Dataset Information

Self-reported medication use validated through record linkage to national prescribing data.

ABSTRACT:

Objectives

Researchers need to be confident about the reliability of epidemiologic studies that quantify medication use through self-report. Some evidence suggests that psychiatric medications are systemically under-reported. Modern record linkage enables validation of self-report with national prescribing data as gold standard. Here, we investigated the validity of medication self-report for multiple medication types.

Study design and setting

Participants in the Generation Scotland population-based cohort (N = 10,244) recruited 2009-2011 self-reported regular usage of several commonly prescribed medication classes. This was matched against Scottish NHS prescriptions data using 3- and 6-month fixed time windows. Potential predictors of discordant self-report, including general intelligence and psychological distress, were studied via multivariable logistic regression.

Results

Antidepressants self-report showed very good agreement (κ = 0.85, [95% confidence interval (CI) 0.84-0.87]), comparable to antihypertensives (κ = 0.90 [CI 0.89-0.91]). Self-report of mood stabilizers showed moderate-poor agreement (κ = 0.42 [CI 0.33-0.50]). Relevant past medical history was the strongest predictor of self-report sensitivity, whereas general intelligence was not predictive.

Conclusion

In this large population-based study, we found self-report validity varied among medication classes, with no simple relationship between psychiatric medication and under-reporting. History of indicated illness predicted more accurate self-report, for both psychiatric and nonpsychiatric medications. Although other patient-level factors influenced self-report for some medications, none predicted greater accuracy across all medications studied.

SUBMITTER: Hafferty JD

PROVIDER: S-EPMC5808931 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Publications

Self-reported medication use validated through record linkage to national prescribing data.

Hafferty Jonathan D JD Campbell Archie I AI Navrady Lauren B LB Adams Mark J MJ MacIntyre Donald D Lawrie Stephen M SM Nicodemus Kristin K Porteous David J DJ McIntosh Andrew M AM

Journal of clinical epidemiology 20171031

<h4>Objectives</h4>Researchers need to be confident about the reliability of epidemiologic studies that quantify medication use through self-report. Some evidence suggests that psychiatric medications are systemically under-reported. Modern record linkage enables validation of self-report with national prescribing data as gold standard. Here, we investigated the validity of medication self-report for multiple medication types.<h4>Study design and setting</h4>Participants in the Generation Scotla ...[more]

PMID: 29097340

Similar Datasets

Project description:BACKGROUND: There is a recognised need to build primary care medication adherence services which are tailored to patients' needs. Continuous quality improvement of such services requires a regular working method of measuring adherence in order to monitor effectiveness. Self report has been considered the method of choice for clinical use; it is cheap, relatively unobtrusive and able to distinguish between intentional and unintentional non-adherence, which have different underlying causes and therefore require different interventions. A self report adherence measure used in routine clinical practice would ideally be brief, acceptable to patients, valid, reliable, have the ability to distinguish between different types of non-adherence and be able to be completed by or in conjunction with carers where necessary. METHODS: We systematically reviewed the literature in order to identify self report adherence measures currently available which are suitable for primary care and evaluate the extent to which they met the criteria described above. We searched the databases Medline, Embase, International Pharmaceutical Abstracts, Pharmline, CINAHL, PsycINFO and HaPI to identify studies reporting the development, validation or reliability of generic adherence measures. One reviewer screened all abstracts and assessed all relevant full text articles obtained and a second reviewer screened/assessed 10% to check reliability. RESULTS: Fifty eight measures were identified. While validation data were presented in support of the vast majority of self reported measures (54/58), data for a relatively small number of measures was presented for reliability (16/58) and time to complete (3/58). Few were designed to have the ability to be completed by or in conjunction with carers and few were able to distinguish between different types of non-adherence, which limited their ability be used effectively in the continuous improvement of targeted adherence enhancing interventions. The data available suggested that patients find it easier to estimate general adherence than to report a specific number of doses missed. Visual analogue scales can be easier for patients than other types of scale but are not suitable for telephone administration. CONCLUSIONS: There is a need for a measure which can be used in the routine continual quality monitoring of adherence services.

Dataset Information

Self-reported medication use validated through record linkage to national prescribing data.

Objectives

Study design and setting

Results

Conclusion

Publications

Self-reported medication use validated through record linkage to national prescribing data.

Similar Datasets

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