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      Concordance assessment of self-reported medication use in the Netherlands three-generation Lifelines Cohort study with the pharmacy database iaDB.nl: The PharmLines initiative

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          Abstract

          Background

          While self-reported data are commonly used as a source of medication use for pharmaco-epidemiological studies, such information is prone to forms of bias. Several previous studies showed that various factors like age, type of drug and data collection method may influence accuracy. We aimed to assess the concordance of the self-reported medication use that was documented at entry to the Lifelines Cohort Study, a three-generation follow-up study in the Netherlands that started in 2006 and included over 167,000 participants.

          Materials and methods

          As part of the PharmLines Initiative, we collected medication data from the Lifelines participants encoded according to the Anatomical Therapeutic Chemical (ATC) coding scheme and linked the data via Statistics Netherlands to the widely used and representative pharmacy prescription database of the University of Groningen, IADB.nl. Analyses were conducted at second level of ATC coding for all recorded medications as well as a top list of most used medications at drug-specific fifth level. Cohen’s kappa statistics were used to measure the concordance for all participants according to sex and age.

          Results

          The level of concordance between the two data sources largely differed according to the therapeutic class. Medication used for the cardiovascular system and diabetes, thyroid therapy, bisphosphonates and anti-thrombotic drugs showed a very good agreement (κ>0.75). Medication as needed or prone to stigmatization bias showed a moderate agreement (κ=0.41–0.60), whereas medications used for short periods of time showed a fair agreement (κ=0.0–0.4). Concordance was similar for males and females, but younger adults tended to have lower concordance rates than older adults.

          Conclusion

          The self-reported method was valid for capturing prevalent chronic medication use at one moment in time, but invalid for medication used for short periods of time. There is no effect of sex on the agreement, and more studies are needed on the influence of age. Future pharmaco-epidemiological studies should preferably combine the two data sources to achieve the highest accuracy of drug exposure rates.

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          Most cited references15

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          Concordance between Patient Self-Reports and Claims Data on Clinical Diagnoses, Medication Use, and Health System Utilization in Taiwan

          Purpose The aim of this study was to evaluate the concordance between claims records in the National Health Insurance Research Database and patient self-reports on clinical diagnoses, medication use, and health system utilization. Methods In this study, we used the data of 15,574 participants collected from the 2005 Taiwan National Health Interview Survey. We assessed positive agreement, negative agreement, and Cohen's kappa statistics to examine the concordance between claims records and patient self-reports. Results Kappa values were 0.43, 0.64, and 0.61 for clinical diagnoses, medication use, and health system utilization, respectively. Using a strict algorithm to identify the clinical diagnoses recorded in claims records could improve the negative agreement; however, the effect on positive agreement and kappa was diverse across various conditions. Conclusion We found that the overall concordance between claims records in the National Health Insurance Research Database and patient self-reports in the Taiwan National Health Interview Survey was moderate for clinical diagnosis and substantial for both medication use and health system utilization.
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            Proper interpretation of non-differential misclassification effects: expectations vs observations.

            Many investigators write as if non-differential exposure misclassification inevitably leads to a reduction in the strength of an estimated exposure-disease association. Unfortunately, non-differentiality alone is insufficient to guarantee bias towards the null. Furthermore, because bias refers to the average estimate across study repetitions rather than the result of a single study, bias towards the null is insufficient to guarantee that an observed estimate will be an underestimate. Thus, as noted before, exposure misclassification can spuriously increase the observed strength of an association even when the misclassification process is non-differential and the bias it produced is towards the null. We present additional results on this topic, including a simulation study of how often an observed relative risk is an overestimate of the true relative risk when the bias is towards the null. The frequency of overestimation depends on many factors: the value of the true relative risk, exposure prevalence, baseline (unexposed) risk, misclassification rates, and other factors that influence bias and random error. Non-differentiality of exposure misclassification does not justify claims that the observed estimate must be an underestimate; further conditions must hold to get bias towards the null, and even when they do hold the observed estimate may by chance be an overestimate.
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              Recall accuracy for prescription medications: self-report compared with database information.

              A methodological study was performed in 1992 to evaluate the accuracy of self-reported use of nonsteroidal antiinflammatory drugs (NSAIDs) and noncontraceptive estrogens that had been dispensed during the previous 12 years. A sample of 560 individuals dispensed NSAIDs or estrogens, and 140 individuals without NSAID/estrogen dispensations were selected from the Group Health Cooperative pharmacy database. Demographic, behavioral, and drug information was ascertained by telephone interview for 356 persons with and 98 persons without NSAID/estrogen dispensations. Of those with only a single NSAID dispensation, 41% (95% confidence interval (CI) 32-50%) were able to recall any NSAID use compared with 85% (95% CI 76-94%) for those with multiple NSAID dispensations. Thirty percent (95% CI 24-36%) recalled the NSAID name, and 15% (95% CI 10-20%) recalled both the name and dose. For estrogens, 78% (95% CI 70-86%) recalled the name, but only 26% (95% CI 17-34%) recalled the name and dose. Age, but not sex, appeared to influence recall accuracy: Persons 50-65 years of age recalled the NSAID name more accurately than those aged 66-80 (odds ratio (OR) = 1.8, 95% confidence interval (CI) 1.0-3.4). A similar advantage was noted for 50- to 65-year-old women in recalling the estrogen name (OR = 1.5, 95% CI 0.6-3.9). Drug name was recalled more frequently for exposures stopped 2-3 years prior to interview than for those stopped 7-11 years prior (OR = 3.0, 95% CI 1.6-5.7, and OR = 2.4, 95% CI 0.9-6.7, for NSAIDs and estrogens, respectively). Specificity was consistently high, ranging from 92% to 100%. This study suggests significant underascertainment of self-reported prescription drug exposure but little evidence that exposures are overreported.
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                Author and article information

                Journal
                Clin Epidemiol
                Clin Epidemiol
                Clinical Epidemiology
                Clinical Epidemiology
                Dove Medical Press
                1179-1349
                2018
                16 August 2018
                : 10
                : 981-989
                Affiliations
                [1 ]Department of Pharmaco-Therapy, Epidemiology & Economics, University of Groningen, Groningen Research Institute of Pharmacy, Groningen, the Netherlands, e.hak@ 123456rug.nl
                [2 ]Lifelines Cohort Study, Lifelines Databeheer B.V., Groningen, the Netherlands
                [3 ]Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, Groningen, the Netherlands
                [4 ]Department of Epidemiology, University Medical Center Groningen, Groningen, the Netherlands, e.hak@ 123456rug.nl
                Author notes
                Correspondence: Eelko Hak, PharmacoTherapy, Epidemiology & Economics, Groningen Research Institute of Pharmacy, University of Groningen, Antonius Deusinglaan 1, 9713 AV Groningen, the Netherlands, Tel +31.50 363 7576, Email e.hak@ 123456rug.nl
                Article
                clep-10-981
                10.2147/CLEP.S163037
                6101003
                30147377
                ec896a81-ae8b-4758-af92-2c7c0975a79a
                © 2018 Sediq et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

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                Public health
                self-reported data,prescription data,pharmacy records,agreement,questionnaire,medication,interview,validity

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