Outcomes of a Medication Optimization Virtual Interdisciplinary Geriatric Specialist (MOVING) Program: A Feasibility Study.

IF 1.9 Q3 PHARMACOLOGY & PHARMACY Drugs - Real World Outcomes Pub Date : 2024-03-01 Epub Date: 2023-11-26 DOI:10.1007/s40801-023-00403-0
Joanne Man-Wai Ho, Eric To, Rebecca Sammy, Matei Stoian, Jennifer Man-Han Tung, Robert Jack Bodkin, Lindsay Cox, Tony Antoniou, Sophiya Benjamin
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Abstract

Background: Adverse drug events among older adults result in significant mortality, morbidity and cost. This harm may be mitigated with appropriate prescribing and deprescribing. We sought to understand the prescribing outcomes of an interdisciplinary geriatric virtual consultation service.

Methods: We conducted a retrospective, before-and-after feasibility study to measure prescribing outcomes for a medication optimization virtual interdisciplinary geriatric specialist (MOVING) programme comprised of expertise from geriatric clinical pharmacology, pharmacy and psychiatry for older adults (aged ≥ 65 years) between June and December 2018, Ontario, Canada. The primary outcome was the number of distinct prescriptions and the presence of polypharmacy (defined as ≥ 4 medications) before and after the service. Secondary outcomes included the number of as needed and regularly administered prescriptions, number of potentially inappropriate prescriptions as defined by the Beers and STOPP criteria, and number of prescriptions for psychotropics, long-acting opioids and diabetic medications.

Results: We studied 40 patients with a mean age of 80.6 [standard deviation (SD) 8.8] years who received a MOVING consult. We found no significant change in the mean total number of prescriptions per patient before (12.02, SD 5.83) and after the intervention (11.58, SD 5.28), with a mean difference of -0.45 [95% confidence interval (CI) -0.94 to 0.04; p = 0.07]. We found statistically significant decreases in as needed prescriptions (mean difference - 0.30, 95% CI - 0.45 to - 0.15; p<0.001), and potentially harmful medications as identified by the Beers (mean difference -1.25, 95% CI -2.00 to -0.50; p = 0.002) and STOPP (mean difference -1.65, 95% CI -2.33 to -0.97; p < 0.001) scores. Without including the cost savings from hospital diversion by a MOVING consult, the costs of a MOVING consult were $545.80-$629.80 per person, compared with the costs associated with traditional in-person consults involving similar specialist clinical services ($904.89-$1270.69 per person).

Conclusion: A MOVING model of care is associated with decreases in prescriptions for potentially inappropriate medications in older adults. These findings support further evaluation to ascertain health system impacts.

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药物优化虚拟跨学科老年专家(移动)计划的结果:可行性研究。
背景:老年人药物不良事件导致显著的死亡率、发病率和成本。这种危害可以通过适当的处方和解除处方来减轻。我们试图了解一个跨学科的老年虚拟咨询服务的处方结果。方法:我们进行了一项回顾性的前后可行性研究,以衡量2018年6月至12月期间加拿大安大略省老年人(年龄≥65岁)的药物优化虚拟跨学科老年专家(MOVING)计划的处方结果,该计划由老年临床药理学、药学和精神病学专业知识组成。主要观察指标是服务前后不同处方的数量和多药(定义为≥4种药物)的存在。次要结果包括按需和定期给药的处方数量,根据Beers和STOPP标准定义的可能不适当的处方数量,以及精神药物、长效阿片类药物和糖尿病药物的处方数量。结果:我们研究了40例接受MOVING咨询的患者,平均年龄为80.6[标准差(SD) 8.8]岁。我们发现干预前(12.02,SD 5.83)和干预后(11.58,SD 5.28)每位患者的平均处方总数无显著变化,平均差异为-0.45[95%置信区间(CI) -0.94 ~ 0.04;P = 0.07]。我们发现按需处方的减少具有统计学意义(平均差异- 0.30,95% CI - 0.45至- 0.15;结论:移动护理模式与老年人潜在不适当药物处方的减少有关。这些发现支持进一步评估以确定卫生系统的影响。
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来源期刊
Drugs - Real World Outcomes
Drugs - Real World Outcomes PHARMACOLOGY & PHARMACY-
CiteScore
3.60
自引率
5.00%
发文量
49
审稿时长
8 weeks
期刊介绍: Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.
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