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Evaluating the long-term effects of a data-driven approach to reduce variation in emergency department pathology investigations: study protocol for evaluation of the NSW Health Pathology Atlas of variation
INTRODUCTION: Variation in test ordering is a major issue in Australia and globally with significant financial and clinical impacts. There is currently a lack of research identifying and remediating variation in the use of pathology tests in emergency departments (EDs). In 2019, NSW Health Pathology...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7552857/ https://www.ncbi.nlm.nih.gov/pubmed/33046472 http://dx.doi.org/10.1136/bmjopen-2020-039437 |
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author | Scowen, Craig Wabe, Nasir Eigenstetter, Alex Lindeman, Robert Miao, Melissa Westbrook, Johanna I Georgiou, Andrew |
author_facet | Scowen, Craig Wabe, Nasir Eigenstetter, Alex Lindeman, Robert Miao, Melissa Westbrook, Johanna I Georgiou, Andrew |
author_sort | Scowen, Craig |
collection | PubMed |
description | INTRODUCTION: Variation in test ordering is a major issue in Australia and globally with significant financial and clinical impacts. There is currently a lack of research identifying and remediating variation in the use of pathology tests in emergency departments (EDs). In 2019, NSW Health Pathology introduced the Pathology Atlas of Variation that uses a data-driven tool (the Atlas Analytical Model) to investigate test order variation across New South Wales (NSW) and engage with local health districts (LHDs) to reduce variation. The objectives of this study are to evaluate whether this data-driven approach is associated with: (1) a reduction in test order variation; (2) improvements in patient outcomes and (3) cost benefits, for the five most frequent ED presentations. METHODS AND ANALYSIS: This is a large multisite study including 45 major public hospitals across 15 LHDs in NSW, Australia. The Atlas Analytical Model is a data analytics and visualisation tool capable of providing analytical insights into variation in pathology investigations across NSW EDs, which will be used as feedback to inform LHDs efforts to reduce variation. Interrupted time series analyses using 2 years pre Atlas (2017–2018) and 2 years post Atlas (2021–2022) data will be conducted. Study data will be obtained by linking hospital and laboratory databases. Funnel plots will be used to identify EDs with outlying pathology test ordering practices. The outcome measures include changes in test ordering practices, ED length of stay, hospital admission and cost benefits (total pathology costs per ED encounter). ETHICS AND DISSEMINATION: The study has received ethical approval from the NSW Population and Health Service Research Ethics Committee (reference, 2019/ETH00184). The findings of the study will be published in peer-reviewed journals and disseminated via presentations at conferences. We will also engage directly with key stakeholders to disseminate the findings and to inform policies related to pathology testing in the ED. |
format | Online Article Text |
id | pubmed-7552857 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-75528572020-10-21 Evaluating the long-term effects of a data-driven approach to reduce variation in emergency department pathology investigations: study protocol for evaluation of the NSW Health Pathology Atlas of variation Scowen, Craig Wabe, Nasir Eigenstetter, Alex Lindeman, Robert Miao, Melissa Westbrook, Johanna I Georgiou, Andrew BMJ Open Health Informatics INTRODUCTION: Variation in test ordering is a major issue in Australia and globally with significant financial and clinical impacts. There is currently a lack of research identifying and remediating variation in the use of pathology tests in emergency departments (EDs). In 2019, NSW Health Pathology introduced the Pathology Atlas of Variation that uses a data-driven tool (the Atlas Analytical Model) to investigate test order variation across New South Wales (NSW) and engage with local health districts (LHDs) to reduce variation. The objectives of this study are to evaluate whether this data-driven approach is associated with: (1) a reduction in test order variation; (2) improvements in patient outcomes and (3) cost benefits, for the five most frequent ED presentations. METHODS AND ANALYSIS: This is a large multisite study including 45 major public hospitals across 15 LHDs in NSW, Australia. The Atlas Analytical Model is a data analytics and visualisation tool capable of providing analytical insights into variation in pathology investigations across NSW EDs, which will be used as feedback to inform LHDs efforts to reduce variation. Interrupted time series analyses using 2 years pre Atlas (2017–2018) and 2 years post Atlas (2021–2022) data will be conducted. Study data will be obtained by linking hospital and laboratory databases. Funnel plots will be used to identify EDs with outlying pathology test ordering practices. The outcome measures include changes in test ordering practices, ED length of stay, hospital admission and cost benefits (total pathology costs per ED encounter). ETHICS AND DISSEMINATION: The study has received ethical approval from the NSW Population and Health Service Research Ethics Committee (reference, 2019/ETH00184). The findings of the study will be published in peer-reviewed journals and disseminated via presentations at conferences. We will also engage directly with key stakeholders to disseminate the findings and to inform policies related to pathology testing in the ED. BMJ Publishing Group 2020-10-12 /pmc/articles/PMC7552857/ /pubmed/33046472 http://dx.doi.org/10.1136/bmjopen-2020-039437 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Health Informatics Scowen, Craig Wabe, Nasir Eigenstetter, Alex Lindeman, Robert Miao, Melissa Westbrook, Johanna I Georgiou, Andrew Evaluating the long-term effects of a data-driven approach to reduce variation in emergency department pathology investigations: study protocol for evaluation of the NSW Health Pathology Atlas of variation |
title | Evaluating the long-term effects of a data-driven approach to reduce variation in emergency department pathology investigations: study protocol for evaluation of the NSW Health Pathology Atlas of variation |
title_full | Evaluating the long-term effects of a data-driven approach to reduce variation in emergency department pathology investigations: study protocol for evaluation of the NSW Health Pathology Atlas of variation |
title_fullStr | Evaluating the long-term effects of a data-driven approach to reduce variation in emergency department pathology investigations: study protocol for evaluation of the NSW Health Pathology Atlas of variation |
title_full_unstemmed | Evaluating the long-term effects of a data-driven approach to reduce variation in emergency department pathology investigations: study protocol for evaluation of the NSW Health Pathology Atlas of variation |
title_short | Evaluating the long-term effects of a data-driven approach to reduce variation in emergency department pathology investigations: study protocol for evaluation of the NSW Health Pathology Atlas of variation |
title_sort | evaluating the long-term effects of a data-driven approach to reduce variation in emergency department pathology investigations: study protocol for evaluation of the nsw health pathology atlas of variation |
topic | Health Informatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7552857/ https://www.ncbi.nlm.nih.gov/pubmed/33046472 http://dx.doi.org/10.1136/bmjopen-2020-039437 |
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