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

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.date.issued2020
dc.date.updated2021-11-28T07:31:35Z
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).en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn1471-2288en_AU
dc.identifier.urihttp://hdl.handle.net/1885/212424
dc.language.isoen_AUen_AU
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.en_AU
dc.publisherBioMed Central
dc.rights© The Author(s).
dc.rights.licenseCreative Commons Attribution 4.0 International Licenseen_AU
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_AU
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
dcterms.accessRightsOpen Accessen_AU
local.bibliographicCitation.issue110en_AU
local.bibliographicCitation.lastpage9en_AU
local.bibliographicCitation.startpage1en_AU
local.contributor.affiliationWalsh, Erin, College of Health and Medicine, ANUen_AU
local.contributor.affiliationChung, Youn Jin, College of Health and Medicine, ANUen_AU
local.contributor.affiliationCherbuin, Nicolas, College of Health and Medicine, ANUen_AU
local.contributor.affiliationSalvador-Carulla, Luis, College of Health and Medicine, ANUen_AU
local.contributor.authoruidWalsh, Erin, u4402564en_AU
local.contributor.authoruidChung, Youn Jin, u1057153en_AU
local.contributor.authoruidCherbuin, Nicolas, u3184049en_AU
local.contributor.authoruidSalvador-Carulla, Luis, u1034103en_AU
local.description.notesImported from ARIESen_AU
local.identifier.absfor111714 - Mental Healthen_AU
local.identifier.absfor111711 - Health Information Systems (incl. Surveillance)en_AU
local.identifier.absseo920209 - Mental Health Servicesen_AU
local.identifier.absseo920208 - Health Policy Evaluationen_AU
local.identifier.absseo920204 - Evaluation of Health Outcomesen_AU
local.identifier.ariespublicationu4102339xPUB474en_AU
local.identifier.citationvolume20en_AU
local.identifier.doi10.1186/s12874-020-00986-0en_AU
local.identifier.scopusID2-s2.0-85084399533
local.publisher.urlhttp://www.biomedcentral.com/bmcmedresmethodol/en_AU
local.type.statusPublished Versionen_AU

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