{"id":{"repo_id":"mississippi","oai_identifier":"oai:egrove.olemiss.edu:etd-2101"},"canonical_url":"https://search.dev.ndltd.org/etd/mississippi/oai:egrove.olemiss.edu:etd-2101","repository":{"repo_id":"mississippi","name":"University of Mississippi","base_url":"https://egrove.olemiss.edu/do/oai/"},"display":{"title":"Concurrent Adherence To Multiple Chronic Disease Medications: Examining The Behavior And Issues Concerning Its Measurement","abstract":"Objectives the objectives were to 1) examine adherence to multiple medications prescribed for a chronic disease (intra-disease multiple medication adherence) and that of multiple chronic diseases (inter-disease multiple medication adherence); 2) determine appropriate measurement paradigm from different intra-disease multiple medication adherence measurement approaches; 3) identify optimal cut-point for a dichotomized composite measure. Methods a retrospective study design was used. The subjects came from the marketscanâ® commercial claims and encounters data 2002-2003 and filled both sulfonylurea (su) and thiazolidinedione (tzd). Adherence was measured by proportion of days covered (pdc) over each period of 30 or 90 days and cumulatively. Random components from multivariate multilevel models were analyzed to examine multiple medication adherence relationships, including associations of evolutions of adherence. Survival analysis was performed on any-cause or diabetes-related emergency services (er) utilization. Concordance statistics were computed to compare different measurement approaches. Results intra-disease multiple medication analysis demonstrated strong and significant (p<0.05) relationships between overall adherence estimates for su and tzd and changes in adherence estimates over time. Patients who were receiving lipid or hypertension medications, or both in addition to su and tzd shostrong and significant (p<0.05) relationships between overall adherence to cross-disease medications or cross-disease adherence slope estimates. However, such results were not observed in diabetic subjects who were prescribed nitrates for angina. Each of six composite measures of intra-disease multiple medication adherence significantly predicted hazard (hazard ratio <1.0) of all-cause or any diabetes-related er utilization. Although each concordance statistic was significant (p<0.05), there were no differences among concordance statistics produced by these measurement approaches. The average and all approach shosome superiority. The optimality of cut-point for categorizing adherence based on a composite measure of intra-disease multiple medication adherence ranged from 75-85%. Conclusion the study population demonstrated good but not optimal levels of adherence to multiple chronic disease medications. Factors that affect adherence to individual medications appear to be related and should be targeted for intervention. Efficacy of a composite measure of intra-disease multiple medications may depend on intervention goals. Further research needs to identify a composite measurement approach that demonstrates superiority in predictive and discriminatory power consistently.","abstract_html":"Objectives the objectives were to 1) examine adherence to multiple medications prescribed for a chronic disease (intra-disease multiple medication adherence) and that of multiple chronic diseases (inter-disease multiple medication adherence); 2) determine appropriate measurement paradigm from different intra-disease multiple medication adherence measurement approaches; 3) identify optimal cut-point for a dichotomized composite measure. Methods a retrospective study design was used. The subjects came from the marketscanâ® commercial claims and encounters data 2002-2003 and filled both sulfonylurea (su) and thiazolidinedione (tzd). Adherence was measured by proportion of days covered (pdc) over each period of 30 or 90 days and cumulatively. Random components from multivariate multilevel models were analyzed to examine multiple medication adherence relationships, including associations of evolutions of adherence. Survival analysis was performed on any-cause or diabetes-related emergency services (er) utilization. Concordance statistics were computed to compare different measurement approaches. Results intra-disease multiple medication analysis demonstrated strong and significant (p&lt;0.05) relationships between overall adherence estimates for su and tzd and changes in adherence estimates over time. Patients who were receiving lipid or hypertension medications, or both in addition to su and tzd shostrong and significant (p&lt;0.05) relationships between overall adherence to cross-disease medications or cross-disease adherence slope estimates. However, such results were not observed in diabetic subjects who were prescribed nitrates for angina. Each of six composite measures of intra-disease multiple medication adherence significantly predicted hazard (hazard ratio &lt;1.0) of all-cause or any diabetes-related er utilization. Although each concordance statistic was significant (p&lt;0.05), there were no differences among concordance statistics produced by these measurement approaches. The average and all approach shosome superiority. The optimality of cut-point for categorizing adherence based on a composite measure of intra-disease multiple medication adherence ranged from 75-85%. Conclusion the study population demonstrated good but not optimal levels of adherence to multiple chronic disease medications. Factors that affect adherence to individual medications appear to be related and should be targeted for intervention. Efficacy of a composite measure of intra-disease multiple medications may depend on intervention goals. Further research needs to identify a composite measurement approach that demonstrates superiority in predictive and discriminatory power consistently.","abstract_has_math":false,"creators":["Basak, Ram Sankar"],"institution":null,"degree_name":"Ph.D. in Pharmaceutical Sciences","degree_level":"Dissertation","degree_discipline":"Pharmacy Administration","degree_department":null,"school":null,"contributors":["David J. McCaffrey","Donna West-Strum","Sarahmona Przybyla"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-01-01T08:00:00Z","date_published":"2013-01-01T08:00:00Z","updated_at":"2026-07-24T03:06:21Z","subjects":["Association Of The Evolutions","Medication Adherence","Multiple Chronic Medications","Pdc Measures","Proportion Of Days Covered","Survival Analysis","Pharmacy and Pharmaceutical Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://egrove.olemiss.edu/etd/1102","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["David J. McCaffrey","Donna West-Strum","Sarahmona Przybyla"]},{"key":"dc:creator","label":"Author","values":["Basak, Ram Sankar"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-06-20T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Pharmacy Administration"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D. in Pharmaceutical Sciences"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Association Of The Evolutions","Medication Adherence","Multiple Chronic Medications","Pdc Measures","Proportion Of Days Covered","Survival Analysis","Pharmacy and Pharmaceutical Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://egrove.olemiss.edu/etd/1102"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Objectives the objectives were to 1) examine adherence to multiple medications prescribed for a chronic disease (intra-disease multiple medication adherence) and that of multiple chronic diseases (inter-disease multiple medication adherence); 2) determine appropriate measurement paradigm from different intra-disease multiple medication adherence measurement approaches; 3) identify optimal cut-point for a dichotomized composite measure. Methods a retrospective study design was used. The subjects came from the marketscanâ® commercial claims and encounters data 2002-2003 and filled both sulfonylurea (su) and thiazolidinedione (tzd). Adherence was measured by proportion of days covered (pdc) over each period of 30 or 90 days and cumulatively. Random components from multivariate multilevel models were analyzed to examine multiple medication adherence relationships, including associations of evolutions of adherence. Survival analysis was performed on any-cause or diabetes-related emergency services (er) utilization. Concordance statistics were computed to compare different measurement approaches. Results intra-disease multiple medication analysis demonstrated strong and significant (p<0.05) relationships between overall adherence estimates for su and tzd and changes in adherence estimates over time. Patients who were receiving lipid or hypertension medications, or both in addition to su and tzd shostrong and significant (p<0.05) relationships between overall adherence to cross-disease medications or cross-disease adherence slope estimates. However, such results were not observed in diabetic subjects who were prescribed nitrates for angina. Each of six composite measures of intra-disease multiple medication adherence significantly predicted hazard (hazard ratio <1.0) of all-cause or any diabetes-related er utilization. Although each concordance statistic was significant (p<0.05), there were no differences among concordance statistics produced by these measurement approaches. The average and all approach shosome superiority. The optimality of cut-point for categorizing adherence based on a composite measure of intra-disease multiple medication adherence ranged from 75-85%. Conclusion the study population demonstrated good but not optimal levels of adherence to multiple chronic disease medications. Factors that affect adherence to individual medications appear to be related and should be targeted for intervention. Efficacy of a composite measure of intra-disease multiple medications may depend on intervention goals. Further research needs to identify a composite measurement approach that demonstrates superiority in predictive and discriminatory power consistently."]},{"key":"dc:title","label":"Title","values":["Concurrent Adherence To Multiple Chronic Disease Medications: Examining The Behavior And Issues Concerning Its Measurement"]}]}],"canonical_facts":{"dc:contributor":["David J. McCaffrey","Donna West-Strum","Sarahmona Przybyla"],"dc:creator":["Basak, Ram Sankar"],"dc:date.available":["2019-06-20T07:00:00Z"],"dc:description.abstract":["Objectives the objectives were to 1) examine adherence to multiple medications prescribed for a chronic disease (intra-disease multiple medication adherence) and that of multiple chronic diseases (inter-disease multiple medication adherence); 2) determine appropriate measurement paradigm from different intra-disease multiple medication adherence measurement approaches; 3) identify optimal cut-point for a dichotomized composite measure. Methods a retrospective study design was used. The subjects came from the marketscanâ® commercial claims and encounters data 2002-2003 and filled both sulfonylurea (su) and thiazolidinedione (tzd). Adherence was measured by proportion of days covered (pdc) over each period of 30 or 90 days and cumulatively. Random components from multivariate multilevel models were analyzed to examine multiple medication adherence relationships, including associations of evolutions of adherence. Survival analysis was performed on any-cause or diabetes-related emergency services (er) utilization. Concordance statistics were computed to compare different measurement approaches. Results intra-disease multiple medication analysis demonstrated strong and significant (p<0.05) relationships between overall adherence estimates for su and tzd and changes in adherence estimates over time. Patients who were receiving lipid or hypertension medications, or both in addition to su and tzd shostrong and significant (p<0.05) relationships between overall adherence to cross-disease medications or cross-disease adherence slope estimates. However, such results were not observed in diabetic subjects who were prescribed nitrates for angina. Each of six composite measures of intra-disease multiple medication adherence significantly predicted hazard (hazard ratio <1.0) of all-cause or any diabetes-related er utilization. Although each concordance statistic was significant (p<0.05), there were no differences among concordance statistics produced by these measurement approaches. The average and all approach shosome superiority. The optimality of cut-point for categorizing adherence based on a composite measure of intra-disease multiple medication adherence ranged from 75-85%. Conclusion the study population demonstrated good but not optimal levels of adherence to multiple chronic disease medications. Factors that affect adherence to individual medications appear to be related and should be targeted for intervention. Efficacy of a composite measure of intra-disease multiple medications may depend on intervention goals. Further research needs to identify a composite measurement approach that demonstrates superiority in predictive and discriminatory power consistently."],"dc:identifier":["https://egrove.olemiss.edu/etd/1102"],"dc:subject":["Association Of The Evolutions","Medication Adherence","Multiple Chronic Medications","Pdc Measures","Proportion Of Days Covered","Survival Analysis","Pharmacy and Pharmaceutical Sciences"],"dc:title":["Concurrent Adherence To Multiple Chronic Disease Medications: Examining The Behavior And Issues Concerning Its Measurement"],"thesis:degree_discipline":["Pharmacy Administration"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D. in Pharmaceutical Sciences"]},"updated_at":"2026-07-24T03:06:21Z"}