Medication Adherence Patterns after Hospitalization for Coronary Heart Disease. A Population-Based Study Using Electronic Records and Group-Based Trajectory Models
To identify adherence patterns over time and their predictors for evidence-based medications used after hospitalization for coronary heart disease (CHD). We built a population-based retrospective cohort of all patients discharged after hospitalization for CHD from public hospitals in the Valencia re...
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| Veröffentlicht in: | PloS one 2016-08, Vol.11 (8), p.e0161381-e0161381 |
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| description | To identify adherence patterns over time and their predictors for evidence-based medications used after hospitalization for coronary heart disease (CHD).
We built a population-based retrospective cohort of all patients discharged after hospitalization for CHD from public hospitals in the Valencia region (Spain) during 2008 (n = 7462). From this initial cohort, we created 4 subcohorts with at least one prescription (filled or not) from each therapeutic group (antiplatelet, beta-blockers, ACEI/ARB, statins) within the first 3 months after discharge. Monthly adherence was defined as having ≥24 days covered out of 30, leading to a repeated binary outcome measure. We assessed the membership to trajectory groups of adherence using group-based trajectory models. We also analyzed predictors of the different adherence patterns using multinomial logistic regression.
We identified a maximum of 5 different adherence patterns: 1) Nearly-always adherent patients; 2) An early gap in adherence with a later recovery; 3) Brief gaps in medication use or occasional users; 4) A slow decline in adherence; and 5) A fast decline. These patterns represented variable proportions of patients, the descending trajectories being more frequent for the beta-blocker and ACEI/ARB cohorts (16% and 17%, respectively) than the antiplatelet and statin cohorts (10% and 8%, respectively). Predictors of poor or intermediate adherence patterns were having a main diagnosis of unstable angina or other forms of CHD vs. AMI in the index hospitalization, being born outside Spain, requiring copayment or being older.
Distinct adherence patterns over time and their predictors were identified. This may be a useful approach for targeting improvement interventions in patients with poor adherence patterns. |
| doi_str_mv | 10.1371/journal.pone.0161381 |
| format | Article |
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We built a population-based retrospective cohort of all patients discharged after hospitalization for CHD from public hospitals in the Valencia region (Spain) during 2008 (n = 7462). From this initial cohort, we created 4 subcohorts with at least one prescription (filled or not) from each therapeutic group (antiplatelet, beta-blockers, ACEI/ARB, statins) within the first 3 months after discharge. Monthly adherence was defined as having ≥24 days covered out of 30, leading to a repeated binary outcome measure. We assessed the membership to trajectory groups of adherence using group-based trajectory models. We also analyzed predictors of the different adherence patterns using multinomial logistic regression.
We identified a maximum of 5 different adherence patterns: 1) Nearly-always adherent patients; 2) An early gap in adherence with a later recovery; 3) Brief gaps in medication use or occasional users; 4) A slow decline in adherence; and 5) A fast decline. These patterns represented variable proportions of patients, the descending trajectories being more frequent for the beta-blocker and ACEI/ARB cohorts (16% and 17%, respectively) than the antiplatelet and statin cohorts (10% and 8%, respectively). Predictors of poor or intermediate adherence patterns were having a main diagnosis of unstable angina or other forms of CHD vs. AMI in the index hospitalization, being born outside Spain, requiring copayment or being older.
Distinct adherence patterns over time and their predictors were identified. This may be a useful approach for targeting improvement interventions in patients with poor adherence patterns.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0161381</identifier><identifier>PMID: 27551748</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adhesion ; Adrenergic beta-Antagonists - therapeutic use ; Adult ; Aged ; Aged, 80 and over ; Analysis ; Angina ; Angina Pectoris - drug therapy ; Angina Pectoris - epidemiology ; Angina Pectoris - pathology ; Cardiovascular disease ; Cardiovascular diseases ; Care and treatment ; Clinical outcomes ; Computerized physician order entry ; Coronary artery disease ; Coronary Disease - drug therapy ; Coronary Disease - epidemiology ; Coronary Disease - pathology ; Coronary heart disease ; Diagnosis ; Drugs ; Female ; Health care ; Health services ; Heart ; Heart diseases ; Hospitalization ; Hospitals ; Humans ; Hydroxymethylglutaryl-CoA Reductase Inhibitors - therapeutic use ; Logistic Models ; Male ; Mathematical models ; Medical records ; Medical research ; Medication Adherence ; Medicine and Health Sciences ; Middle Aged ; Patient compliance ; Patient Discharge ; Patient outcomes ; Patients ; People and Places ; Pharmacy ; Physician-Patient Relations ; Platelet Aggregation Inhibitors - therapeutic use ; Population studies ; Population-based studies ; Prescriptions ; Public health ; Pulmonary Disease, Chronic Obstructive - drug therapy ; Pulmonary Disease, Chronic Obstructive - epidemiology ; Pulmonary Disease, Chronic Obstructive - pathology ; Regression analysis ; Retrospective Studies ; Spain ; Statins ; Studies ; Trajectory analysis</subject><ispartof>PloS one, 2016-08, Vol.11 (8), p.e0161381-e0161381</ispartof><rights>COPYRIGHT 2016 Public Library of Science</rights><rights>2016 Librero et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2016 Librero et al 2016 Librero et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c776t-be0965e6d742775a042ab5766227e06ab6509dac30bc7eff90faee2d558bffa43</citedby><cites>FETCH-LOGICAL-c776t-be0965e6d742775a042ab5766227e06ab6509dac30bc7eff90faee2d558bffa43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4995009/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4995009/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27551748$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Ahrens, Ingo</contributor><creatorcontrib>Librero, Julián</creatorcontrib><creatorcontrib>Sanfélix-Gimeno, Gabriel</creatorcontrib><creatorcontrib>Peiró, Salvador</creatorcontrib><title>Medication Adherence Patterns after Hospitalization for Coronary Heart Disease. A Population-Based Study Using Electronic Records and Group-Based Trajectory Models</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>To identify adherence patterns over time and their predictors for evidence-based medications used after hospitalization for coronary heart disease (CHD).
We built a population-based retrospective cohort of all patients discharged after hospitalization for CHD from public hospitals in the Valencia region (Spain) during 2008 (n = 7462). From this initial cohort, we created 4 subcohorts with at least one prescription (filled or not) from each therapeutic group (antiplatelet, beta-blockers, ACEI/ARB, statins) within the first 3 months after discharge. Monthly adherence was defined as having ≥24 days covered out of 30, leading to a repeated binary outcome measure. We assessed the membership to trajectory groups of adherence using group-based trajectory models. We also analyzed predictors of the different adherence patterns using multinomial logistic regression.
We identified a maximum of 5 different adherence patterns: 1) Nearly-always adherent patients; 2) An early gap in adherence with a later recovery; 3) Brief gaps in medication use or occasional users; 4) A slow decline in adherence; and 5) A fast decline. These patterns represented variable proportions of patients, the descending trajectories being more frequent for the beta-blocker and ACEI/ARB cohorts (16% and 17%, respectively) than the antiplatelet and statin cohorts (10% and 8%, respectively). Predictors of poor or intermediate adherence patterns were having a main diagnosis of unstable angina or other forms of CHD vs. AMI in the index hospitalization, being born outside Spain, requiring copayment or being older.
Distinct adherence patterns over time and their predictors were identified. 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therapeutic use</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Mathematical models</subject><subject>Medical records</subject><subject>Medical research</subject><subject>Medication Adherence</subject><subject>Medicine and Health Sciences</subject><subject>Middle Aged</subject><subject>Patient compliance</subject><subject>Patient Discharge</subject><subject>Patient outcomes</subject><subject>Patients</subject><subject>People and Places</subject><subject>Pharmacy</subject><subject>Physician-Patient Relations</subject><subject>Platelet Aggregation Inhibitors - therapeutic use</subject><subject>Population studies</subject><subject>Population-based studies</subject><subject>Prescriptions</subject><subject>Public health</subject><subject>Pulmonary Disease, Chronic Obstructive - drug therapy</subject><subject>Pulmonary Disease, Chronic Obstructive - epidemiology</subject><subject>Pulmonary Disease, Chronic Obstructive - pathology</subject><subject>Regression analysis</subject><subject>Retrospective Studies</subject><subject>Spain</subject><subject>Statins</subject><subject>Studies</subject><subject>Trajectory analysis</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNk99u0zAUxiMEYmPwBggsISG4aLHj2EluJpUxtkmbNu0Pt5ZjH7eu0rjYDmK8Di-K22bTinYx5cLRye98n_PZJ8veEjwmtCRf5q73nWzHS9fBGBNOaEWeZbukpvmI55g-f_C-k70KYY4xoxXnL7OdvGSMlEW1m_09A22VjNZ1aKJn4KFTgC5kjOC7gKRJKzp2YWmjbO2fDWicRwfOu076W3QM0kf0zQaQAcZogi7csm_X4OhrKml0FXt9i26C7abosAUVU6dV6BKU8zp5dBodedcvB_zay3mCXNI-cxra8Dp7YWQb4M2w7mU33w-vD45Hp-dHJweT05EqSx5HDeCaM-C6LPKyZBIXuWxYyXmel4C5bDjDtZaK4kaVYEyNjQTINWNVY4ws6F72fqO7bF0QQ75BkIpQnpO64ok42RDayblYertICQgnrVgXnJ-KFIZVLYhkRwtMgZkmL7CmsmpoDpUhBWUK1yZp7Q9ufbMAraCLXrZbottfOjsTU_dLFHXNMK6TwKdBwLufPYQoFjYoaFvZgevX-66TW16zp6BFQquqTOiH_9DHgxioqUz_ajvj0hbVSlRMCp7EcM5WtuNHqPRoWFiV7q2xqb7V8HmrITERfsep7EMQJ1eXT2fPf2yzHx-wM5BtnAXX9qtLGrbBYgMq70LwYO7Pg2CxGru7NMRq7MQwdqnt3cOzvG-6mzP6D-7sKYo</recordid><startdate>20160823</startdate><enddate>20160823</enddate><creator>Librero, Julián</creator><creator>Sanfélix-Gimeno, Gabriel</creator><creator>Peiró, Salvador</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20160823</creationdate><title>Medication Adherence Patterns after Hospitalization for Coronary Heart Disease. A Population-Based Study Using Electronic Records and Group-Based Trajectory Models</title><author>Librero, Julián ; Sanfélix-Gimeno, Gabriel ; Peiró, Salvador</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c776t-be0965e6d742775a042ab5766227e06ab6509dac30bc7eff90faee2d558bffa43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adhesion</topic><topic>Adrenergic beta-Antagonists - therapeutic use</topic><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Analysis</topic><topic>Angina</topic><topic>Angina Pectoris - drug therapy</topic><topic>Angina Pectoris - epidemiology</topic><topic>Angina Pectoris - pathology</topic><topic>Cardiovascular disease</topic><topic>Cardiovascular diseases</topic><topic>Care and treatment</topic><topic>Clinical outcomes</topic><topic>Computerized physician order entry</topic><topic>Coronary artery disease</topic><topic>Coronary Disease - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Librero, Julián</au><au>Sanfélix-Gimeno, Gabriel</au><au>Peiró, Salvador</au><au>Ahrens, Ingo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Medication Adherence Patterns after Hospitalization for Coronary Heart Disease. A Population-Based Study Using Electronic Records and Group-Based Trajectory Models</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2016-08-23</date><risdate>2016</risdate><volume>11</volume><issue>8</issue><spage>e0161381</spage><epage>e0161381</epage><pages>e0161381-e0161381</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>To identify adherence patterns over time and their predictors for evidence-based medications used after hospitalization for coronary heart disease (CHD).
We built a population-based retrospective cohort of all patients discharged after hospitalization for CHD from public hospitals in the Valencia region (Spain) during 2008 (n = 7462). From this initial cohort, we created 4 subcohorts with at least one prescription (filled or not) from each therapeutic group (antiplatelet, beta-blockers, ACEI/ARB, statins) within the first 3 months after discharge. Monthly adherence was defined as having ≥24 days covered out of 30, leading to a repeated binary outcome measure. We assessed the membership to trajectory groups of adherence using group-based trajectory models. We also analyzed predictors of the different adherence patterns using multinomial logistic regression.
We identified a maximum of 5 different adherence patterns: 1) Nearly-always adherent patients; 2) An early gap in adherence with a later recovery; 3) Brief gaps in medication use or occasional users; 4) A slow decline in adherence; and 5) A fast decline. These patterns represented variable proportions of patients, the descending trajectories being more frequent for the beta-blocker and ACEI/ARB cohorts (16% and 17%, respectively) than the antiplatelet and statin cohorts (10% and 8%, respectively). Predictors of poor or intermediate adherence patterns were having a main diagnosis of unstable angina or other forms of CHD vs. AMI in the index hospitalization, being born outside Spain, requiring copayment or being older.
Distinct adherence patterns over time and their predictors were identified. This may be a useful approach for targeting improvement interventions in patients with poor adherence patterns.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>27551748</pmid><doi>10.1371/journal.pone.0161381</doi><tpages>e0161381</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | PloS one, 2016-08, Vol.11 (8), p.e0161381-e0161381 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1813621986 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Adhesion Adrenergic beta-Antagonists - therapeutic use Adult Aged Aged, 80 and over Analysis Angina Angina Pectoris - drug therapy Angina Pectoris - epidemiology Angina Pectoris - pathology Cardiovascular disease Cardiovascular diseases Care and treatment Clinical outcomes Computerized physician order entry Coronary artery disease Coronary Disease - drug therapy Coronary Disease - epidemiology Coronary Disease - pathology Coronary heart disease Diagnosis Drugs Female Health care Health services Heart Heart diseases Hospitalization Hospitals Humans Hydroxymethylglutaryl-CoA Reductase Inhibitors - therapeutic use Logistic Models Male Mathematical models Medical records Medical research Medication Adherence Medicine and Health Sciences Middle Aged Patient compliance Patient Discharge Patient outcomes Patients People and Places Pharmacy Physician-Patient Relations Platelet Aggregation Inhibitors - therapeutic use Population studies Population-based studies Prescriptions Public health Pulmonary Disease, Chronic Obstructive - drug therapy Pulmonary Disease, Chronic Obstructive - epidemiology Pulmonary Disease, Chronic Obstructive - pathology Regression analysis Retrospective Studies Spain Statins Studies Trajectory analysis |
| title | Medication Adherence Patterns after Hospitalization for Coronary Heart Disease. A Population-Based Study Using Electronic Records and Group-Based Trajectory Models |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-31T10%3A25%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Medication%20Adherence%20Patterns%20after%20Hospitalization%20for%20Coronary%20Heart%20Disease.%20A%20Population-Based%20Study%20Using%20Electronic%20Records%20and%20Group-Based%20Trajectory%20Models&rft.jtitle=PloS%20one&rft.au=Librero,%20Juli%C3%A1n&rft.date=2016-08-23&rft.volume=11&rft.issue=8&rft.spage=e0161381&rft.epage=e0161381&rft.pages=e0161381-e0161381&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0161381&rft_dat=%3Cgale_plos_%3EA461410255%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1813621986&rft_id=info:pmid/27551748&rft_galeid=A461410255&rft_doaj_id=oai_doaj_org_article_ab63403e5fb240d3a8b32e8f1435c09f&rfr_iscdi=true |