Pharmacoepidemiological methods for computing the duration of pharmacological prescriptions using secondary data sources.

Purpose: In pharmacoepidemiology, correctly defining the exposure period of pharmacological treatment is a challenging step when information on the time in treatment is missing or incomplete. Methods: In this review, we describe several methods for defining exposure to pharmacological treatments usi...

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Publicado en:European Journal of Clinical Pharmacology Vol. 77; no. 12; pp. 1805 - 1815
Autores principales: Meaidi, Marianne, Støvring, Henrik, Rostgaard, Klaus, Torp-Pedersen, Christian, Kragholm, Kristian Hay, Andersen, Morten, Sessa, Maurizio
Formato: review tables/charts Journal Article
Publicado: Springer Nature Dec2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2021
      vid: 77
      iid: 12
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s00228-021-03188-9
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        atl: Pharmacoepidemiological methods for computing the duration of pharmacological prescriptions using secondary data sources.
      aug:
        au:
          Meaidi, Marianne
          Støvring, Henrik
          Rostgaard, Klaus
          Torp-Pedersen, Christian
          Kragholm, Kristian Hay
          Andersen, Morten
          Sessa, Maurizio
        affil: Department of Drug Design and Pharmacology, University of Copenhagen, Jagtvej 160, 2100, København Ø, Denmark
      sug:
        subj:
          Drug Therapy Methods
          Treatment Duration
          Medication Compliance
          Prescriptions, Drug
          Research, Medical
      ab: Purpose: In pharmacoepidemiology, correctly defining the exposure period of pharmacological treatment is a challenging step when information on the time in treatment is missing or incomplete. Methods: In this review, we describe several methods for defining exposure to pharmacological treatments using secondary data sources that lack such information. Results and conclusion: Several methods for assessing the duration of redeemed prescriptions and combining them into temporal sequences are available. We present a set of considerations to make researchers aware of the potentials and pitfalls of these methods that may aid in minimizing biases in research using these methods. Additionally, we highlight that, to date, there is no one-size-fits-all solution. Thus, the choice of method should be based on their area of applicability combined with a careful mapping to the research scenario under investigation.
      pubtype: Academic Journal
      doctype:
        review
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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