Evidence map›Paper›PMID 21544512›Full record

ArticleEuropean journal of clinical pharmacology2011

Discrepancies between prescribed and defined daily doses: a matter of patients or drug classes?

Thomas Grimmsmann, Wolfgang Himmel

Abstract readComparative Study
In one paragraph

Article in European journal of clinical pharmacology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Thomas GrimmsmannMedical Review Board of the Statutory Health Insurance Funds Mecklenburg-Vorpommern, Schwerin, Germany. t.grimmsmann@mdk-mv.de
Wolfgang Himmel

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeDefined daily doses (DDD) are used for the measurement of drug utilisation. The aim of the study was to analyse whether differences between DDD and prescribed daily doses (PDD) exist for relevant drug classes such as antihypertensive drugs and, if so, whether they primarily depend on drug classes or patient-related factors.

methodsUsing the data of a large German statutory health insurance scheme, we analysed continuous prescriptions for the following antihypertensive drug classes: thiazide diuretics, beta-blockers, dihydropyridine calcium channel blockers (CCBs), angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin-II receptor blockers (ARBs). We summed the doses of all dispensed drugs per person during a defined time frame. We calculated the PDD (= total dose divided by the number of days) and expressed them as the PDD:DDD ratio (= amount of DDD per day and person).

resultsDuring the study period, 149,704 patients continuously received an antihypertensive medication. The average PDD:DDD ratio ranged from 0.84 (beta-blockers) to 1.88 (ARBs) and 2.17 (ACEIs). The average prescribed dosage of each drug class remained unchanged, even if the patients had previously received another antihypertensive drug with another PDD:DDD ratio. For example, if patients were switched from a beta-blocker to an ACEI, the PDD:DDD ratio increased, on average, from 0.79 to 2.17. Vice versa, the ratio decreased for patients with a drug change from an ACEI to a beta-blocker from 2.06 to 0.75.

conclusionsEven large differences between DDD and PDD seem to be a matter of drug classes and not primarily of patient characteristics.

Indexed as

AlgorithmsAntihypertensive AgentsDrug PrescriptionsDrug Utilization ReviewFemaleGermanyHumansHypertensionInsurance, Health, ReimbursementMaleNational Health ProgramsPrescription DrugsReproducibility of ResultsAntihypertensive AgentsPrescription Drugs

Identifiers

PMID21544512
PMCPMC3134712

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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.