Evidence map›Paper›PMID 29316910›Full record

ArticleBMC health services research2018

Determinants of new drugs prescription in the Swiss healthcare market.

Anne Decollogny, Romain Piaget-Rossel, Patrick Taffé, Yves Eggli

Abstract read
In one paragraph

Article in BMC health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Newer long-acting insulin prescriptions for patients with type 2 diabetes: prevalence and practice variation in a retrospective cohort study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2022
    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

4 authors.

Anne DecollognyInstitute of Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois and Faculty of Biology and Medicine, Route de la Corniche 10, 1010, Lausanne, Switzerland. anne.decollogny@chuv.ch.ORCID 0000-0003-0607-2593
Romain Piaget-RosselInstitute of Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois and Faculty of Biology and Medicine, Route de la Corniche 10, 1010, Lausanne, Switzerland.
Patrick TafféInstitute of Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois and Faculty of Biology and Medicine, Route de la Corniche 10, 1010, Lausanne, Switzerland.
Yves EggliInstitute of Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois and Faculty of Biology and Medicine, Route de la Corniche 10, 1010, Lausanne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDrug markets are very complex and, while many new drugs are registered each year, little is known about what drives the prescription of these new drugs. This study attempts to lift the veil from this important subject by analyzing simultaneously the impact of several variables on the prescription of novelty.

methodsData provided by four Swiss sickness funds were analyzed. These data included information about more than 470,000 insured, notably their drug intake. Outcome variable that captured novelty was the age of the drug prescribed. The overall variance in novelty was partitioned across five levels (substitutable drug market, patient, physician, region, and prescription) and the influence of several variables measured at each of these levels was assessed using a non-hierarchical multilevel model estimated by Bayesian Markov Chain Monte Carlo methods.

resultsMore than 92% of the variation in novelty was explained at the substitutable drug market-level and at the prescription-level. Newer drugs were prescribed in markets that were costlier, less concentrated, included more insured, provided more drugs and included more active substances. Over-the-counter drugs were on average 12.5 years older while generic drugs were more than 15 years older than non-generics. Regional disparities in terms of age of prescribed drugs could reach 2.8 years.

conclusionsRegulation of the demand has low impact, with little variation explained at the patient-level and physician-level. In contrary, the market structure (e.g. end of patent with generic apparition, concurrence among producers) had a strong contribution to the variation of drugs ages.

Indexed as

Drugs, GenericHealth Care SectorPrescription DrugsAdultAged, 80 and overBayes TheoremChildCross-Sectional StudiesDrug PrescriptionsFemaleHumansInsurance Claim ReviewMalePractice Patterns, Physicians'SwitzerlandDrugs, GenericPrescription DrugsBayesian Markov Chain Monte Carlo methodsDrug marketDrugs prescriptionNon-hierarchical multilevel modelPrescription drivers

Identifiers

PMID29316910
PMCPMC5759272

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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.