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Opening the black box of the group‐based trajectory modeling process to analyze medication adherence patterns: An example using real‐world statin adherence data

Purpose The rationale for choosing a final group‐based trajectory modeling (GBTM) specification and evaluations of patient adherence patterns within groups are often omitted in the GBTM medication adherence literature. We aimed to (1) reveal the complexity of GBTM and (2) assess model discrimination...

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Published in:Pharmacoepidemiology and drug safety 2020-03, Vol.29 (3), p.357-362
Main Authors: Hickson, Ryan P., Annis, Izabela E., Killeya‐Jones, Ley A., Fang, Gang
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Language:English
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creator Hickson, Ryan P.
Annis, Izabela E.
Killeya‐Jones, Ley A.
Fang, Gang
description Purpose The rationale for choosing a final group‐based trajectory modeling (GBTM) specification and evaluations of patient adherence patterns within groups are often omitted in the GBTM medication adherence literature. We aimed to (1) reveal the complexity of GBTM and (2) assess model discrimination of patient medication adherence patterns. Methods Medicare administrative claims were used to measure statin medication adherence as a continuous value in the 6 months before an acute myocardial infarction (AMI) hospitalization. Different GBTM specifications beyond default settings were constructed and compared with the Bayesian information criterion. Spaghetti plots were used to compare individual adherence patterns with group averages. Results Overall, 113,296 prevalent statin users met eligibility criteria. Four adherence groups were identified: persistently adherent, moderately adherent, progressively nonadherent, and persistently nonadherent. Spaghetti plots showed the persistently adherent and persistently nonadherent groups had relatively homogeneous adherence patterns that matched predicted trajectories well. Spaghetti plots also showed that, while adherence patterns in the progressively nonadherent group were not as homogeneous, most patients in this group appeared to be discontinuing statin therapy pre‐AMI. Conclusions Subjective decisions are necessary to identify a final trajectory model. Greater transparency and disclosure of these decisions in the medication adherence literature are needed. Individual patient adherence patterns from spaghetti plots provided additional diagnostic information about trajectory models beyond standard model‐fit assessments to determine if group‐average adherence estimates represent homogeneous patterns of medication adherence.
doi_str_mv 10.1002/pds.4917
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We aimed to (1) reveal the complexity of GBTM and (2) assess model discrimination of patient medication adherence patterns. Methods Medicare administrative claims were used to measure statin medication adherence as a continuous value in the 6 months before an acute myocardial infarction (AMI) hospitalization. Different GBTM specifications beyond default settings were constructed and compared with the Bayesian information criterion. Spaghetti plots were used to compare individual adherence patterns with group averages. Results Overall, 113,296 prevalent statin users met eligibility criteria. Four adherence groups were identified: persistently adherent, moderately adherent, progressively nonadherent, and persistently nonadherent. Spaghetti plots showed the persistently adherent and persistently nonadherent groups had relatively homogeneous adherence patterns that matched predicted trajectories well. Spaghetti plots also showed that, while adherence patterns in the progressively nonadherent group were not as homogeneous, most patients in this group appeared to be discontinuing statin therapy pre‐AMI. Conclusions Subjective decisions are necessary to identify a final trajectory model. Greater transparency and disclosure of these decisions in the medication adherence literature are needed. Individual patient adherence patterns from spaghetti plots provided additional diagnostic information about trajectory models beyond standard model‐fit assessments to determine if group‐average adherence estimates represent homogeneous patterns of medication adherence.</description><identifier>ISSN: 1053-8569</identifier><identifier>EISSN: 1099-1557</identifier><identifier>DOI: 10.1002/pds.4917</identifier><identifier>PMID: 31802581</identifier><language>eng</language><publisher>England: Wiley Subscription Services, Inc</publisher><subject>Adult ; Aged ; Bayes Theorem ; Bayesian analysis ; Female ; group‐based trajectory modeling ; health behavior ; Hospitalization ; Humans ; Hydroxymethylglutaryl-CoA Reductase Inhibitors - therapeutic use ; Male ; Mathematical models ; Medicare ; Medication adherence ; Medication Adherence - statistics &amp; numerical data ; methods ; Middle Aged ; Myocardial Infarction ; Patient compliance ; pharmacoepidemiology ; Statins ; statistical distributions ; United States</subject><ispartof>Pharmacoepidemiology and drug safety, 2020-03, Vol.29 (3), p.357-362</ispartof><rights>2019 John Wiley &amp; Sons, Ltd.</rights><rights>2020 John Wiley &amp; Sons, Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4777-d3d6160b7f7e87e8a3380c788ff1f697d769b0ee2d539dcfa065e05d8fa96ac33</citedby><cites>FETCH-LOGICAL-c4777-d3d6160b7f7e87e8a3380c788ff1f697d769b0ee2d539dcfa065e05d8fa96ac33</cites><orcidid>0000-0002-3448-589X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31802581$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hickson, Ryan P.</creatorcontrib><creatorcontrib>Annis, Izabela E.</creatorcontrib><creatorcontrib>Killeya‐Jones, Ley A.</creatorcontrib><creatorcontrib>Fang, Gang</creatorcontrib><title>Opening the black box of the group‐based trajectory modeling process to analyze medication adherence patterns: An example using real‐world statin adherence data</title><title>Pharmacoepidemiology and drug safety</title><addtitle>Pharmacoepidemiol Drug Saf</addtitle><description>Purpose The rationale for choosing a final group‐based trajectory modeling (GBTM) specification and evaluations of patient adherence patterns within groups are often omitted in the GBTM medication adherence literature. We aimed to (1) reveal the complexity of GBTM and (2) assess model discrimination of patient medication adherence patterns. Methods Medicare administrative claims were used to measure statin medication adherence as a continuous value in the 6 months before an acute myocardial infarction (AMI) hospitalization. Different GBTM specifications beyond default settings were constructed and compared with the Bayesian information criterion. Spaghetti plots were used to compare individual adherence patterns with group averages. Results Overall, 113,296 prevalent statin users met eligibility criteria. Four adherence groups were identified: persistently adherent, moderately adherent, progressively nonadherent, and persistently nonadherent. Spaghetti plots showed the persistently adherent and persistently nonadherent groups had relatively homogeneous adherence patterns that matched predicted trajectories well. Spaghetti plots also showed that, while adherence patterns in the progressively nonadherent group were not as homogeneous, most patients in this group appeared to be discontinuing statin therapy pre‐AMI. Conclusions Subjective decisions are necessary to identify a final trajectory model. Greater transparency and disclosure of these decisions in the medication adherence literature are needed. 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Spaghetti plots also showed that, while adherence patterns in the progressively nonadherent group were not as homogeneous, most patients in this group appeared to be discontinuing statin therapy pre‐AMI. Conclusions Subjective decisions are necessary to identify a final trajectory model. Greater transparency and disclosure of these decisions in the medication adherence literature are needed. Individual patient adherence patterns from spaghetti plots provided additional diagnostic information about trajectory models beyond standard model‐fit assessments to determine if group‐average adherence estimates represent homogeneous patterns of medication adherence.</abstract><cop>England</cop><pub>Wiley Subscription Services, Inc</pub><pmid>31802581</pmid><doi>10.1002/pds.4917</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0002-3448-589X</orcidid><oa>free_for_read</oa></addata></record>
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subjects Adult
Aged
Bayes Theorem
Bayesian analysis
Female
group‐based trajectory modeling
health behavior
Hospitalization
Humans
Hydroxymethylglutaryl-CoA Reductase Inhibitors - therapeutic use
Male
Mathematical models
Medicare
Medication adherence
Medication Adherence - statistics & numerical data
methods
Middle Aged
Myocardial Infarction
Patient compliance
pharmacoepidemiology
Statins
statistical distributions
United States
title Opening the black box of the group‐based trajectory modeling process to analyze medication adherence patterns: An example using real‐world statin adherence data
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