远程医疗评价优化养老院老年人用药处方。

Charlotte Berard, Thomas Di Mascio, Maeva Montaleytang, Anne Laure Couderc, Patrick Villani, Stephane Honoré, Aurelie Daumas, Florian Correard
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引用次数: 2

摘要

由于与年龄相关的生理变化、多种病理和多种药物作用,生活在养老院(NH)的老年人发生可预防的药物相关不良事件的风险更高。NH居民特别暴露于潜在不适当的药物(pim)。为了提高NH药物处方的质量和安全性,已经制定了许多策略,包括药物审查(MRs)。方法:在远程医疗应用的背景下,我们通过远程专家(或“远程医疗审查”,以下简称“远程医疗审查”[TMR])在法国NH居民中开发并目前正在实施一种新型的基于医院专家的MRs。评估这些TMR在实施后3个月对计划外住院的影响。TMR考虑与患者有关的所有可用的社会人口学、临床、生物学和药学数据,并根据患者的卫生保健目标进行。结果:迄今(2021年9月)进行的39例tmr的初步结果显示,共检测到402例PIM,所有居民都至少有一种PIM。我们还提出了这种新颖的TMR对NH的可行性和实用性,并用两个具体的TMR经验说明了这些初步结果。在执行的39例TMR中,向在NH工作的全科医生(GP)提出的专家建议的平均接受率为33%。讨论和结论:这种新颖的TMR的成功取决于医院专家团队提出的处方调整如何随后融入医疗保健实践。全科医生的低接受率突出表明,在制定TMR的过程中,需要积极地让这些专业人士参与进来,以鼓励他们对拟议的调整采取行动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Telemedication Reviews to Optimize Medication Prescription for Older People in Nursing Homes.

Introduction: Older people living in nursing homes (NH) are at a higher risk of preventable drug-related adverse events because of age-related physiological changes, polypathology, and polypharmacy. NH residents are particularly exposed to potentially inappropriate medications (PIMs). Many strategies have been developed to improve the quality and the safety of drug prescription in NH, including medication reviews (MRs). Methods: In the context of the application of telemedicine, we developed and are currently implementing a novel hospital expert-based MRs through tele-expertise (or "telemedication review," telemedication reviews hereafter [TMR]) in French NH residents. The impact of these TMR on unplanned hospitalizations 3 months after implementation is assessed. TMR consider all available sociodemographic, clinical, biological, and pharmaceutical data pertaining to the patient and are performed in accordance with their health care objectives. Results: The preliminary results for the 39 TMRs performed to date (September 2021) showed that a total of 402 PIMs were detected, and all residents had at least one PIM. We also present the feasibility and the usefulness of this novel TMR for NH, illustrating these preliminary results with two concrete TMR experiences. Among the 39 TMR performed, the average acceptance rate of expert recommendations made to general practitioners (GP) working in NH was ∼33%. Discussion and Conclusions: The success of this novel TMR depends on how the proposed prescription adjustments made by the hospital expert team are subsequently integrated into health care practices. The low acceptance rate by GP highlights the need to actively involve these professionals in the process of developing TMR, with a view to encouraging them to act on proposed adjustments.

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