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Behavioral Economics Applications to Geriatrics Leveraging EHRs (BEAGLE)

Behavioral Economics Applications to Geriatrics Leveraging EHRs (BEAGLE)
利用 EHR 的行为经济学在老年病学中的应用 (BEAGLE)
批准号:
10007063
负责人:
Stephen Persell
金额:
$78.3万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-15 至 2022-08-31

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项目成果

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中文摘要
翻译
项目摘要 许多诊断方法和治疗方法对老年人的风险和好处不同,与 中年人。当诊断和治疗策略被错误地应用于老年人时,这可能导致 发病率和死亡率增加。临床医生往往不能最好地遵循的公认例子 照顾老年人的做法包括美国老年医学会为老年人确定的做法 明智地选择主动性:1)无症状菌尿的检测和治疗,2)前列腺特异性抗原 在没有前列腺癌的老年男性中进行测试,以及3)过度使用胰岛素或口服降糖药治疗2型 糖尿病。关于为什么临床医生没有将最好的证据纳入老年医学,有几个假设 临床护理。首先,他们可能低估了测试的下游危害,这似乎很容易完成(例如, 对于非特定症状的尿检)或适合年轻患者的治疗(例如 强化胰岛素以实现严格控制)。其次,临床医生可能会高估不履行职责的风险。 行为(例如,漏诊癌症、未诊断无尿路患者的尿路感染 症状)。第三,临床医生可能会对真实的或感知的社会规范(来自患者和他们的 家庭、其他临床医生或两者兼而有之),设定特定行为方式的期望。第四,习惯的力量可能 引导临床医生采取与过去类似的方式,即使目前的证据不是这样 支持它。第五,临床医生可能会过度使用测试或治疗,以避免感觉他们正在表达一种 对病人的年龄歧视。临床决策支持推动,社会心理学和 通过电子健康记录(EHR)提供的,是有希望的战略,以减少滥用服务在 最佳利用率可能不是零,但应远低于当前做法的情况。这些干预措施 寻求影响临床决策的有意识和无意识的驱动因素,实施成本低, 传播,并可纳入现有的交付系统。在拟议的R21阶段 行为经济学在老年医学中的应用利用EHR(Beagle)研究,我们将:选择EHR- 根据主要的心理学基础,提出了解决老年人潜在滥用的3个主题 通过与高使用率的临床医生的访谈确定过度使用的驱动因素;开发和试点测试决策支持 卫生系统EHR中的工具,以了解技术可行性、工作流程适用性、初步影响 临床结果和临床医生的可接受性;以及开发和验证电子临床质量测量 与照顾老年人有关的潜在过度使用/滥用。在R33阶段,我们将:完善这些方法 并在一项在40多个临床试验中进行的整群随机对照试验中评估每个轻推的效果 在一个大的地理区域内的地点。我们将衡量对临床质量指标、指标的影响 患者安全和临床医生的态度。
英文摘要
Project Summary The risks and benefits of many diagnostic approaches and treatments differ for older adults compared to middle aged adults. When diagnostic and therapeutic strategies are misapplied to older adults this can lead to increased morbidity and mortality. Well-established examples where clinicians do not often follow best practices in the care of older adults include those identified by the American Geriatrics Society for the Choosing Wisely initiative: 1) testing and treatment for asymptomatic bacteriuria, 2) prostate specific antigen testing in older men without prostate cancer, and 3) overuse of insulin or oral hypoglycemics for type 2 diabetes. There are several hypotheses as to why clinicians fail to incorporate best evidence into geriatric clinical care. First, they may underestimate downstream harms of testing which seems easy to do (e.g., a urinalysis for a non-specific symptom) or treatment that may be appropriate for younger patients (e.g. intensifying insulin to achieve tight control). Second, clinicians may overweigh the risks of not performing the action (e.g., missing cancer diagnosis, failing to diagnose UTI in a patient presenting without urinary tract symptoms). Third, clinicians may respond to real or perceived social norms (from patients and their families, other clinicians or both) that set expectations to behave in specific ways. Fourth, force of habit may lead clinicians to act in a way similar to how they have done in the past even if current evidence doesn’t support it. And fifth, clinicians may overuse a test or treatment to avoid feeling they are expressing an ageist bias toward their patients. Clinical decision support nudges, informed by social psychology and delivered via electronic health records (EHRs), are promising strategies to reduce the misuse of services in cases where optimal utilization may not be zero but should be well below current practice. These interventions seek to influence conscious and unconscious drivers of clinical decision making, are low cost to implement and disseminate, and can be incorporated into existing delivery systems. In the R21 phase of the proposed Behavioral Economics Applications to Geriatrics Leveraging EHRs (BEAGLE) study, we will: select EHR- delivered nudges to address 3 topics of potential misuse in older adults based on the main psychological drivers of overuse identified in interviews with high-using clinicians; develop and pilot test decision support tools within a health systems’ EHR to understand technical feasibility, work flow fit, preliminary impact on clinical outcomes, and clinician acceptability; and develop and validate electronic clinical quality measures of potential overuse/misuse related to the care of older adults. In the R33 phase we will: refine these approaches and evaluate the effects of each nudge in a cluster randomized controlled trial conducted in over 40 clinical sites across a large geographic region. We will measure the impact on clinical quality measures, indicators of patient safety, and clinician attitudes.
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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
Behavioral Economics Applications to Geriatrics Leveraging EHRs (BEAGLE)
Behavioral Economics Applications to Geriatrics Leveraging EHRs (BEAGLE)
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