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首页> 外文期刊>BMC Geriatrics >Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study
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Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study

机译:行政数据与居民评估工具最小数据集(RAI-MDS)之间在长期护理机构中使用药物的协议:基于人群的研究

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Background Prescription medication use, which is common among long-term care facility (LTCF) residents, is routinely used to describe quality of care and predict health outcomes. Data sources that capture medication information, which include surveys, medical charts, administrative health databases, and clinical assessment records, may not collect concordant information, which can result in comparable prevalence and effect size estimates. The purpose of this research was to estimate agreement between two population-based electronic data sources for measuring use of several medication classes among LTCF residents: outpatient prescription drug administrative data and the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0. Methods Prescription drug and RAI-MDS data from the province of Saskatchewan, Canada (population 1.1 million) were linked for 2010/11 in this cross-sectional study. Agreement for anti-psychotic, anti-depressant, and anti-anxiety/hypnotic medication classes was examined using prevalence estimates, Cohen’s κ, and positive and negative agreement. Mixed-effects logistic regression models tested resident and facility characteristics associated with disagreement. Results The cohort was comprised of 8,866 LTCF residents. In the RAI-MDS data, prevalence of anti-psychotics was 35.7%, while for anti-depressants it was 37.9% and for hypnotics it was 27.1%. Prevalence was similar in prescription drug data for anti-psychotics and anti-depressants, but lower for hypnotics (18.0%). Cohen’s κ ranged from 0.39 to 0.85 and was highest for the first two medication classes. Diagnosis of a mood disorder and facility affiliation was associated with disagreement for hypnotics. Conclusions Agreement between prescription drug administrative data and RAI-MDS assessment data was influenced by the type of medication class, as well as selected patient and facility characteristics. Researchers should carefully consider the purpose of their study, whether it is to capture medication that are dispensed or medications that are currently used by residents, when selecting a data source for research on LTCF populations.
机译:背景技术在长期护理机构(LTCF)居民中常见的处方药用法通常用于描述护理质量和预测健康结果。捕获药物信息的数据源(包括调查,病历表,行政健康数据库和临床评估记录)可能不会收集一致的信息,这可能导致可比的患病率和效应量估计值。这项研究的目的是估计两个基于人口的电子数据源之间的一致性,以测量LTCF居民中几种药物的使用情况:门诊处方药管理数据和居民评估工具最低数据集(RAI-MDS)版本2.0。方法在本横断面研究中,将2010/11年加拿大萨斯喀彻温省(人口110万)的处方药和RAI-MDS数据联系起来。抗精神病药,抗抑郁药和抗焦虑药/催眠药类别的协议使用患病率估算,Cohenκ以及阳性和阴性协议进行了检查。混合效应逻辑回归模型测试了与分歧相关的居民和设施特征。结果该队列由8,866名LTCF居民组成。在RAI-MDS数据中,抗精神病药的患病率为35.7%,而抗抑郁药的患病率为37.9%,催眠药的患病率为27.1%。抗精神病药和抗抑郁药的处方药数据相似,但催眠药的患病率较低(18.0%)。科恩的κ值介于0.39到0.85之间,在前两种药物类别中最高。情绪障碍和设施隶属关系的诊断与催眠药的分歧有关。结论处方药管理数据与RAI-MDS评估数据之间的一致性受药物类别的类型以及所选患者和设施特征的影响。研究人员在选择用于研究LTCF人群的数据源时,应仔细考虑研究目的,无论是捕获已分发的药物还是居民目前使用的药物。

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