{"id":{"repo_id":"mississippi","oai_identifier":"oai:egrove.olemiss.edu:etd-1281"},"canonical_url":"https://search.dev.ndltd.org/etd/mississippi/oai:egrove.olemiss.edu:etd-1281","repository":{"repo_id":"mississippi","name":"University of Mississippi","base_url":"https://egrove.olemiss.edu/do/oai/"},"display":{"title":"An Evaluation of Medicaid Programs Using Medication Use-Related Quality Measures","abstract":"Objective: To assess quality of care provided to Medicaid beneficiaries using medication use-related quality indicators. Methods: This study is a retrospective analysis of 2006 & 2007 Medicaid administrative claims data from 45 states and DC. Eleven medication use-related measures (adherence/persistence and standard of care) from the AHRQ initial core set were included. A composite measure of medication use-related quality was also created. Patient case-mix adjusted measure scores were computed using hierarchical logistic regression models. States were ranked on both case-mix adjusted and unadjusted scores and categorized into top (?20%), medium (60%) and bottom (?20%) performers. Agreement in rankings and groups based on adjusted and unadjusted scores were determined using Kendall's ? b and Cohen's ?. Cross-state variations in measure scores were described using coefficient of variation and choropleth maps. Multi-level models were used to assess the amount of variation in measures explained by the state level. Results: National benchmarks on medication use-related measures for Medicaid for 2007 ranged from 31.5% for the AD chronic measure to 66.8% for the ICS measure. There was substantial variation in the 13 measures being studied with coefficient of variation ranging from 6.7 for the ICS measure to 20.5 for the MI1 measure. The best performing state Medicaid programs also had significant room for improvement across all measures. There was a lack of agreement in grouping based on crude and case-mix adjusted methods for majority of the measures (?=0.22-0.74), except for the ICS measure (?=0.91). A very small proportion of variation in the study measures (1.5 – 5.7%) was explained by the state level random effect. Conclusions: This study highlights the need for including medication use-related measures in the Medicaid adult quality measure set, considering the substantial variation in scores across states and the considerable room for improvement. States could create a composite measure of medication use-related quality using the approach used in this study if they find it burdensome to report on multiple measures. The study showcased the lack of agreement in crude and case-mix adjusted scores. Medicaid programs should consider the study findings before publicly reporting on crude scores.","abstract_html":"Objective: To assess quality of care provided to Medicaid beneficiaries using medication use-related quality indicators. Methods: This study is a retrospective analysis of 2006 & 2007 Medicaid administrative claims data from 45 states and DC. Eleven medication use-related measures (adherence/persistence and standard of care) from the AHRQ initial core set were included. A composite measure of medication use-related quality was also created. Patient case-mix adjusted measure scores were computed using hierarchical logistic regression models. States were ranked on both case-mix adjusted and unadjusted scores and categorized into top (?20%), medium (60%) and bottom (?20%) performers. Agreement in rankings and groups based on adjusted and unadjusted scores were determined using Kendall's ? b and Cohen's ?. Cross-state variations in measure scores were described using coefficient of variation and choropleth maps. Multi-level models were used to assess the amount of variation in measures explained by the state level. Results: National benchmarks on medication use-related measures for Medicaid for 2007 ranged from 31.5% for the AD chronic measure to 66.8% for the ICS measure. There was substantial variation in the 13 measures being studied with coefficient of variation ranging from 6.7 for the ICS measure to 20.5 for the MI1 measure. The best performing state Medicaid programs also had significant room for improvement across all measures. There was a lack of agreement in grouping based on crude and case-mix adjusted methods for majority of the measures (?=0.22-0.74), except for the ICS measure (?=0.91). A very small proportion of variation in the study measures (1.5 – 5.7%) was explained by the state level random effect. Conclusions: This study highlights the need for including medication use-related measures in the Medicaid adult quality measure set, considering the substantial variation in scores across states and the considerable room for improvement. States could create a composite measure of medication use-related quality using the approach used in this study if they find it burdensome to report on multiple measures. The study showcased the lack of agreement in crude and case-mix adjusted scores. Medicaid programs should consider the study findings before publicly reporting on crude scores.","abstract_has_math":false,"creators":["Thumula, Vennela"],"institution":null,"degree_name":"Ph.D. in Pharmaceutical Sciences","degree_level":"Dissertation","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Benjamin F. Banahan","Sarahmona M. Przybyla","Yi Yang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-01-01T08:00:00Z","date_published":"2012-01-01T08:00:00Z","updated_at":"2026-07-24T03:05:22Z","subjects":["Case-Mix Adjustment","Interstate Variation In Healthcare Quality","Medicaid Adult Quality Measurement","Medicaid Quality","Medication Use-Related Quality Measures","Multilevel Modeling","Pharmacy and Pharmaceutical Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://egrove.olemiss.edu/etd/282","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Benjamin F. Banahan","Sarahmona M. Przybyla","Yi Yang"]},{"key":"dc:creator","label":"Author","values":["Thumula, Vennela"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-01-01T08:00:00Z"]},{"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":["Case-Mix Adjustment","Interstate Variation In Healthcare Quality","Medicaid Adult Quality Measurement","Medicaid Quality","Medication Use-Related Quality Measures","Multilevel Modeling","Pharmacy and Pharmaceutical Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://egrove.olemiss.edu/etd/282"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Objective: To assess quality of care provided to Medicaid beneficiaries using medication use-related quality indicators. Methods: This study is a retrospective analysis of 2006 & 2007 Medicaid administrative claims data from 45 states and DC. Eleven medication use-related measures (adherence/persistence and standard of care) from the AHRQ initial core set were included. A composite measure of medication use-related quality was also created. Patient case-mix adjusted measure scores were computed using hierarchical logistic regression models. States were ranked on both case-mix adjusted and unadjusted scores and categorized into top (?20%), medium (60%) and bottom (?20%) performers. Agreement in rankings and groups based on adjusted and unadjusted scores were determined using Kendall's ? b and Cohen's ?. Cross-state variations in measure scores were described using coefficient of variation and choropleth maps. Multi-level models were used to assess the amount of variation in measures explained by the state level. Results: National benchmarks on medication use-related measures for Medicaid for 2007 ranged from 31.5% for the AD chronic measure to 66.8% for the ICS measure. There was substantial variation in the 13 measures being studied with coefficient of variation ranging from 6.7 for the ICS measure to 20.5 for the MI1 measure. The best performing state Medicaid programs also had significant room for improvement across all measures. There was a lack of agreement in grouping based on crude and case-mix adjusted methods for majority of the measures (?=0.22-0.74), except for the ICS measure (?=0.91). A very small proportion of variation in the study measures (1.5 – 5.7%) was explained by the state level random effect. Conclusions: This study highlights the need for including medication use-related measures in the Medicaid adult quality measure set, considering the substantial variation in scores across states and the considerable room for improvement. States could create a composite measure of medication use-related quality using the approach used in this study if they find it burdensome to report on multiple measures. The study showcased the lack of agreement in crude and case-mix adjusted scores. Medicaid programs should consider the study findings before publicly reporting on crude scores."]},{"key":"dc:title","label":"Title","values":["An Evaluation of Medicaid Programs Using Medication Use-Related Quality Measures"]}]}],"canonical_facts":{"dc:contributor":["Benjamin F. Banahan","Sarahmona M. Przybyla","Yi Yang"],"dc:creator":["Thumula, Vennela"],"dc:date.available":["2019-01-01T08:00:00Z"],"dc:description.abstract":["Objective: To assess quality of care provided to Medicaid beneficiaries using medication use-related quality indicators. Methods: This study is a retrospective analysis of 2006 & 2007 Medicaid administrative claims data from 45 states and DC. Eleven medication use-related measures (adherence/persistence and standard of care) from the AHRQ initial core set were included. A composite measure of medication use-related quality was also created. Patient case-mix adjusted measure scores were computed using hierarchical logistic regression models. States were ranked on both case-mix adjusted and unadjusted scores and categorized into top (?20%), medium (60%) and bottom (?20%) performers. Agreement in rankings and groups based on adjusted and unadjusted scores were determined using Kendall's ? b and Cohen's ?. Cross-state variations in measure scores were described using coefficient of variation and choropleth maps. Multi-level models were used to assess the amount of variation in measures explained by the state level. Results: National benchmarks on medication use-related measures for Medicaid for 2007 ranged from 31.5% for the AD chronic measure to 66.8% for the ICS measure. There was substantial variation in the 13 measures being studied with coefficient of variation ranging from 6.7 for the ICS measure to 20.5 for the MI1 measure. The best performing state Medicaid programs also had significant room for improvement across all measures. There was a lack of agreement in grouping based on crude and case-mix adjusted methods for majority of the measures (?=0.22-0.74), except for the ICS measure (?=0.91). A very small proportion of variation in the study measures (1.5 – 5.7%) was explained by the state level random effect. Conclusions: This study highlights the need for including medication use-related measures in the Medicaid adult quality measure set, considering the substantial variation in scores across states and the considerable room for improvement. States could create a composite measure of medication use-related quality using the approach used in this study if they find it burdensome to report on multiple measures. The study showcased the lack of agreement in crude and case-mix adjusted scores. Medicaid programs should consider the study findings before publicly reporting on crude scores."],"dc:identifier":["https://egrove.olemiss.edu/etd/282"],"dc:subject":["Case-Mix Adjustment","Interstate Variation In Healthcare Quality","Medicaid Adult Quality Measurement","Medicaid Quality","Medication Use-Related Quality Measures","Multilevel Modeling","Pharmacy and Pharmaceutical Sciences"],"dc:title":["An Evaluation of Medicaid Programs Using Medication Use-Related Quality Measures"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D. in Pharmaceutical Sciences"]},"updated_at":"2026-07-24T03:05:22Z"}