Identification of Mood Disorders in Self-Reported Versus Health Administrative Data

IF 2.6 3区 心理学 Q2 BEHAVIORAL SCIENCES
Irène Dohouin, Maude Laberge, Anaïs Lacasse, Thomas G. Poder, TorSaDE Cohort working group
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引用次数: 0

Abstract

Background

Producing relevant knowledge on the prevalence of mood disorders (MDs) requires a clear identification of people living with the condition. Analyzing this multifaceted disease from the perspective of health administrative data and population-based surveys could contribute to document inconsistencies between these data sources and highlight the strengths and limitations of each methodological approaches.

Objectives

The aim of this study was to estimate the prevalence of MD disease, assess concordance of MD patterns in population-based surveys versus health administrative data, and investigate statistical differences in characteristics between individuals presenting the disease in each data sources.

Methods

This study used the Care Trajectories—Enriched Data (TorSaDE) cohort. The TorSaDE cohort is built by merging five waves of the Canadian Community Health Survey (CCHS) with health administrative data of the province of Quebec, Canada. The sample includes individuals who participated in at least one round of CCHS and for whom evidence of use of health services in the year of CCHS completion and the year before were present in health administrative data. The cohort was split into four groups based on the presence and absence of MD in self-reported versus health administrative data. Groups' characteristics were compared using chi-square tests and ANOVA.

Results

The study cohort was composed of 96,079 individuals, of which 10,418 (10.8%) had MD, regardless of the data sources. Self-reported prevalence of MD was 6.03%, while the prevalence from health administrative data was about 7.79%. Estimates showed a low level of concordance between the two measures, as only 27.4% of people presenting this medical condition were identified in both data sources. Furthermore, individuals identified with MD only in survey data had poorer socioeconomic outcomes but better health outcomes than those from the concordant group (i.e., identified in both data sources). In addition, people presenting MD in health administrative data only had better socioeconomic and health outcomes than those who reported MD diagnosis only in survey data.

Conclusion

Findings suggest that each measure capture different specific subpopulations. Estimates obtained from each source should thus be contextualized and interpreted with caution.

从自我报告和健康管理数据中识别情绪失调症。
背景:要获得有关情绪障碍(MDs)患病率的相关知识,需要明确识别情绪障碍患者。从卫生行政数据和人口调查的角度分析这种多发性疾病,有助于记录这些数据来源之间的不一致性,并突出每种方法的优势和局限性:本研究旨在估算MD疾病的患病率,评估基于人口的调查与卫生行政数据中MD模式的一致性,并调查两种数据来源中患病个体特征的统计差异:本研究使用了护理轨迹-丰富数据(TorSaDE)队列。TorSaDE 队列由加拿大社区健康调查(CCHS)的五次波次与加拿大魁北克省的卫生行政数据合并而成。样本包括至少参加过一轮加拿大社区健康调查的个人,这些人在完成加拿大社区健康调查的当年和前一年使用医疗服务的证据均存在于卫生管理数据中。根据自我报告与卫生行政数据中是否存在 MD,将人群分为四组。采用卡方检验和方差分析比较各组的特征:研究队列由 96,079 人组成,无论数据来源如何,其中 10,418 人(10.8%)患有 MD。自我报告的多发性硬化症患病率为 6.03%,而来自卫生行政数据的患病率约为 7.79%。估算结果表明,这两种测量方法的一致性较低,因为只有 27.4% 的人在两种数据来源中都被发现患有这种病症。此外,仅在调查数据中被识别出患有 MD 的人的社会经济状况较差,但其健康状况却优于一致组(即在两个数据源中均被识别出)的人。此外,与仅在调查数据中报告了 MD 诊断的人相比,仅在卫生行政数据中报告了 MD 的人具有更好的社会经济和健康结果:研究结果表明,每种测量方法都能捕捉到不同的特定亚人群。因此,从每种来源获得的估计值都应结合具体情况并谨慎解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Brain and Behavior
Brain and Behavior BEHAVIORAL SCIENCES-NEUROSCIENCES
CiteScore
5.30
自引率
0.00%
发文量
352
审稿时长
14 weeks
期刊介绍: Brain and Behavior is supported by other journals published by Wiley, including a number of society-owned journals. The journals listed below support Brain and Behavior and participate in the Manuscript Transfer Program by referring articles of suitable quality and offering authors the option to have their paper, with any peer review reports, automatically transferred to Brain and Behavior. * [Acta Psychiatrica Scandinavica](https://publons.com/journal/1366/acta-psychiatrica-scandinavica) * [Addiction Biology](https://publons.com/journal/1523/addiction-biology) * [Aggressive Behavior](https://publons.com/journal/3611/aggressive-behavior) * [Brain Pathology](https://publons.com/journal/1787/brain-pathology) * [Child: Care, Health and Development](https://publons.com/journal/6111/child-care-health-and-development) * [Criminal Behaviour and Mental Health](https://publons.com/journal/3839/criminal-behaviour-and-mental-health) * [Depression and Anxiety](https://publons.com/journal/1528/depression-and-anxiety) * Developmental Neurobiology * [Developmental Science](https://publons.com/journal/1069/developmental-science) * [European Journal of Neuroscience](https://publons.com/journal/1441/european-journal-of-neuroscience) * [Genes, Brain and Behavior](https://publons.com/journal/1635/genes-brain-and-behavior) * [GLIA](https://publons.com/journal/1287/glia) * [Hippocampus](https://publons.com/journal/1056/hippocampus) * [Human Brain Mapping](https://publons.com/journal/500/human-brain-mapping) * [Journal for the Theory of Social Behaviour](https://publons.com/journal/7330/journal-for-the-theory-of-social-behaviour) * [Journal of Comparative Neurology](https://publons.com/journal/1306/journal-of-comparative-neurology) * [Journal of Neuroimaging](https://publons.com/journal/6379/journal-of-neuroimaging) * [Journal of Neuroscience Research](https://publons.com/journal/2778/journal-of-neuroscience-research) * [Journal of Organizational Behavior](https://publons.com/journal/1123/journal-of-organizational-behavior) * [Journal of the Peripheral Nervous System](https://publons.com/journal/3929/journal-of-the-peripheral-nervous-system) * [Muscle & Nerve](https://publons.com/journal/4448/muscle-and-nerve) * [Neural Pathology and Applied Neurobiology](https://publons.com/journal/2401/neuropathology-and-applied-neurobiology)
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