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COVID-19: protocol for observational studies utilizing near real-time electronic Australian general practice data to promote effective care and best-practice policy—a design thinking approach
BACKGROUND: Health systems around the world have been forced to make choices about how to prioritize care, manage infection control and maintain reserve capacity for future disease outbreaks. Primary healthcare has moved into the front line as COVID-19 testing transitions from hospitals to multiple...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423333/ https://www.ncbi.nlm.nih.gov/pubmed/34493295 http://dx.doi.org/10.1186/s12961-021-00772-4 |
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author | Georgiou, Andrew Li, Julie Pearce, Christopher McLeod, Adam Wabe, Nasir Hardie, Rae-Anne Franco, Guilherme Saffi Imai, Chisato Sezgin, Gorkem Thomas, Judith Dai, Zhaoli Sheikh, Muhammad Kashif Proposch, Amanda Weeding, Stephen Wickham, Brendon Badrick, Tony Murgatroyd, Darnel |
author_facet | Georgiou, Andrew Li, Julie Pearce, Christopher McLeod, Adam Wabe, Nasir Hardie, Rae-Anne Franco, Guilherme Saffi Imai, Chisato Sezgin, Gorkem Thomas, Judith Dai, Zhaoli Sheikh, Muhammad Kashif Proposch, Amanda Weeding, Stephen Wickham, Brendon Badrick, Tony Murgatroyd, Darnel |
author_sort | Georgiou, Andrew |
collection | PubMed |
description | BACKGROUND: Health systems around the world have been forced to make choices about how to prioritize care, manage infection control and maintain reserve capacity for future disease outbreaks. Primary healthcare has moved into the front line as COVID-19 testing transitions from hospitals to multiple providers, where tracking testing behaviours can be fragmented and delayed. Pooled general practice data are a valuable resource which can be used to inform population and individual care decision-making. This project aims to examine the feasibility of using near real-time electronic general practice data to promote effective care and best-practice policy. METHODS: The project will utilize a design thinking approach involving all collaborators (primary health networks [PHNs], general practices, consumer groups, researchers, and digital health developers, pathology professionals) to enhance the development of meaningful and translational project outcomes. The project will be based on a series of observational studies utilizing near real-time electronic general practice data from a secure and comprehensive digital health platform [POpulation Level Analysis and Reporting (POLAR) general practice data warehouse]. The study will be carried out over 1.5 years (July 2020–December 2021) using data from over 450 general practices within three Victorian PHNs and Gippsland PHN, Eastern Melbourne PHN and South Eastern Melbourne PHN, supplemented by data from consenting general practices from two PHNs in New South Wales, Central and Eastern Sydney PHN and South Western Sydney PHN. DISCUSSION: The project will be developed using a design thinking approach, leading to the building of a meaningful near real-time COVID-19 geospatial reporting framework and dashboard for decision-makers at community, state and nationwide levels, to identify and monitor emerging trends and the impact of interventions/policy decisions. This will integrate timely evidence about the impact of the COVID-19 pandemic related to its diagnosis and treatment, and its impact across clinical, population and general practice levels. |
format | Online Article Text |
id | pubmed-8423333 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84233332021-09-08 COVID-19: protocol for observational studies utilizing near real-time electronic Australian general practice data to promote effective care and best-practice policy—a design thinking approach Georgiou, Andrew Li, Julie Pearce, Christopher McLeod, Adam Wabe, Nasir Hardie, Rae-Anne Franco, Guilherme Saffi Imai, Chisato Sezgin, Gorkem Thomas, Judith Dai, Zhaoli Sheikh, Muhammad Kashif Proposch, Amanda Weeding, Stephen Wickham, Brendon Badrick, Tony Murgatroyd, Darnel Health Res Policy Syst Study Protocol BACKGROUND: Health systems around the world have been forced to make choices about how to prioritize care, manage infection control and maintain reserve capacity for future disease outbreaks. Primary healthcare has moved into the front line as COVID-19 testing transitions from hospitals to multiple providers, where tracking testing behaviours can be fragmented and delayed. Pooled general practice data are a valuable resource which can be used to inform population and individual care decision-making. This project aims to examine the feasibility of using near real-time electronic general practice data to promote effective care and best-practice policy. METHODS: The project will utilize a design thinking approach involving all collaborators (primary health networks [PHNs], general practices, consumer groups, researchers, and digital health developers, pathology professionals) to enhance the development of meaningful and translational project outcomes. The project will be based on a series of observational studies utilizing near real-time electronic general practice data from a secure and comprehensive digital health platform [POpulation Level Analysis and Reporting (POLAR) general practice data warehouse]. The study will be carried out over 1.5 years (July 2020–December 2021) using data from over 450 general practices within three Victorian PHNs and Gippsland PHN, Eastern Melbourne PHN and South Eastern Melbourne PHN, supplemented by data from consenting general practices from two PHNs in New South Wales, Central and Eastern Sydney PHN and South Western Sydney PHN. DISCUSSION: The project will be developed using a design thinking approach, leading to the building of a meaningful near real-time COVID-19 geospatial reporting framework and dashboard for decision-makers at community, state and nationwide levels, to identify and monitor emerging trends and the impact of interventions/policy decisions. This will integrate timely evidence about the impact of the COVID-19 pandemic related to its diagnosis and treatment, and its impact across clinical, population and general practice levels. BioMed Central 2021-09-07 /pmc/articles/PMC8423333/ /pubmed/34493295 http://dx.doi.org/10.1186/s12961-021-00772-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Study Protocol Georgiou, Andrew Li, Julie Pearce, Christopher McLeod, Adam Wabe, Nasir Hardie, Rae-Anne Franco, Guilherme Saffi Imai, Chisato Sezgin, Gorkem Thomas, Judith Dai, Zhaoli Sheikh, Muhammad Kashif Proposch, Amanda Weeding, Stephen Wickham, Brendon Badrick, Tony Murgatroyd, Darnel COVID-19: protocol for observational studies utilizing near real-time electronic Australian general practice data to promote effective care and best-practice policy—a design thinking approach |
title | COVID-19: protocol for observational studies utilizing near real-time electronic Australian general practice data to promote effective care and best-practice policy—a design thinking approach |
title_full | COVID-19: protocol for observational studies utilizing near real-time electronic Australian general practice data to promote effective care and best-practice policy—a design thinking approach |
title_fullStr | COVID-19: protocol for observational studies utilizing near real-time electronic Australian general practice data to promote effective care and best-practice policy—a design thinking approach |
title_full_unstemmed | COVID-19: protocol for observational studies utilizing near real-time electronic Australian general practice data to promote effective care and best-practice policy—a design thinking approach |
title_short | COVID-19: protocol for observational studies utilizing near real-time electronic Australian general practice data to promote effective care and best-practice policy—a design thinking approach |
title_sort | covid-19: protocol for observational studies utilizing near real-time electronic australian general practice data to promote effective care and best-practice policy—a design thinking approach |
topic | Study Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423333/ https://www.ncbi.nlm.nih.gov/pubmed/34493295 http://dx.doi.org/10.1186/s12961-021-00772-4 |
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