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爱尔兰全科医疗中特定高风险药物实验室监测未达最佳标准的患病率及预测因素:一项针对社区居住老年人的5年回顾性队列研究

Prevalence and predictors of sub-optimal laboratory monitoring of selected higher risk medicines in Irish general practice: a 5-year retrospective cohort study of community-dwelling older adults.

作者信息

McCarthy Caroline, Moriarty Frank, Doherty Ann Sinéad, Feighery Mark, Boland Fiona, Fahey Tom, Wallace Emma

机构信息

Department of General Practice, RSCI University of Medicine and Health Sciences, Dublin, Ireland.

School of Pharmacy and Biomolecular Sciences, RSCI University of Medicine and Health Sciences, Dublin, Ireland.

出版信息

BMJ Open. 2025 Jan 25;15(1):e086446. doi: 10.1136/bmjopen-2024-086446.

DOI:10.1136/bmjopen-2024-086446
PMID:39863414
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11784346/
Abstract

OBJECTIVES

To describe the prevalence of sub-optimal monitoring for selected higher-risk medicines in older community-dwelling adults and to evaluate patient characteristics and outcomes associated with sub-optimal monitoring.

STUDY DESIGN

Retrospective observational study (2011-2015) using historical general practice-based cohort data and linked dispensing data from a national pharmacy claims database.

SETTING

Irish primary care.

PARTICIPANTS

625 community-dwelling adults aged ≥70 years and prescribed at least one higher-risk medicine during the 5-year study period.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome was the prevalence of sub-optimal laboratory monitoring using a composite measure of published medication monitoring indicators, with a focus on commonly prescribed higher-risk medicines such as diuretics and anticoagulants. Poisson regression was used to assess the patient characteristics associated with sub-optimal monitoring and explanatory variables included the number of medicines, age, sex, deprivation and anxiety/depression symptoms. Logistic regression was used to explore the association between baseline sub-optimal monitoring and the odds of adverse health outcomes (unplanned healthcare utilisation, adverse drug reactions and mortality).

RESULTS

Of 625 participants, the mean age was 77.7 years, 53% were female, the mean number of drugs was 7.3 (SD 3.3) and 499 (79.8%) had ≥1 unmonitored dispensing over 5 years. The number of drugs, deprivation and anxiety/depression symptoms were significantly associated with sub-optimal monitoring, with the strongest association seen for anxiety/depression symptoms (incidence rate ratio: 1.33, 95% CI 1.05 to 1.68). There was a small but significant association between baseline sub-optimal monitoring and emergency department visits at follow-up, but no evidence of an association with unplanned hospital admissions, mortality or adverse drug reactions.

CONCLUSION

The prevalence of sub-optimal medication monitoring was high, and number of drugs, deprivation and anxiety/depression symptoms were significantly associated with sub-optimal monitoring. However, the public health impact of these findings remains uncertain, as there was no clear evidence of an association between sub-optimal monitoring and adverse health outcomes. Further research is needed to evaluate the effect of improved monitoring strategies and the optimal timing for drug monitoring of higher risk medications.

摘要

目的

描述老年社区居住成年人中选定的高风险药物监测欠佳的患病率,并评估与监测欠佳相关的患者特征和结局。

研究设计

回顾性观察性研究(2011 - 2015年),使用基于历史全科医疗的队列数据以及来自国家药房索赔数据库的关联配药数据。

研究地点

爱尔兰初级医疗保健机构。

参与者

625名年龄≥70岁的社区居住成年人,在5年研究期间至少开具了一种高风险药物。

主要和次要结局指标

主要结局是使用已发表的药物监测指标的综合测量方法来衡量监测欠佳的实验室监测的患病率,重点关注常用的高风险药物,如利尿剂和抗凝剂。泊松回归用于评估与监测欠佳相关的患者特征,解释变量包括药物数量、年龄、性别、贫困程度和焦虑/抑郁症状。逻辑回归用于探讨基线监测欠佳与不良健康结局(非计划医疗保健利用、药物不良反应和死亡率)的几率之间的关联。

结果

在625名参与者中,平均年龄为77.7岁,53%为女性,平均药物数量为7.3(标准差3.3),499人(79.8%)在5年中有≥1次未监测的配药。药物数量、贫困程度和焦虑/抑郁症状与监测欠佳显著相关,其中焦虑/抑郁症状的关联最强(发病率比:1.33,95%置信区间1.05至1.68)。基线监测欠佳与随访时的急诊科就诊之间存在小但显著的关联,但没有证据表明与非计划住院、死亡率或药物不良反应有关联。

结论

监测欠佳的药物监测患病率很高,药物数量、贫困程度和焦虑/抑郁症状与监测欠佳显著相关。然而,这些发现对公共卫生的影响仍不确定,因为没有明确证据表明监测欠佳与不良健康结局之间存在关联。需要进一步研究来评估改进监测策略的效果以及高风险药物监测的最佳时机。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c3c/11784346/08b6d7725ff3/bmjopen-15-1-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c3c/11784346/08b6d7725ff3/bmjopen-15-1-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c3c/11784346/08b6d7725ff3/bmjopen-15-1-g001.jpg

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