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Experts' perceptions on the use of visual analytics for complex mental healthcare planning: an exploratory study

Walsh, Erin; Chung, Youn Jin; Cherbuin, Nicolas; Salvador-Carulla, Luis

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Abstract Background: Health experts including planners and policy-makers face complex decisions in diverse and constantly changing healthcare systems. Visual analytics may play a critical role in supporting analysis of complex healthcare data and decision-making. The purpose of this study was to examine the real-world experience that experts in mental healthcare planning have with visual analytics tools, investigate how well current visualisation techniques meet their needs, and suggest...[Show more]

dc.contributor.authorWalsh, Erin
dc.contributor.authorChung, Youn Jin
dc.contributor.authorCherbuin, Nicolas
dc.contributor.authorSalvador-Carulla, Luis
dc.date.accessioned2020-10-12T00:02:13Z
dc.date.available2020-10-12T00:02:13Z
dc.identifier.issn1471-2288
dc.identifier.urihttp://hdl.handle.net/1885/212424
dc.description.abstractAbstract Background: Health experts including planners and policy-makers face complex decisions in diverse and constantly changing healthcare systems. Visual analytics may play a critical role in supporting analysis of complex healthcare data and decision-making. The purpose of this study was to examine the real-world experience that experts in mental healthcare planning have with visual analytics tools, investigate how well current visualisation techniques meet their needs, and suggest priorities for the future development of visual analytics tools of practical benefit to mental healthcare policy and decision-making. Methods: Health expert experience was assessed by an online exploratory survey consisting of a mix of multiple choice and open-ended questions. Health experts were sampled from an international pool of policy-makers, health agency directors, and researchers with extensive and direct experience of using visual analytics tools for complex mental healthcare systems planning. We invited them to the survey, and the experts' responses were analysed using statistical and text mining approaches. Results: The forty respondents who took part in the study recognised the complexity of healthcare systems data, but had most experience with and preference for relatively simple and familiar visualisations such as bar charts, scatter plots, and geographical maps. Sixty-five percent rated visual analytics as important to their field for evidence-informed decision-making processes. Fifty-five percent indicated that more advanced visual analytics tools were needed for their data analysis, and 67.5% stated their willingness to learn new tools. This was reflected in text mining and qualitative synthesis of open-ended responses. Conclusions: This exploratory research provides readers with the first self-report insight into expert experience with visual analytics in mental healthcare systems research and policy. In spite of the awareness of their importance for complex healthcare planning, the majority of experts use simple, readily available visualisation tools. We conclude that co-creation and co-development strategies will be required to support advanced visual analytics tools and skills, which will become essential in the future of healthcare. Keywords: Visual analytics, Expert experience, Complex data analysis, Mental healthcare systems, Evidence-informed decision-making, Co-development
dc.description.sponsorshipThe study was supported by the 2019 Excellence in Population Health Research Award (Research School of Population Health, Australian National University).
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherBioMed Central
dc.rights© The Author(s).
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceBMC Medical Research Methodology
dc.titleExperts' perceptions on the use of visual analytics for complex mental healthcare planning: an exploratory study
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume20
dc.date.issued2020
local.identifier.absfor111714 - Mental Health
local.identifier.absfor111711 - Health Information Systems (incl. Surveillance)
local.identifier.ariespublicationu4102339xPUB474
local.publisher.urlhttp://www.biomedcentral.com/bmcmedresmethodol/
local.type.statusPublished Version
local.contributor.affiliationWalsh, Erin, College of Health and Medicine, ANU
local.contributor.affiliationChung, Youn Jin, College of Health and Medicine, ANU
local.contributor.affiliationCherbuin, Nicolas, College of Health and Medicine, ANU
local.contributor.affiliationSalvador-Carulla, Luis, College of Health and Medicine, ANU
local.bibliographicCitation.issue110
local.bibliographicCitation.startpage1
local.bibliographicCitation.lastpage9
local.identifier.doi10.1186/s12874-020-00986-0
local.identifier.absseo920209 - Mental Health Services
local.identifier.absseo920208 - Health Policy Evaluation
local.identifier.absseo920204 - Evaluation of Health Outcomes
dc.date.updated2020-07-05T08:18:13Z
dcterms.accessRightsOpen Access
dc.provenance© The Author(s). 2020 Open Access This 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/. 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 in a credit line to the data.
dc.rights.licenseCreative Commons Attribution 4.0 International License
CollectionsANU Research Publications

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