强其可扩展性-只要它们被以下临床医生接受 担心EHR对他们的工作流程的影响。 该项目的总体目标是测试基于EHR的行为经济推动,这可能 减少老年患者中高危多药联用的发生率和程度,并描述他们的 对临床医生的体验和工作流程的影响。具体目标是(1)评估电子健康记录的效果- 基于承诺的轻推、理由轻推以及复合度量上两种轻推的组合 在所有老年人和患有痴呆症或轻度认知障碍的亚群中使用高风险多药 通过一项务实的随机对照试验。这将使用集群随机,其中初级保健诊所 来自两个大型健康系统的患者使用析因设计随机接受0、1或2个轻推。这个 轻推将持续18个月,然后进行12个月的观察,以评估效果的持续性;以及(2) 定性和定量评估临床医生使用基于EHR的NUGES的经验,包括他们的 可接受性和对工作流程的影响。在干预期结束时,半结构化访谈 约40名临床医生将被用来详细描述他们使用轻推的经验,以及 将进行临床医生调查,以检查临床医生对轻推的看法, 他们对EHR工具的实际使用,以及这些因素与高危人群实际变化的关系 综合药房。这项研究将产生基于EHR的微调,可以在全国范围内实施,详细说明 描述这些轻推如何影响临床医生的工作流程(以促进传播),以及科学论文 记录NUGES在减少老年人中高风险多药使用方面的有效性。
英文摘要
Project Summary/Abstract High-risk polypharmacy is common among older adults in the United States and is associated with harms such as adverse drug reactions, falls, and higher costs of care. Individuals with cognitive impairment or dementia may be at particularly at risk for adverse outcomes from polypharmacy. To date, efforts to reduce the rate of high-risk polypharmacy have had limited uptake due to their expense per clinician and their modest effectiveness in helping clinicians stop potentially inappropriate medications. These prior efforts have relied on rational clinician behavior models. However, like people in general, clinicians are susceptible to irrational biases and cognitive shortcuts that might perpetuate inappropriate high-risk polypharmacy. Therefore, behavioral economic nudges, which do not assume rational decision making, might be well-positioned to reduce such high-risk polypharmacy. Moreover, such nudges can be embedded in electronic health records (EHRs), enhancing their scalability at a low cost per clinician—as long as they are acceptable to clinicians who worry about EHRs’ effects on their workflows. The overall objectives of the project are to test EHR-based behavioral economic nudges that may reduce the prevalence and degree of high-risk polypharmacy among older adult patients and to describe their impact on clinicians’ experiences and workflows. The specific aims are (1) to evaluate the effects of an EHR- based commitment nudge, a justification nudge, and the combination of both nudges on a composite measure of high-risk polypharmacy in all older adults and the subpopulation with dementia or mild cognitive impairment via a pragmatic randomized controlled trial. This will use cluster randomization in which primary care clinics from two large health systems are randomized to receive 0, 1, or 2 nudges using a factorial design. The nudges will run for 18 months, followed by 12 months of observation to assess persistence of effects; and (2) to assess qualitatively and quantitatively clinician experiences with the EHR-based nudges, including their acceptability and effects on workflow. At the conclusion of the intervention period, semi-structured interviews with approximately 40 clinicians will be used to describe their experiences with the nudges in detail, and a clinician survey will be conducted to examine the relationships between clinicians’ perceptions of the nudges, their actual use of the EHR tools, and the relationships of these factors to actual changes in high-risk polypharmacy. The study will yield EHR-based nudges that can be implemented across the country, detailed descriptions of how these nudges affect clinicians’ workflows (to spur dissemination), and scientific papers documenting the nudges’ effectiveness in reducing high-risk polypharmacy among older adults.
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Reducing High Risk Polypharmacy Using Behavioral Economics through Electronic Health Records
Behavioral Economics Applications to Geriatrics Leveraging EHRs (BEAGLE)
Behavioral Economics Applications to Geriatrics Leveraging EHRs (BEAGLE)
Behavioral Economics Applications to Geriatrics Leveraging EHRs (BEAGLE)
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