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Using electronic admission data to monitor temporal trends in local medication use: Experience from an Australian tertiary teaching hospital
Background and aims: Medication usage varies according to prescribing behavior, professional recommendations, and the introduction of new drugs. Local surveillance of medication usage may be useful for understanding and comparing prescribing practices by healthcare providers, particularly in countri...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9614045/ https://www.ncbi.nlm.nih.gov/pubmed/36313311 http://dx.doi.org/10.3389/fphar.2022.888677 |
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author | Woodman, Richard J. Horwood, Chris Kunnel, Aline Hakendorf, Paul Mangoni, Arduino A. |
author_facet | Woodman, Richard J. Horwood, Chris Kunnel, Aline Hakendorf, Paul Mangoni, Arduino A. |
author_sort | Woodman, Richard J. |
collection | PubMed |
description | Background and aims: Medication usage varies according to prescribing behavior, professional recommendations, and the introduction of new drugs. Local surveillance of medication usage may be useful for understanding and comparing prescribing practices by healthcare providers, particularly in countries such as Australia that are in the process of enhancing nationwide data linkage programs. We sought to investigate the utility of electronic hospital admission data to investigate local trends in medication use, to determine similarities and differences with other Australian studies, and to identify areas for targeted interventions. Methods: We performed a retrospective longitudinal analysis using combined data from a hospital admissions administrative dataset from a large tertiary teaching hospital in Adelaide, South Australia and a hospital administrative database documenting medication usage matched for the same set of patients. All adult admissions over a 12-year period, between 1 January 2007 and 31st December 2018, were included in the study population. Medications were categorized into 21 pre-defined drug classes of interest according to the ATC code list 2021. Results: Of the 692,522 total admissions, 300,498 (43.4%) had at least one recorded medication. The overall mean number of medications for patients that were medicated increased steadily from a mean (SD) of 5.93 (4.04) in 2007 to 7.21 (4.98) in 2018. Results varied considerably between age groups, with the older groups increasing more rapidly. Increased medication usage was partly due to increased case-complexity with the mean (SD) Charlson comorbidity index increasing from 0.97 (1.66) in 2007-to-2012 to 1.17 (1.72) in 2013-to-2018 for medicated patients. Of the 21 medication classes, 15 increased (p < 0.005), including antithrombotic agents; OR = 1.18 [1.16–1.21], proton pump inhibitors; OR = 1.14 [1.12–1.17], statins; OR = 1.12; [1.09–1.14], and renin-angiotensin system agents; OR = 1.06 [1.04–1.08], whilst 3 decreased (p < 0.005) including anti-inflammatory drugs (OR = 0.55; 99.5% CI = 0.53–0.58), cardiac glycosides (OR = 0.81; 99.5% CI = 0.78–0.86) and opioids (OR = 0.82; 99.5% CI = 0.79–0.83). The mean number of medications for all admissions increased between 2007 and 2011 and then declined until 2018 for each age group, except for the 18-to-35-year-olds. Conclusion: Increased medication use occurred in most age groups between 2007 and 2011 before declining slightly even after accounting for increased comorbidity burden. The use of electronic hospital admission data can assist with monitoring local medication trends and the effects of initiatives to enhance the quality use of medicines in Australia. |
format | Online Article Text |
id | pubmed-9614045 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96140452022-10-29 Using electronic admission data to monitor temporal trends in local medication use: Experience from an Australian tertiary teaching hospital Woodman, Richard J. Horwood, Chris Kunnel, Aline Hakendorf, Paul Mangoni, Arduino A. Front Pharmacol Pharmacology Background and aims: Medication usage varies according to prescribing behavior, professional recommendations, and the introduction of new drugs. Local surveillance of medication usage may be useful for understanding and comparing prescribing practices by healthcare providers, particularly in countries such as Australia that are in the process of enhancing nationwide data linkage programs. We sought to investigate the utility of electronic hospital admission data to investigate local trends in medication use, to determine similarities and differences with other Australian studies, and to identify areas for targeted interventions. Methods: We performed a retrospective longitudinal analysis using combined data from a hospital admissions administrative dataset from a large tertiary teaching hospital in Adelaide, South Australia and a hospital administrative database documenting medication usage matched for the same set of patients. All adult admissions over a 12-year period, between 1 January 2007 and 31st December 2018, were included in the study population. Medications were categorized into 21 pre-defined drug classes of interest according to the ATC code list 2021. Results: Of the 692,522 total admissions, 300,498 (43.4%) had at least one recorded medication. The overall mean number of medications for patients that were medicated increased steadily from a mean (SD) of 5.93 (4.04) in 2007 to 7.21 (4.98) in 2018. Results varied considerably between age groups, with the older groups increasing more rapidly. Increased medication usage was partly due to increased case-complexity with the mean (SD) Charlson comorbidity index increasing from 0.97 (1.66) in 2007-to-2012 to 1.17 (1.72) in 2013-to-2018 for medicated patients. Of the 21 medication classes, 15 increased (p < 0.005), including antithrombotic agents; OR = 1.18 [1.16–1.21], proton pump inhibitors; OR = 1.14 [1.12–1.17], statins; OR = 1.12; [1.09–1.14], and renin-angiotensin system agents; OR = 1.06 [1.04–1.08], whilst 3 decreased (p < 0.005) including anti-inflammatory drugs (OR = 0.55; 99.5% CI = 0.53–0.58), cardiac glycosides (OR = 0.81; 99.5% CI = 0.78–0.86) and opioids (OR = 0.82; 99.5% CI = 0.79–0.83). The mean number of medications for all admissions increased between 2007 and 2011 and then declined until 2018 for each age group, except for the 18-to-35-year-olds. Conclusion: Increased medication use occurred in most age groups between 2007 and 2011 before declining slightly even after accounting for increased comorbidity burden. The use of electronic hospital admission data can assist with monitoring local medication trends and the effects of initiatives to enhance the quality use of medicines in Australia. Frontiers Media S.A. 2022-10-14 /pmc/articles/PMC9614045/ /pubmed/36313311 http://dx.doi.org/10.3389/fphar.2022.888677 Text en Copyright © 2022 Woodman, Horwood, Kunnel, Hakendorf and Mangoni. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pharmacology Woodman, Richard J. Horwood, Chris Kunnel, Aline Hakendorf, Paul Mangoni, Arduino A. Using electronic admission data to monitor temporal trends in local medication use: Experience from an Australian tertiary teaching hospital |
title | Using electronic admission data to monitor temporal trends in local medication use: Experience from an Australian tertiary teaching hospital |
title_full | Using electronic admission data to monitor temporal trends in local medication use: Experience from an Australian tertiary teaching hospital |
title_fullStr | Using electronic admission data to monitor temporal trends in local medication use: Experience from an Australian tertiary teaching hospital |
title_full_unstemmed | Using electronic admission data to monitor temporal trends in local medication use: Experience from an Australian tertiary teaching hospital |
title_short | Using electronic admission data to monitor temporal trends in local medication use: Experience from an Australian tertiary teaching hospital |
title_sort | using electronic admission data to monitor temporal trends in local medication use: experience from an australian tertiary teaching hospital |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9614045/ https://www.ncbi.nlm.nih.gov/pubmed/36313311 http://dx.doi.org/10.3389/fphar.2022.888677 |
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