ArticleBMC research notes2016
Application of a framework for determining number of drugs.
Article in BMC research notes, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of methods for determining cross-sectional active medications using pharmacy databases.Pharmacoepidemiology and drug safety · 2019Pooled it
- Perspective of older people on which medicines they need to report to healthcare professionals as part of a medicines history: a qualitative descriptive study.International journal of clinical pharmacy · 2025Article
- Validation of self-reported medication use for hypertension, diabetes, and dyslipidemia among employees of large-sized companies in Japan.Journal of occupational health · 2020Article
- Comparison of Pharmacy Database Methods for Determining Prevalent Chronic Medication Use.Medical care · 2019Article
- Assessment of polypharmacy in elderly patients by using data from dispensed medications in community pharmacies: analysis of results by using different methods of estimation.International journal of clinical pharmacy · 2018Observational
- Intensification of older adults' outpatient blood pressure treatment at hospital discharge: national retrospective cohort study.BMJ (Clinical research ed.) · 2018Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundThere are many different methodologies used in the literature for determining the number of drugs used by a patient, and many are incompletely described. This may be attributable to the lack of a framework to help investigators choose and describe their methods and the lack of evidence on the implications of the choice. The purpose of the study was to propose a framework and illustrate how that framework can be used to create and succinctly describe various approaches to counting the number of drugs used by patients and to examine the impact of varying individual components of the framework on the resulting drug count.
methodsThe three component framework requires specification of scope, uniqueness, and timeframe. The framework was applied to Medicare beneficiaries admitted for acute myocardial infarction in 2008. Drug use was ascertained by Part D prescription drug event files. A default measure for drug count was established, and fourteen additional measures were created by separately altering individual components of the default to illustrate the application of the framework and understand how these changes impacted drug count. Median drug counts and the frequency distributions of beneficiaries experiencing a change in count from default were produced for each measure.
resultsThe median drug count for the default measure was 4. Alteration of the timeframe component had the largest impact on drug counts, with a look-back period of 180 days producing a median count of 8 and changing the count by at least two for 73 % of patients. Variations of the other components had less impact.
conclusionOur framework is intended to be used by investigators to select an approach to counting number of drugs in their studies. Extending the timeframe over which fills from a pharmacy refill database could be counted toward the drug count produced the greatest changes in the number of drugs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.