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Prescription fill rates for acute and chronic medications in claims-EMR linked data
Nonadherence to prescribed medications poses a significant public health problem. Prescription data in electronic medical records (EMRs) linked with pharmacy claims data provides an opportunity to examine the prescription fill rates and factors associated with it. Using a claims-EMR linked data, pat...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6221733/ https://www.ncbi.nlm.nih.gov/pubmed/30383700 http://dx.doi.org/10.1097/MD.0000000000013110 |
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author | Park, Yoonyoung Yang, Hyuna Das, Amar K. Yuen-Reed, Gigi |
author_facet | Park, Yoonyoung Yang, Hyuna Das, Amar K. Yuen-Reed, Gigi |
author_sort | Park, Yoonyoung |
collection | PubMed |
description | Nonadherence to prescribed medications poses a significant public health problem. Prescription data in electronic medical records (EMRs) linked with pharmacy claims data provides an opportunity to examine the prescription fill rates and factors associated with it. Using a claims-EMR linked data, patients who had a prescription for either an antibiotic, antihypertensive, or antidiabetic in EMR were identified (index prescription). Prescription fill was defined as a pharmacy claim found within the 90 days following the EMR prescription. For each medication group, patient characteristics and fill rates were examined using descriptive statistics. Multivariate logistic regression was used to evaluate the association between fill rates and factors such as age, race, brand vs generic, and prior treatment during 365 days before the index date. Among 77,996 patients with index antibiotic prescription, 78,462 with index antihypertensive prescription, and 24,013 with index antidiabetic prescription, the prescription fill rate was 73%, 74%, and 76%, respectively. Overall, African American race was negatively associated with fill rates (odds ratio [OR] 0.8 for all 3 groups). Prior treatment history was positively associated with antihypertensives (OR 5.6, 95% confidence interval [CI] 5.4–5.7) or antidiabetics (OR 4.1, CI 3.8–4.4) but negatively with antibiotics (OR 0.6, CI 0.6–0.6). Older age was an additional factor that was negatively associated with first time fill rate among patients without prior treatment. Significant proportions of patients, especially patients with no prior treatment history, did not fill prescriptions for antibiotics, antihypertensives, or antidiabetics. The association between patient factors and medication fill rates varied across different medication groups. |
format | Online Article Text |
id | pubmed-6221733 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-62217332018-12-04 Prescription fill rates for acute and chronic medications in claims-EMR linked data Park, Yoonyoung Yang, Hyuna Das, Amar K. Yuen-Reed, Gigi Medicine (Baltimore) Research Article Nonadherence to prescribed medications poses a significant public health problem. Prescription data in electronic medical records (EMRs) linked with pharmacy claims data provides an opportunity to examine the prescription fill rates and factors associated with it. Using a claims-EMR linked data, patients who had a prescription for either an antibiotic, antihypertensive, or antidiabetic in EMR were identified (index prescription). Prescription fill was defined as a pharmacy claim found within the 90 days following the EMR prescription. For each medication group, patient characteristics and fill rates were examined using descriptive statistics. Multivariate logistic regression was used to evaluate the association between fill rates and factors such as age, race, brand vs generic, and prior treatment during 365 days before the index date. Among 77,996 patients with index antibiotic prescription, 78,462 with index antihypertensive prescription, and 24,013 with index antidiabetic prescription, the prescription fill rate was 73%, 74%, and 76%, respectively. Overall, African American race was negatively associated with fill rates (odds ratio [OR] 0.8 for all 3 groups). Prior treatment history was positively associated with antihypertensives (OR 5.6, 95% confidence interval [CI] 5.4–5.7) or antidiabetics (OR 4.1, CI 3.8–4.4) but negatively with antibiotics (OR 0.6, CI 0.6–0.6). Older age was an additional factor that was negatively associated with first time fill rate among patients without prior treatment. Significant proportions of patients, especially patients with no prior treatment history, did not fill prescriptions for antibiotics, antihypertensives, or antidiabetics. The association between patient factors and medication fill rates varied across different medication groups. Wolters Kluwer Health 2018-11-02 /pmc/articles/PMC6221733/ /pubmed/30383700 http://dx.doi.org/10.1097/MD.0000000000013110 Text en Copyright © 2018 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0 |
spellingShingle | Research Article Park, Yoonyoung Yang, Hyuna Das, Amar K. Yuen-Reed, Gigi Prescription fill rates for acute and chronic medications in claims-EMR linked data |
title | Prescription fill rates for acute and chronic medications in claims-EMR linked data |
title_full | Prescription fill rates for acute and chronic medications in claims-EMR linked data |
title_fullStr | Prescription fill rates for acute and chronic medications in claims-EMR linked data |
title_full_unstemmed | Prescription fill rates for acute and chronic medications in claims-EMR linked data |
title_short | Prescription fill rates for acute and chronic medications in claims-EMR linked data |
title_sort | prescription fill rates for acute and chronic medications in claims-emr linked data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6221733/ https://www.ncbi.nlm.nih.gov/pubmed/30383700 http://dx.doi.org/10.1097/MD.0000000000013110 |
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