Disparities in Medicare beneficiaries' receiving medication synchronization
Copyright © 2022 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved..
BACKGROUND: Medication synchronization (med-sync) aligns patients' monthly or quarterly chronic medications to a predetermined single pickup date at a community pharmacy. The study objective was to examine med-sync enrollment disparities based on Medicare beneficiaries' predisposing, enabling, and need characteristics.
METHODS: This was a retrospective cohort study using a Medicare dataset of beneficiaries receiving medications from pharmacies that self-identified as providing med-sync. Medicare beneficiaries who were continuously enrolled in fee-for-service medical and pharmacy benefits during the study period (2014-2016) were included. Study cohorts (med-sync and non-med-sync patients) were defined, and bivariate and multivariable logistic regression analyses were performed. Andersen's Health Services Utilization Model guided our inclusion of predisposing, enabling, and need characteristics to examine for association with med-sync enrollment.
RESULTS: A total of 170,180 beneficiaries were included, of which 13,193 comprised the med-sync cohort and 156,987 comprised the non-med-sync cohort. Bivariate logistic regression analysis revealed statistically significant differences (P < 0.05) in cohorts based on age, geographic region, type of residence, number of unique chronic medications, comorbidities, outpatient visits, and inpatient hospitalizations. Beneficiaries had higher odds of being enrolled in med-sync with increasing age (adjusted odds ratio [AOR] 1.003 [95% CI 1.001-1.005]) and if they resided in the Northeast (AOR 1.094 [95% CI 1.018-1.175]), South (AOR 1.109 [95% CI 1.035-1.188]), and West (AOR 1.113 [95% CI 1.020-1.215]) than those in the Midwest. Beneficiaries residing in nonmetro areas had lower odds of enrollment (AOR 0.914 [95% CI 0.863-0.969]) than those in metro areas. Beneficiaries with previous fewer inpatient hospitalizations (AOR 0.945 [95% CI 0.914-0.977]) were more likely to be enrolled, and those with more outpatient visits (AOR 1.003 [95% CI 1.001-1.004]) were more likely to be enrolled. Those taking a higher number of oral chronic medications (AOR 1.005 [95% CI 1.002-1.008]) had greater odds of enrollment in med-sync.
CONCLUSIONS: Med-sync program expansion opportunities exist to address potential enrollment disparities based on age, geographic region, metropolitan area, and prior health utilization. Further studies are needed to develop and examine strategies among pharmacies to improve med-sync enrollment outreach to these subgroups of patients.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:63 |
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| Enthalten in: |
Journal of the American Pharmacists Association : JAPhA - 63(2023), 2 vom: 31. März, Seite 538-546.e2 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Waghmare, Prajakta H [VerfasserIn] |
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| Links: |
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| Themen: |
Journal Article |
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| Anmerkungen: |
Date Completed 04.04.2023 Date Revised 31.01.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.japh.2022.10.021 |
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| Förderinstitution / Projekttitel: |
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| 500 | |a published: Print-Electronic | ||
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| 520 | |a Copyright © 2022 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved. | ||
| 520 | |a BACKGROUND: Medication synchronization (med-sync) aligns patients' monthly or quarterly chronic medications to a predetermined single pickup date at a community pharmacy. The study objective was to examine med-sync enrollment disparities based on Medicare beneficiaries' predisposing, enabling, and need characteristics | ||
| 520 | |a METHODS: This was a retrospective cohort study using a Medicare dataset of beneficiaries receiving medications from pharmacies that self-identified as providing med-sync. Medicare beneficiaries who were continuously enrolled in fee-for-service medical and pharmacy benefits during the study period (2014-2016) were included. Study cohorts (med-sync and non-med-sync patients) were defined, and bivariate and multivariable logistic regression analyses were performed. Andersen's Health Services Utilization Model guided our inclusion of predisposing, enabling, and need characteristics to examine for association with med-sync enrollment | ||
| 520 | |a RESULTS: A total of 170,180 beneficiaries were included, of which 13,193 comprised the med-sync cohort and 156,987 comprised the non-med-sync cohort. Bivariate logistic regression analysis revealed statistically significant differences (P < 0.05) in cohorts based on age, geographic region, type of residence, number of unique chronic medications, comorbidities, outpatient visits, and inpatient hospitalizations. Beneficiaries had higher odds of being enrolled in med-sync with increasing age (adjusted odds ratio [AOR] 1.003 [95% CI 1.001-1.005]) and if they resided in the Northeast (AOR 1.094 [95% CI 1.018-1.175]), South (AOR 1.109 [95% CI 1.035-1.188]), and West (AOR 1.113 [95% CI 1.020-1.215]) than those in the Midwest. Beneficiaries residing in nonmetro areas had lower odds of enrollment (AOR 0.914 [95% CI 0.863-0.969]) than those in metro areas. Beneficiaries with previous fewer inpatient hospitalizations (AOR 0.945 [95% CI 0.914-0.977]) were more likely to be enrolled, and those with more outpatient visits (AOR 1.003 [95% CI 1.001-1.004]) were more likely to be enrolled. Those taking a higher number of oral chronic medications (AOR 1.005 [95% CI 1.002-1.008]) had greater odds of enrollment in med-sync | ||
| 520 | |a CONCLUSIONS: Med-sync program expansion opportunities exist to address potential enrollment disparities based on age, geographic region, metropolitan area, and prior health utilization. Further studies are needed to develop and examine strategies among pharmacies to improve med-sync enrollment outreach to these subgroups of patients | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 700 | 1 | |a Huang, Chien-Yu |e verfasserin |4 aut | |
| 700 | 1 | |a Jaynes, Heather A |e verfasserin |4 aut | |
| 700 | 1 | |a Green, Wendy M |e verfasserin |4 aut | |
| 700 | 1 | |a Snyder, Margie E |e verfasserin |4 aut | |
| 700 | 1 | |a Adeoye-Olatunde, Omolola A |e verfasserin |4 aut | |
| 700 | 1 | |a Coe, Antoinette B |e verfasserin |4 aut | |
| 700 | 1 | |a Farley, Joel F |e verfasserin |4 aut | |
| 700 | 1 | |a Zillich, Alan J |e verfasserin |4 aut | |
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