Evidence map›Paper›PMID 16872246›Full record

ArticleDrug safety2006

Clinical risk management in Dutch community pharmacies: the case of drug-drug interactions.

Henk Buurma, Peter A G M De Smet, Antoine C G Egberts

Abstract read
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Article in Drug safety, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Article
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  8. Lower alert rates by clustering of related drug interaction alerts.Journal of the American Medical Informatics Association : JAMIA · 2017
    Article
  9. Nature and management of duplicate medication alerts.Journal of the American Medical Informatics Association : JAMIA · 2015
    Article
  10. Article
  11. Article
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  17. Use of anti-depressants and the risk of fracture of the hip or femur.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2009
    Article
  18. Article
  19. Article
  20. A nurse-led intervention for identification of drug-related problems.European journal of clinical pharmacology · 2008
    Article
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

3 authors.

Henk BuurmaSIR Institute for Pharmacy Practice and Policy, Leiden, The Netherlands. h.buurma@stevenshof.nl
Peter A G M De Smet
Antoine C G Egberts

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe prevention of drug-drug interactions requires a systematic approach for which the concept of clinical risk management can be used. The objective of our study was to measure the frequency, nature and management of drug-drug interaction alerts as these occur in daily practice of Dutch community pharmacies.

methodsIn total, 63 Dutch pharmacies collected all drug-drug interaction alerts during 153 research days (on average 2.4 days/pharmacy), as well as variables related to these alerts, such as involved medicines, first time or recurrent drug-drug interaction, same or different prescribers, patient data (age, sex) and information about the management of drug-drug interactions by the pharmacy. The latter was discriminated into internal procedures only and external action, such as communication with the patient, the prescriber or the anticoagulation clinic and prescription modification. All drug-drug interactions were classified into categories of clinical relevance (A-F) and available evidence (0-4).

resultsA total of 43,129 prescription-only medicines were dispensed during the study period. On average, 16.8 interaction alerts per day per pharmacy were collected. Approximately 6% of all prescriptions generated a drug-drug interaction alert. Of all alerts (n = 2572), 31.1% occurred for the first time and with 21% two different prescribers were involved. The 20 most frequently occurring drug-drug interaction alerts accounted for approximately 76% of all alerts. Cardiovascular drugs, NSAIDs, oral contraceptives and antibacterials were most frequently involved. External action was taken in response to 27.3% of the alerts, meaning either a modification of one of the concerned prescriptions (n = 65; 9.3%), communication with the prescriber or anticoagulation clinic (n = 90; 12.8%) or communication with the patient or a relative (n = 547; 77.9%). Where there was no external action (n = 1860; 72.3%), pharmacists concluded in about two-thirds of cases that the drug-drug interaction had been managed in the past. Other reasons not to intervene externally were for instance: incorrect alert; acceptable drug-drug interaction; or outcome of the interaction considered irrelevant. Adjusted for several variables, a first alert was found to be a main determinant for external action. After stratifying for first alerts no other significant determinants were found.

conclusionsA high frequency of drug-drug interaction alerts was found. Most concerned recurrent alerts, which were the main reason not to act externally. Concerning the assessment phase in the risk-management process, drug-drug interactions with no or low evidence/relevance should be reconsidered. Concerning the management of drug-drug interactions in pharmacies, the opportunity to actively suppress alerts for a certain period of time should be studied in more detail. There are indicators that the management of patient-orientated advice could be improved and a greater degree of consistency developed for the management of first and recurrent interaction alerts.

Indexed as

Adverse Drug Reaction Reporting SystemsCommunity Pharmacy ServicesDrug InteractionsRisk ManagementAdolescentAdultAgedAnti-Bacterial AgentsAnti-Inflammatory Agents, Non-SteroidalCardiovascular AgentsChildChild, PreschoolContraceptives, OralFemaleHumansInfantAnti-Bacterial AgentsAnti-Inflammatory Agents, Non-SteroidalCardiovascular AgentsContraceptives, Oral

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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.