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 using...
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Veröffentlicht in: | European journal of clinical pharmacology 2021-12, Vol.77 (12), p.1805-1814 |
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container_title | European journal of clinical pharmacology |
container_volume | 77 |
creator | Meaidi, Marianne Støvring, Henrik Rostgaard, Klaus Torp-Pedersen, Christian Kragholm, Kristian Hay Andersen, Morten Sessa, Maurizio |
description | 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. |
doi_str_mv | 10.1007/s00228-021-03188-9 |
format | Article |
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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.</description><identifier>ISSN: 0031-6970</identifier><identifier>EISSN: 1432-1041</identifier><identifier>DOI: 10.1007/s00228-021-03188-9</identifier><identifier>PMID: 34247270</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Biomedical and Life Sciences ; Biomedicine ; Data Collection - methods ; Drug dosages ; Drug Prescriptions - statistics & numerical data ; Drug therapy ; Drug Utilization ; Humans ; Medical research ; Methods ; Pharmacoepidemiology - methods ; Pharmacology ; Pharmacology/Toxicology ; Prescription Drugs - administration & dosage ; Prescriptions ; Review</subject><ispartof>European journal of clinical pharmacology, 2021-12, Vol.77 (12), p.1805-1814</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021</rights><rights>2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-9944c670f93968cd0ba56c2948f11ca8a9425147acdb4829deeec7aca723dad43</citedby><cites>FETCH-LOGICAL-c375t-9944c670f93968cd0ba56c2948f11ca8a9425147acdb4829deeec7aca723dad43</cites><orcidid>0000-0003-0874-4744</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00228-021-03188-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00228-021-03188-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,781,785,27926,27927,41490,42559,51321</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34247270$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Meaidi, Marianne</creatorcontrib><creatorcontrib>Støvring, Henrik</creatorcontrib><creatorcontrib>Rostgaard, Klaus</creatorcontrib><creatorcontrib>Torp-Pedersen, Christian</creatorcontrib><creatorcontrib>Kragholm, Kristian Hay</creatorcontrib><creatorcontrib>Andersen, Morten</creatorcontrib><creatorcontrib>Sessa, Maurizio</creatorcontrib><title>Pharmacoepidemiological methods for computing the duration of pharmacological prescriptions using secondary data sources</title><title>European journal of clinical pharmacology</title><addtitle>Eur J Clin Pharmacol</addtitle><addtitle>Eur J Clin Pharmacol</addtitle><description>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.</description><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Data Collection - methods</subject><subject>Drug dosages</subject><subject>Drug Prescriptions - statistics & numerical data</subject><subject>Drug therapy</subject><subject>Drug Utilization</subject><subject>Humans</subject><subject>Medical research</subject><subject>Methods</subject><subject>Pharmacoepidemiology - methods</subject><subject>Pharmacology</subject><subject>Pharmacology/Toxicology</subject><subject>Prescription Drugs - administration & dosage</subject><subject>Prescriptions</subject><subject>Review</subject><issn>0031-6970</issn><issn>1432-1041</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNp9kU2LFDEQhoMo7rj6BzxIwIuX1spHd5KjLH7Bgh70HDJJ9Uwv3Z021Q367804swoePIVKPe9bVbyMPRfwWgCYNwQgpW1AigaUsLZxD9hOaCUbAVo8ZDuo303nDFyxJ0R3AKJ1oB6zK6WlNtLAjv34cgxlCjHjMiSchjzmwxDDyCdcjzkR73PhMU_Ltg7zga9H5GkrYR3yzHPPl4v6XrUUpFiG5dQnvtFJQxjznEL5yVNYA6e8lYj0lD3qw0j47PJes2_v3329-djcfv7w6ebtbROVadfGOa1jZ6B3ynU2JtiHtovSadsLEYMNTstWaBNi2msrXULEWKtgpEohaXXNXp19l5K_b0irnwaKOI5hxryRl20LXfWTrqIv_0Hv6q5z3a5SrhPGWmMqJc9ULJmoYO-XMkz1PC_An3Lx51x8zcX_zsWfrF9crLf9hOmP5D6ICqgzQLU1H7D8nf0f218Toptf</recordid><startdate>20211201</startdate><enddate>20211201</enddate><creator>Meaidi, Marianne</creator><creator>Støvring, Henrik</creator><creator>Rostgaard, Klaus</creator><creator>Torp-Pedersen, Christian</creator><creator>Kragholm, Kristian Hay</creator><creator>Andersen, Morten</creator><creator>Sessa, Maurizio</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7TK</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-0874-4744</orcidid></search><sort><creationdate>20211201</creationdate><title>Pharmacoepidemiological methods for computing the duration of pharmacological prescriptions using secondary data sources</title><author>Meaidi, Marianne ; Støvring, Henrik ; Rostgaard, Klaus ; Torp-Pedersen, Christian ; Kragholm, Kristian Hay ; Andersen, Morten ; Sessa, Maurizio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-9944c670f93968cd0ba56c2948f11ca8a9425147acdb4829deeec7aca723dad43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Data Collection - methods</topic><topic>Drug dosages</topic><topic>Drug Prescriptions - statistics & numerical data</topic><topic>Drug therapy</topic><topic>Drug Utilization</topic><topic>Humans</topic><topic>Medical research</topic><topic>Methods</topic><topic>Pharmacoepidemiology - methods</topic><topic>Pharmacology</topic><topic>Pharmacology/Toxicology</topic><topic>Prescription Drugs - administration & dosage</topic><topic>Prescriptions</topic><topic>Review</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Meaidi, Marianne</creatorcontrib><creatorcontrib>Støvring, Henrik</creatorcontrib><creatorcontrib>Rostgaard, Klaus</creatorcontrib><creatorcontrib>Torp-Pedersen, Christian</creatorcontrib><creatorcontrib>Kragholm, Kristian Hay</creatorcontrib><creatorcontrib>Andersen, Morten</creatorcontrib><creatorcontrib>Sessa, Maurizio</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>European journal of clinical pharmacology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Meaidi, Marianne</au><au>Støvring, Henrik</au><au>Rostgaard, Klaus</au><au>Torp-Pedersen, Christian</au><au>Kragholm, Kristian Hay</au><au>Andersen, Morten</au><au>Sessa, Maurizio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Pharmacoepidemiological methods for computing the duration of pharmacological prescriptions using secondary data sources</atitle><jtitle>European journal of clinical pharmacology</jtitle><stitle>Eur J Clin Pharmacol</stitle><addtitle>Eur J Clin Pharmacol</addtitle><date>2021-12-01</date><risdate>2021</risdate><volume>77</volume><issue>12</issue><spage>1805</spage><epage>1814</epage><pages>1805-1814</pages><issn>0031-6970</issn><eissn>1432-1041</eissn><abstract>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.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>34247270</pmid><doi>10.1007/s00228-021-03188-9</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-0874-4744</orcidid></addata></record> |
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subjects | Biomedical and Life Sciences Biomedicine Data Collection - methods Drug dosages Drug Prescriptions - statistics & numerical data Drug therapy Drug Utilization Humans Medical research Methods Pharmacoepidemiology - methods Pharmacology Pharmacology/Toxicology Prescription Drugs - administration & dosage Prescriptions Review |
title | Pharmacoepidemiological methods for computing the duration of pharmacological prescriptions using secondary data sources |
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