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A methodological protocol for selecting and quantifying low-value prescribing practices in routinely collected data: an Australian case study
BACKGROUND: Growing imperatives for safety, quality and responsible resource allocation have prompted renewed efforts to identify and quantify harmful or wasteful (low-value) medical practices such as test ordering, procedures and prescribing. Quantifying these practices at a population level using...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5415810/ https://www.ncbi.nlm.nih.gov/pubmed/28468629 http://dx.doi.org/10.1186/s13012-017-0585-9 |
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author | Brett, Jonathan Elshaug, Adam G. Bhatia, R. Sacha Chalmers, Kelsey Badgery-Parker, Tim Pearson, Sallie-Anne |
author_facet | Brett, Jonathan Elshaug, Adam G. Bhatia, R. Sacha Chalmers, Kelsey Badgery-Parker, Tim Pearson, Sallie-Anne |
author_sort | Brett, Jonathan |
collection | PubMed |
description | BACKGROUND: Growing imperatives for safety, quality and responsible resource allocation have prompted renewed efforts to identify and quantify harmful or wasteful (low-value) medical practices such as test ordering, procedures and prescribing. Quantifying these practices at a population level using routinely collected health data allows us to understand the scale of low-value medical practices, measure practice change following specific interventions and prioritise policy decisions. To date, almost all research examining health care through the low-value lens has focused on medical services (tests and procedures) rather than on prescribing. The protocol described herein outlines a program of research funded by Australia’s National Health and Medical Research Council to select and quantify low-value prescribing practices within Australian routinely collected health data. METHODS: We start by describing our process for identifying and cataloguing international low-value prescribing practices. We then outline our approach to translate these prescribing practices into indicators that can be applied to Australian routinely collected health data. Next, we detail methods of using Australian health data to quantify these prescribing practices (e.g. prevalence of low-value prescribing and related costs) and their downstream health consequences. We have approval from the necessary Australian state and commonwealth human research ethics and data access committees to undertake this work. DISCUSSION: The lack of systematic and transparent approaches to quantification of low-value practices in routinely collected data has been noted in recent reviews. Here, we present a methodology applied in the Australian context with the aim of demonstrating principles that can be applied across jurisdictions in order to harmonise international efforts to measure low-value prescribing. The outcomes of this research will be submitted to international peer-reviewed journals. Results will also be presented at national and international pharmacoepidemiology and health policy forums such that other jurisdictions have guidance to adapt this methodology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13012-017-0585-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5415810 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54158102017-05-04 A methodological protocol for selecting and quantifying low-value prescribing practices in routinely collected data: an Australian case study Brett, Jonathan Elshaug, Adam G. Bhatia, R. Sacha Chalmers, Kelsey Badgery-Parker, Tim Pearson, Sallie-Anne Implement Sci Study Protocol BACKGROUND: Growing imperatives for safety, quality and responsible resource allocation have prompted renewed efforts to identify and quantify harmful or wasteful (low-value) medical practices such as test ordering, procedures and prescribing. Quantifying these practices at a population level using routinely collected health data allows us to understand the scale of low-value medical practices, measure practice change following specific interventions and prioritise policy decisions. To date, almost all research examining health care through the low-value lens has focused on medical services (tests and procedures) rather than on prescribing. The protocol described herein outlines a program of research funded by Australia’s National Health and Medical Research Council to select and quantify low-value prescribing practices within Australian routinely collected health data. METHODS: We start by describing our process for identifying and cataloguing international low-value prescribing practices. We then outline our approach to translate these prescribing practices into indicators that can be applied to Australian routinely collected health data. Next, we detail methods of using Australian health data to quantify these prescribing practices (e.g. prevalence of low-value prescribing and related costs) and their downstream health consequences. We have approval from the necessary Australian state and commonwealth human research ethics and data access committees to undertake this work. DISCUSSION: The lack of systematic and transparent approaches to quantification of low-value practices in routinely collected data has been noted in recent reviews. Here, we present a methodology applied in the Australian context with the aim of demonstrating principles that can be applied across jurisdictions in order to harmonise international efforts to measure low-value prescribing. The outcomes of this research will be submitted to international peer-reviewed journals. Results will also be presented at national and international pharmacoepidemiology and health policy forums such that other jurisdictions have guidance to adapt this methodology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13012-017-0585-9) contains supplementary material, which is available to authorized users. BioMed Central 2017-05-03 /pmc/articles/PMC5415810/ /pubmed/28468629 http://dx.doi.org/10.1186/s13012-017-0585-9 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Study Protocol Brett, Jonathan Elshaug, Adam G. Bhatia, R. Sacha Chalmers, Kelsey Badgery-Parker, Tim Pearson, Sallie-Anne A methodological protocol for selecting and quantifying low-value prescribing practices in routinely collected data: an Australian case study |
title | A methodological protocol for selecting and quantifying low-value prescribing practices in routinely collected data: an Australian case study |
title_full | A methodological protocol for selecting and quantifying low-value prescribing practices in routinely collected data: an Australian case study |
title_fullStr | A methodological protocol for selecting and quantifying low-value prescribing practices in routinely collected data: an Australian case study |
title_full_unstemmed | A methodological protocol for selecting and quantifying low-value prescribing practices in routinely collected data: an Australian case study |
title_short | A methodological protocol for selecting and quantifying low-value prescribing practices in routinely collected data: an Australian case study |
title_sort | methodological protocol for selecting and quantifying low-value prescribing practices in routinely collected data: an australian case study |
topic | Study Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5415810/ https://www.ncbi.nlm.nih.gov/pubmed/28468629 http://dx.doi.org/10.1186/s13012-017-0585-9 |
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