Support Preferences and Clinical Decision Support Systems (CDSS) in the Clinical Care of Autistic Children: Stakeholder Perspectives
This publication is included in the Autistic Autism Scholarship Project. one author of this publication is identified as autistic in the project.
About the autistic author markerSulek, R., Robertson, J., Goodall, E., Liew, A. W. C., Pillar, S., Upson, G., Whitehouse, A., Wicks, R., & Trembath, D. (2024). Support Preferences and Clinical Decision Support Systems (CDSS) in the Clinical Care of Autistic Children: Stakeholder Perspectives. Advances in Neurodevelopmental Disorders, 9(2), 355-365. https://doi.org/10.1007/s41252-024-00410-4
- Journal or book title
- Advances in Neurodevelopmental Disorders
- Publisher
- Springer Science and Business Media LLC
- Volume
- 9
- Issue
- 2
- Pages
- 355-365
This publication is integrated into AutiHub through:
Authors
Abstract
Abstract Objectives Clinical decision support systems (CDSS) are increasingly utilised within healthcare settings to enhance decision making. However, few studies have investigated their application in the context of clinical services for autistic people, with no research to date exploring the perspectives of the key stakeholders who are, or in the future may be, impacted by their use. Given the importance of stakeholder perspectives in ensuring that CDSSs are relevant, feasible, and acceptable to those who use them, the aim of this study was to examine the views of key stakeholders in relation to support preferences and a proposed CDSS intended to aide in the selection of the most appropriate supports for autistic children. Method Using a co-designed, mixed-methods approach, 20 participants comprising autistic adults, parents of autistic children, and practitioners providing services to autistic children were invited to participate in focus groups, or an open-ended online survey, to explore views regarding support provision and any opportunities, barriers, recommendations, and support for the use of CDSSs in clinical practice. Results Participants highlighted potential benefits of using a CDSS in clinical practice, such as creating efficiencies and consistency in decision making when selecting therapies and supports, provided it was part of a holistic approach to working with autistic children. Potential barriers largely centred on concerns about the safety of data to be utilised within the system. Conclusions The findings indicate that CDSS have the potential to play a valuable role in selecting supports for autistic children, providing appropriate safeguarding occurs.
Bibliography cited by this reference
Cited references are imported from external metadata sources when they are available. The list may be partial.
Cited bibliography overview
These indicators describe the bibliography cited by this publication. An author name is counted each time it appears in one cited reference, so the same person can be counted more than once. Names not yet linked to an author already present in AutiHub are treated as unknown, not as non-autistic. Last computed: 2 Oct 2026 01:40.
- With a DOI
- 15
- Without a DOI, from raw bibliography text
- 6
- References with detected author names
- 15 / 21 (71.4%)
- Without detected author names
- 6
- Without a structured title
- 6
- Without a stable identifier
- 6
- References with raw author names still to review
- 0
- References with external metadata lookup issues
- 0
- From DOI or external metadata
- 73
- From validated raw bibliography text
- 0
- Raw names already validated
- 0
- Raw names still to review
- 29
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Nicola K Gale , Gemma Heath , Elaine Cameron , Sabina Rashid , Sabi Redwood (2013). Using the framework method for the analysis of qualitative data in multi-disciplinary health research . BMC Medical Research Methodology, 13(1), 117. Springer Science and Business Media LLC.Crossref OpenAlex OpenCitations
-
the Precise4Q consortium , Julia Amann , Alessandro Blasimme , Effy Vayena , Dietmar Frey , Vince I. Madai (2020). Explainability for artificial intelligence in healthcare: a multidisciplinary perspective . BMC Medical Informatics and Decision Making, 20(1), 310. Springer Science and Business Media LLC.Crossref OpenAlex OpenCitations
-
Wolfgang Lutz , Anne-Katharina Deisenhofer , Julian Rubel , Björn Bennemann , Julia Giesemann , Kaitlyn Poster et al. (2022). Prospective evaluation of a clinical decision support system in psychological therapy. Journal of Consulting and Clinical Psychology, 90(1), 90-106. American Psychological Association (APA).Crossref OpenAlex OpenCitations
-
Shoshana Haberman , Joseph Feldman , Zaher O. Merhi , Glenn Markenson , Wayne Cohen , Howard Minkoff (2009). Effect of Clinical-Decision Support on Documentation Compliance in an Electronic Medical Record . Obstetrics & Gynecology, 114(2), 311-317. Ovid Technologies (Wolters Kluwer Health).Crossref OpenAlex OpenCitations
-
Monique Botha *Autistic author. Learn more… , Bridget Dibb , David M. Frost (2022). Autism is me”: an investigation of how autistic individuals make sense of autism and stigma . Disabil Soc, 37(3), 427-453. Informa UK Limited.
-
Reed T. Sutton , David Pincock , Daniel C. Baumgart , Daniel C. Sadowski , Richard N. Fedorak , Karen I. Kroeker (2020). An overview of clinical decision support systems: benefits, risks, and strategies for success . npj Digital Medicine, 3(1), 17-17. Springer Science and Business Media LLC.Crossref OpenAlex OpenCitations
-
Olesya I. Zorina , Patrick Haueis , Waldemar Greil , Renate Grohmann , Gerd A. Kullak-Ublick , Stefan Russmann (2013). Comparative Performance of Two Drug Interaction Screening Programmes Analysing a Cross-Sectional Prescription Dataset of 84,625 Psychiatric Inpatients . Drug Safety, 36(4), 247-258. Springer Science and Business Media LLC.Crossref OpenAlex OpenCitations
-
Zhao Chen , Ning Liang , Haili Zhang , Huizhen Li , Yijiu Yang , Xingyu Zong et al. (2023). Harnessing the power of clinical decision support systems: challenges and opportunities . Open Heart, 10(2), e002432. BMJ.Crossref OpenAlex OpenCitations
-
Edward H. Shortliffe , Martin J. Sepúlveda (2018). Clinical Decision Support in the Era of Artificial Intelligence . JAMA, 320(21), 2199. American Medical Association (AMA).Crossref OpenAlex OpenCitations
-
Giovanni Cioni , Emanuela Inguaggiato , Giuseppina Sgandurra (2016). Early intervention in neurodevelopmental disorders: underlying neural mechanisms . Developmental Medicine & Child Neurology, 58(S4), 61-66. Wiley.Crossref OpenAlex OpenCitations
-
S M Honaker , S M Downs (2018). 0744 Automated Universal OSA Screening in Pediatric Primary Care . Sleep, 41(suppl_1), A277-A277. Oxford University Press (OUP).Crossref OpenAlex OpenCitations
-
Commonwealth of Australia, Department of the Prime Minister and Cabinet. (2023). Working together to deliver the NDIS – Independent review into the National Disability Insurance Scheme: Final report.Type: OtherCrossref
-
Jacquiline den Houting *Autistic author. Learn more… (2019). Neurodiversity: An insider’s perspective . Autism, 23(2), 271-273. SAGE Publications.
-
David Trembath , Hannah Waddington , Rhylee Sulek , Kandice Varcin , Catherine Bent , Jill Ashburner et al. (2021). An evidence-based framework for determining the optimal amount of intervention for autistic children . The Lancet Child & Adolescent Health, 5(12), 896-904. Elsevier BV.
-
Tamra Lysaght , Hannah Yeefen Lim , Vicki Xafis , Kee Yuan Ngiam (2019). AI-Assisted Decision-making in Healthcare . Asian Bioethics Review, 11(3), 299-314. Springer Science and Business Media LLC.Crossref OpenAlex OpenCitations
-
Clemens Scott Kruse , Nolan Ehrbar (2020). Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes: Systematic Review . JMIR Medical Informatics, 8(8), e17283. JMIR Publications Inc..Crossref OpenAlex OpenCitations
-
John, R., Buschman, P., Chaszar, M., Honig, J., Mendonca, E., & Bakken, S. (2007). Development and evaluation of a PDA-based decision support system for pediatric depression screening [Article]. Medinfo, 12(Pt 2), 1382–1386. https://www.embase.com/search/results?subaction=viewrecord&id=L350039388&from=exportType: OtherCrossref
-
Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice (4th ed.). SAGE Publications, Inc.Type: OtherCrossref
-
Sackett, D. L., Richardson, W. S., Straus, S. E., Rosenberg, W., & Haynes, R. B. (2000). Evidence-based medicine: How to practice and teach EBM (Vol. 2). Churchill Livingstone. https://books.google.com.au/books?id=oIJrAAAAMAAJType: OtherCrossref
-
Sulek, R., Robertson, J., Baque, E., Liew, A. W. C., Shirota, C., Upson, G., Whitehouse, A. J. O., & Trembath, D. (2022). The use of Clinical Decision Support Systems (CDSS) in the delivery of services to children with neurodevelopmental conditions: a scoping review. OSF. osf.io/m7p2xType: OtherCrossref
-
Trevana, L., McCaffery, K., Salkeld, G., Glasziou, P., Del Mar, C., Doust, J., & Hoffman, T. (2014). Clinical decision-making tools: How effective are they in improving the quality of health care? Australian Healthcare & Hospitals Association. https://ahha.asn.au/system/files/docs/publications/deeble_issues_brief_nlcg-2_clinical_decision-making_tools.pdfType: OtherCrossref