A digital health ecosystem ontology from the perspective of Australian consumers: a mixed-method literature analysis

ABSTRACT

This study presents an ontology that scopes the digital health ecosystem from a consumer–centered perspective. We used a mixed-method analysis on a set of papers collected for a comprehensive review to identify common themes, components, and patterns that repeatedly emerge within Australian-based digital health studies. Three major and four child themes were identified as the foundational aspects of the proposed ontology. The child themes have more precise concept definitions, inherited and distinguishing attributes. Out of 179 recognized concepts, 33 were related to the Healthcare theme; 23 concepts formed a cluster of employed devices under the Technology theme; 40 concepts were associated with Use and Usability factors. 60 other concepts formed the cluster of the consumer–user theme. The theme of Digital Health was seen as being connected to 2 independent clusters. The main cluster embodied 21 extracted concepts, semantically related to “data, information, and knowledge,” whilst the second cluster embodied concepts related to “healthcare.” Different stakeholders can utilize this ontology to define their landscape of digitally enabled healthcare. The novelty of this work resides in capturing a consumer–centered perspective and the method we used in deriving the ontology – formalizing the results of a systematic review based on data-driven analysis methods.

KEYWORDS:

• Digital health
• ecosystem
• healthcare systems
• ontology
• conceptual modeling
• consumer
• Australia

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

FB and AOA conceived of the presented idea and that approved by CB. AOA and FB developed the theory and AOA performed the computations and analyses. FB verified the analytical methods. AOA drafted the manuscript, and it was revised critically for important intellectual content by all authors. All authors approved the manuscript for publication and agree to be accountable for all aspects of the work.

Abraham Oshni Alvandi: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Writing - Original Draft, Writing - Review & Editing, Visualization

Frada Burstein: Conceptualization, Methodology, Validation, Supervision, Writing - Original Draft, Writing - Review & Editing,

Chris Bain: Validation, Funding acquisition, Writing - Original Draft, Writing - Review & Editing

Abraham Oshni Alvandi is a researcher in digital health in the Faculty of Information Technology at Monash University Australia. He is passionate about multidisciplinary studies where cognitive and information systems meet each other and his current focus is on consumer health informatics. He aims to understand how digital healthcare technologies are perceived by the public, how they should be designed to accord to consumers’ health requirements, and how innovations should transform the activities of the healthcare industries in the best ways to deliver excellent customer service to citizens. Abraham also works in Bayesian Networks (BNs) that are applied to support decision-making under uncertainty; especially, health-related problems that are targets for medical decision support systems.

Chris Bain is a Professor of Practice in Digital Health in the Faculty of Information Technology at Monash University in Australia. Chris’ position is the first of its kind in the faculty. He has more than 30 years’ experience in the health industry, including 12 in clinical medicine. He’s led numerous software development and implementation projects in the health industry and works with many faculties and Institutes across the University, as well as with a range of health industry partners, in leading the Monash efforts in Digital Health.

Frada Burstein is a Professor (Adjunct) at the Faculty of Information Technology, Monash University, Melbourne, Australia. At Monash University, Prof. Burstein led multiple projects on the use of technology in the healthcare context. Her current research interests include business intelligence, clinical decision support, and health informatics. Her work appears in leading journals such as Decision Support Systems, Journal of the American Society for Information Science and Technology, Journal of Medical Internet Research, and others. Prof. Burstein has been a guest editor of a few special issues of journals and collections of research papers. She is a Fellow of the Australian Computer Society and Distinguished Member of the Association for Information Systems. Full research profile available at: https://research.monash.edu/en/persons/frada-burstein

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website

Notes

¹ Table 3 lists the top 21 words that are weighted about 30% of all 400 words identified by this analysis. The summary of the analysis can be found in the Appendix B.

² F stands for Frequency

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.