Comparison of record linkage software for deduplicating patient identities in California's Prescription Drug Monitoring Program
Background To help prevent overdose deaths involving prescription drugs, accurate linkage of prescription drug monitoring program (PDMP) records for individual patients is essential. Objectives To compare the accuracy of the linkage program used by California's PDMP against various record linka...
Gespeichert in:
Veröffentlicht in: | Pharmacoepidemiology and drug safety 2024-01, Vol.33 (1), p.e5699-n/a |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | n/a |
---|---|
container_issue | 1 |
container_start_page | e5699 |
container_title | Pharmacoepidemiology and drug safety |
container_volume | 33 |
creator | Stewart, Susan L. Crawford, Andrew Shev, Aaron B. Wintemute, Garen Tseregounis, Iraklis Erik Henry, Stephen G. |
description | Background
To help prevent overdose deaths involving prescription drugs, accurate linkage of prescription drug monitoring program (PDMP) records for individual patients is essential.
Objectives
To compare the accuracy of the linkage program used by California's PDMP against various record linkage programs with respect to accuracy in deduplicating patient identities in the PDMP, with implications for identifying high‐risk opioid use and outlier behaviors.
Research Design
We evaluated California's program, Link Plus, LinkSolv, and The Link King on 557 861 PDMP identity records with addresses in two 3‐digit zip code areas for patients who filled a controlled substance prescription in 2013. Manual review was performed on a stratified sample of 720 paired records identified as matches by at least one program.
Measures
We estimated sensitivity and positive predictive value, and computed PDMP patient alerts for the patient entities identified by each program.
Results
Sensitivity was 95% for LinkSolv and The Link King, 84% for Link Plus, and 73% for California's program; positive predictive value was ≥93% for all programs. The number of patient entities prompting a PDMP alert was similar among the programs for all alerts except multiple provider episodes (obtaining prescriptions from ≥6 prescribers or ≥6 pharmacies in the last 6 months), which were 10.9%, 26.6%, and 16.9% greater using The Link King, Link Plus, and LinkSolv, respectively, compared to California's program.
Conclusions
PDMPs should assess the accuracy of record linkage algorithms and the impacts of these algorithms on patient safety alerts and develop national best practices for PDMP record linkage. |
doi_str_mv | 10.1002/pds.5699 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2871654230</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2916357454</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3839-6d87c865aac27a8088f2210b1a5210292ff460bad389d730225cc8bac91689e13</originalsourceid><addsrcrecordid>eNp1kU1LHTEUhkNpqVaF_gIJdNFuRvMxmSTLcu0XKF6wrkNukrlEZ5LxZAZx1b9ubrUWCt3kPXCePBx4EXpPyQklhJ1OvpyITutXaJ8SrRsqhHy9mwVvVF3soXel3BBSd7p9i_a4lFJzLvfRr1UeJwux5IRzjyG4DB4PMd3abcAl9_O9hYD7DNgHv0xDdHaOaYunGiHNOPr6xjoXHBNe2SFWNkX7seA1hOIgTnOs8jNYtvgipzhn2P1fQ96CHQ_Rm94OJRw95wG6_vrl5-p7c3757cfq83njuOK66bySTnXCWsekVUSpnjFKNtSKGkyzvm87srGeK-0lJ4wJ59TGOk07pQPlB-jTk3eCfLeEMpsxFheGwaaQl2KYkrQTLeOkoh_-QW_yAqleZ1jVcSFb0f4VOsilQOjNBHG08GAoMbtSTC3F7Eqp6PGzcNmMwb-Af1qoQPME3MchPPxXZNZnV7-Fj2uglx4</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2916357454</pqid></control><display><type>article</type><title>Comparison of record linkage software for deduplicating patient identities in California's Prescription Drug Monitoring Program</title><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>Stewart, Susan L. ; Crawford, Andrew ; Shev, Aaron B. ; Wintemute, Garen ; Tseregounis, Iraklis Erik ; Henry, Stephen G.</creator><creatorcontrib>Stewart, Susan L. ; Crawford, Andrew ; Shev, Aaron B. ; Wintemute, Garen ; Tseregounis, Iraklis Erik ; Henry, Stephen G.</creatorcontrib><description>Background
To help prevent overdose deaths involving prescription drugs, accurate linkage of prescription drug monitoring program (PDMP) records for individual patients is essential.
Objectives
To compare the accuracy of the linkage program used by California's PDMP against various record linkage programs with respect to accuracy in deduplicating patient identities in the PDMP, with implications for identifying high‐risk opioid use and outlier behaviors.
Research Design
We evaluated California's program, Link Plus, LinkSolv, and The Link King on 557 861 PDMP identity records with addresses in two 3‐digit zip code areas for patients who filled a controlled substance prescription in 2013. Manual review was performed on a stratified sample of 720 paired records identified as matches by at least one program.
Measures
We estimated sensitivity and positive predictive value, and computed PDMP patient alerts for the patient entities identified by each program.
Results
Sensitivity was 95% for LinkSolv and The Link King, 84% for Link Plus, and 73% for California's program; positive predictive value was ≥93% for all programs. The number of patient entities prompting a PDMP alert was similar among the programs for all alerts except multiple provider episodes (obtaining prescriptions from ≥6 prescribers or ≥6 pharmacies in the last 6 months), which were 10.9%, 26.6%, and 16.9% greater using The Link King, Link Plus, and LinkSolv, respectively, compared to California's program.
Conclusions
PDMPs should assess the accuracy of record linkage algorithms and the impacts of these algorithms on patient safety alerts and develop national best practices for PDMP record linkage.</description><identifier>ISSN: 1053-8569</identifier><identifier>EISSN: 1099-1557</identifier><identifier>DOI: 10.1002/pds.5699</identifier><identifier>PMID: 37779337</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Inc</publisher><subject>Accuracy ; Algorithms ; California - epidemiology ; controlled substance ; Drug Prescriptions ; Humans ; Opioid-Related Disorders ; overdose prevention ; Prescription Drug Monitoring Programs ; Prescription drugs ; prescription registry ; record linkage ; Software</subject><ispartof>Pharmacoepidemiology and drug safety, 2024-01, Vol.33 (1), p.e5699-n/a</ispartof><rights>2023 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2023 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.</rights><rights>2023. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3839-6d87c865aac27a8088f2210b1a5210292ff460bad389d730225cc8bac91689e13</citedby><cites>FETCH-LOGICAL-c3839-6d87c865aac27a8088f2210b1a5210292ff460bad389d730225cc8bac91689e13</cites><orcidid>0000-0002-1593-440X ; 0000-0002-5643-0881</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fpds.5699$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fpds.5699$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,1411,27903,27904,45553,45554</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37779337$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Stewart, Susan L.</creatorcontrib><creatorcontrib>Crawford, Andrew</creatorcontrib><creatorcontrib>Shev, Aaron B.</creatorcontrib><creatorcontrib>Wintemute, Garen</creatorcontrib><creatorcontrib>Tseregounis, Iraklis Erik</creatorcontrib><creatorcontrib>Henry, Stephen G.</creatorcontrib><title>Comparison of record linkage software for deduplicating patient identities in California's Prescription Drug Monitoring Program</title><title>Pharmacoepidemiology and drug safety</title><addtitle>Pharmacoepidemiol Drug Saf</addtitle><description>Background
To help prevent overdose deaths involving prescription drugs, accurate linkage of prescription drug monitoring program (PDMP) records for individual patients is essential.
Objectives
To compare the accuracy of the linkage program used by California's PDMP against various record linkage programs with respect to accuracy in deduplicating patient identities in the PDMP, with implications for identifying high‐risk opioid use and outlier behaviors.
Research Design
We evaluated California's program, Link Plus, LinkSolv, and The Link King on 557 861 PDMP identity records with addresses in two 3‐digit zip code areas for patients who filled a controlled substance prescription in 2013. Manual review was performed on a stratified sample of 720 paired records identified as matches by at least one program.
Measures
We estimated sensitivity and positive predictive value, and computed PDMP patient alerts for the patient entities identified by each program.
Results
Sensitivity was 95% for LinkSolv and The Link King, 84% for Link Plus, and 73% for California's program; positive predictive value was ≥93% for all programs. The number of patient entities prompting a PDMP alert was similar among the programs for all alerts except multiple provider episodes (obtaining prescriptions from ≥6 prescribers or ≥6 pharmacies in the last 6 months), which were 10.9%, 26.6%, and 16.9% greater using The Link King, Link Plus, and LinkSolv, respectively, compared to California's program.
Conclusions
PDMPs should assess the accuracy of record linkage algorithms and the impacts of these algorithms on patient safety alerts and develop national best practices for PDMP record linkage.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>California - epidemiology</subject><subject>controlled substance</subject><subject>Drug Prescriptions</subject><subject>Humans</subject><subject>Opioid-Related Disorders</subject><subject>overdose prevention</subject><subject>Prescription Drug Monitoring Programs</subject><subject>Prescription drugs</subject><subject>prescription registry</subject><subject>record linkage</subject><subject>Software</subject><issn>1053-8569</issn><issn>1099-1557</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>EIF</sourceid><recordid>eNp1kU1LHTEUhkNpqVaF_gIJdNFuRvMxmSTLcu0XKF6wrkNukrlEZ5LxZAZx1b9ubrUWCt3kPXCePBx4EXpPyQklhJ1OvpyITutXaJ8SrRsqhHy9mwVvVF3soXel3BBSd7p9i_a4lFJzLvfRr1UeJwux5IRzjyG4DB4PMd3abcAl9_O9hYD7DNgHv0xDdHaOaYunGiHNOPr6xjoXHBNe2SFWNkX7seA1hOIgTnOs8jNYtvgipzhn2P1fQ96CHQ_Rm94OJRw95wG6_vrl5-p7c3757cfq83njuOK66bySTnXCWsekVUSpnjFKNtSKGkyzvm87srGeK-0lJ4wJ59TGOk07pQPlB-jTk3eCfLeEMpsxFheGwaaQl2KYkrQTLeOkoh_-QW_yAqleZ1jVcSFb0f4VOsilQOjNBHG08GAoMbtSTC3F7Eqp6PGzcNmMwb-Af1qoQPME3MchPPxXZNZnV7-Fj2uglx4</recordid><startdate>202401</startdate><enddate>202401</enddate><creator>Stewart, Susan L.</creator><creator>Crawford, Andrew</creator><creator>Shev, Aaron B.</creator><creator>Wintemute, Garen</creator><creator>Tseregounis, Iraklis Erik</creator><creator>Henry, Stephen G.</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><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>7TK</scope><scope>K9.</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-1593-440X</orcidid><orcidid>https://orcid.org/0000-0002-5643-0881</orcidid></search><sort><creationdate>202401</creationdate><title>Comparison of record linkage software for deduplicating patient identities in California's Prescription Drug Monitoring Program</title><author>Stewart, Susan L. ; Crawford, Andrew ; Shev, Aaron B. ; Wintemute, Garen ; Tseregounis, Iraklis Erik ; Henry, Stephen G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3839-6d87c865aac27a8088f2210b1a5210292ff460bad389d730225cc8bac91689e13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>California - epidemiology</topic><topic>controlled substance</topic><topic>Drug Prescriptions</topic><topic>Humans</topic><topic>Opioid-Related Disorders</topic><topic>overdose prevention</topic><topic>Prescription Drug Monitoring Programs</topic><topic>Prescription drugs</topic><topic>prescription registry</topic><topic>record linkage</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Stewart, Susan L.</creatorcontrib><creatorcontrib>Crawford, Andrew</creatorcontrib><creatorcontrib>Shev, Aaron B.</creatorcontrib><creatorcontrib>Wintemute, Garen</creatorcontrib><creatorcontrib>Tseregounis, Iraklis Erik</creatorcontrib><creatorcontrib>Henry, Stephen G.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Pharmacoepidemiology and drug safety</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Stewart, Susan L.</au><au>Crawford, Andrew</au><au>Shev, Aaron B.</au><au>Wintemute, Garen</au><au>Tseregounis, Iraklis Erik</au><au>Henry, Stephen G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of record linkage software for deduplicating patient identities in California's Prescription Drug Monitoring Program</atitle><jtitle>Pharmacoepidemiology and drug safety</jtitle><addtitle>Pharmacoepidemiol Drug Saf</addtitle><date>2024-01</date><risdate>2024</risdate><volume>33</volume><issue>1</issue><spage>e5699</spage><epage>n/a</epage><pages>e5699-n/a</pages><issn>1053-8569</issn><eissn>1099-1557</eissn><abstract>Background
To help prevent overdose deaths involving prescription drugs, accurate linkage of prescription drug monitoring program (PDMP) records for individual patients is essential.
Objectives
To compare the accuracy of the linkage program used by California's PDMP against various record linkage programs with respect to accuracy in deduplicating patient identities in the PDMP, with implications for identifying high‐risk opioid use and outlier behaviors.
Research Design
We evaluated California's program, Link Plus, LinkSolv, and The Link King on 557 861 PDMP identity records with addresses in two 3‐digit zip code areas for patients who filled a controlled substance prescription in 2013. Manual review was performed on a stratified sample of 720 paired records identified as matches by at least one program.
Measures
We estimated sensitivity and positive predictive value, and computed PDMP patient alerts for the patient entities identified by each program.
Results
Sensitivity was 95% for LinkSolv and The Link King, 84% for Link Plus, and 73% for California's program; positive predictive value was ≥93% for all programs. The number of patient entities prompting a PDMP alert was similar among the programs for all alerts except multiple provider episodes (obtaining prescriptions from ≥6 prescribers or ≥6 pharmacies in the last 6 months), which were 10.9%, 26.6%, and 16.9% greater using The Link King, Link Plus, and LinkSolv, respectively, compared to California's program.
Conclusions
PDMPs should assess the accuracy of record linkage algorithms and the impacts of these algorithms on patient safety alerts and develop national best practices for PDMP record linkage.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Inc</pub><pmid>37779337</pmid><doi>10.1002/pds.5699</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-1593-440X</orcidid><orcidid>https://orcid.org/0000-0002-5643-0881</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1053-8569 |
ispartof | Pharmacoepidemiology and drug safety, 2024-01, Vol.33 (1), p.e5699-n/a |
issn | 1053-8569 1099-1557 |
language | eng |
recordid | cdi_proquest_miscellaneous_2871654230 |
source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
subjects | Accuracy Algorithms California - epidemiology controlled substance Drug Prescriptions Humans Opioid-Related Disorders overdose prevention Prescription Drug Monitoring Programs Prescription drugs prescription registry record linkage Software |
title | Comparison of record linkage software for deduplicating patient identities in California's Prescription Drug Monitoring Program |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-27T20%3A08%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Comparison%20of%20record%20linkage%20software%20for%20deduplicating%20patient%20identities%20in%20California's%20Prescription%20Drug%20Monitoring%20Program&rft.jtitle=Pharmacoepidemiology%20and%20drug%20safety&rft.au=Stewart,%20Susan%20L.&rft.date=2024-01&rft.volume=33&rft.issue=1&rft.spage=e5699&rft.epage=n/a&rft.pages=e5699-n/a&rft.issn=1053-8569&rft.eissn=1099-1557&rft_id=info:doi/10.1002/pds.5699&rft_dat=%3Cproquest_cross%3E2916357454%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2916357454&rft_id=info:pmid/37779337&rfr_iscdi=true |