Evidence map›Paper›PMID 36011791›Full record

ArticleInternational journal of environmental research and public health2022

The Impact of International Nonproprietary Names Integration on Prescribing Reimbursement Medicines for Arterial Hypertension and Analysis of Medication Errors in Latvia.

Anna Gavrilova, Maksims Zolovs, Gustavs Latkovskis, Inga Urtāne

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 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

4 authors.

Anna GavrilovaDepartment of Pharmaceutical Chemistry, Faculty of Pharmacy, Riga Stradins University, LV-1007 Riga, Latvia.ORCID 0000-0003-3264-1243
Maksims ZolovsStatistical Unit, Faculty of Medicine, Riga Stradins University, LV-1048 Riga, Latvia.ORCID 0000-0001-9120-5869
Gustavs LatkovskisInstitute of Cardiology and Regenerative Medicine, University of Latvia, LV-1586 Riga, Latvia.
Inga UrtāneDepartment of Pharmaceutical Chemistry, Faculty of Pharmacy, Riga Stradins University, LV-1007 Riga, Latvia.ORCID 0000-0002-7711-5573

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of international nonproprietary names (INNs) has been mandatory for prescriptions of state-reimbursed drugs in Latvia since 1 April 2020. In a retrospective analysis, we aimed to examine the impact of the new regulation on changes in the prescribing and dispensing practice of antihypertensive agents with an example of bisoprolol or/and perindopril and their combinations. All state-reimbursed bisoprolol and/or perindopril prescriptions for arterial hypertension were evaluated in two time periods: 1 April 2018 to 31 March 2019 and 1 April 2020 to 31 March 2021. The proportion of INN prescriptions increased from 2.1% to 92.3% (p < 0.001, φ = 0.903). The rate of fixed-dose combinations (FDCs) increased from 60.8% to 66.5% (p < 0.001, φ = 0.059). The rate of medication errors was 0.6%. The most common (80.6%) error was that the dispensed medicine dose was larger or smaller than indicated on the prescription. In addition, prescribing an FDC medicine increased the chance of making an error by 2.5 times on average. Regulatory changes dramatically affected the medicine-prescribing habits of INNs. The increase in FDC prescription rates may align with the recommendations of the 2018 ESC/ESH guidelines. The proportion of total errors is estimated as low, but control mechanisms are needed to prevent them.

Indexed as

HypertensionPerindoprilBisoprololHumansLatviaMedication ErrorsRetrospective StudiesBisoprololPerindoprildatabasedispensingeHealthelectronic prescriptionFDCfixed-dose combinationpharmacistsprimary careregulatory changes

Identifiers

PMID36011791
PMCPMC9408624

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Registered trials

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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.