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潜在不适当处方的卫生系统成本:一项基于人群的回顾性队列研究,使用加拿大安大略省的关联卫生行政数据库。

The Health System Costs of Potentially Inappropriate Prescribing: A Population-Based, Retrospective Cohort Study Using Linked Health Administrative Databases in Ontario, Canada.

作者信息

Black Cody D, Thavorn Kednapa, Coyle Doug, Bjerre Lise M

机构信息

School of Epidemiology and Public Health, University of Ottawa, Room 101, 600 Peter Morand Crescent, Ottawa, ON, K1G 5Z3, Canada.

Ottawa Hospital Research Institute, The Ottawa Hospital, 501 Smyth Box 511, Ottawa, ON, K1H 8L6, Canada.

出版信息

Pharmacoecon Open. 2020 Mar;4(1):27-36. doi: 10.1007/s41669-019-0143-2.

DOI:10.1007/s41669-019-0143-2
PMID:31218653
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7018908/
Abstract

OBJECTIVE

The aim of this study was to determine the health system costs from hospitalizations, emergency department (ED) visits, and medications due to potentially inappropriate prescribing (PIP) in Ontario, Canada, at the population-level.

METHODS

A retrospective cohort of individuals ≥ 66 years of age and prescribed at least one medication from April 2002 to March 2015 was identified using linked population-level health administrative databases from Ontario, Canada. Patients were identified as having PIP or no PIP by applying a subset of the Screening Tool of Older Persons' Potentially Inappropriate Prescribing/Screening Tool to Alert Doctors to Right Treatment (STOPP/START) criteria. The number of days spent in hospital, new medications prescribed, and ED visits in the 90 days following PIP or patient index date were captured, as well as the total costs from each of these health services. Count regression models were used to generate incidence rate ratios (IRRs) for each outcome given the presence of PIP versus no PIP and combined with the prevalence of PIP to generate population attributable fractions (PAFs). The PAF was then multiplied by the cost for each health service to obtain the costs attributable to PIP in the whole cohort, and by age and sex.

RESULTS

PIP was associated with an increased rate of hospitalization (IRR 2.77, 95% confidence interval [CI] 2.72-2.82), ED visits (IRR 1.87, 95% CI 1.82-1.92), and newly prescribed medications (IRR 1.13, 95% CI 1.13-1.14), resulting in PAFs of 55.7, 37.9, and 5.0% for each outcome, respectively. PIP was associated with 38.8% of the total spent on these healthcare services ($1.22 billion) in the 90 days after PIP. Costs attributable to PIP decreased with age despite increasing prevalence.

CONCLUSIONS

PIP in older adults is a significant source of health system costs from healthcare service use beyond medication costs, with a significant portion of hospitalizations and ED visit costs attributable to PIP. Future work should focus on identifying strategies and priorities for intervention.

摘要

目的

本研究旨在确定加拿大安大略省因潜在不适当处方(PIP)导致的住院、急诊就诊和药物治疗方面的卫生系统成本,以人群为基础进行评估。

方法

利用加拿大安大略省的人口水平卫生行政数据库,确定了一个回顾性队列,队列中的个体年龄≥66岁,在2002年4月至2015年3月期间至少开具了一种药物处方。通过应用老年人潜在不适当处方筛查工具/提醒医生正确治疗的筛查工具(STOPP/START)标准的一个子集,将患者确定为有PIP或无PIP。记录PIP或患者索引日期后90天内的住院天数、新开具的药物以及急诊就诊情况,以及这些卫生服务各自的总成本。使用计数回归模型生成有PIP与无PIP情况下各结局的发病率比(IRR),并结合PIP的患病率生成人群归因分数(PAF)。然后将PAF乘以每项卫生服务的成本,以获得整个队列中归因于PIP的成本,并按年龄和性别进行划分。

结果

PIP与住院率增加(IRR 2.77,95%置信区间[CI] 2.72 - 2.82)、急诊就诊率增加(IRR 1.87,95% CI 1.82 - 1.92)以及新开具药物增加(IRR 1.13,95% CI 1.13 - 1.14)相关,各结局的PAF分别为55.7%、37.9%和5.0%。PIP与PIP后90天内这些医疗服务总支出的38.8%(12.2亿美元)相关。尽管患病率增加,但归因于PIP的成本随年龄增长而降低。

结论

老年人中的PIP是卫生系统成本的一个重要来源,不仅包括药物成本,还包括因使用医疗服务产生的成本,很大一部分住院和急诊就诊成本可归因于PIP。未来的工作应侧重于确定干预策略和重点。

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The Health System Costs of Potentially Inappropriate Prescribing: A Population-Based, Retrospective Cohort Study Using Linked Health Administrative Databases in Ontario, Canada.潜在不适当处方的卫生系统成本:一项基于人群的回顾性队列研究,使用加拿大安大略省的关联卫生行政数据库。
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本文引用的文献

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BMJ Open. 2018 Jun 27;8(6):e021727. doi: 10.1136/bmjopen-2018-021727.
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Assessing potentially inappropriate prescribing (PIP) and predicting patient outcomes in Ontario's older population: a population-based cohort study applying subsets of the STOPP/START and Beers' criteria in large health administrative databases.评估安大略省老年人群中潜在不适当处方(PIP)并预测患者预后:一项基于人群的队列研究,在大型卫生管理数据库中应用STOPP/START标准和Beers标准的子集
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