Abstract
Identifying those patient groups, who have unwanted outcomes, in the early stages is crucial to providing the most appropriate level of care. In this study, we intend to find distinctive patterns in health service use (HSU) of transport accident injured patients within the first week post-injury. Aiming those patterns that are associated with the outcome of interest. To recognize these patterns, we propose a multi-objective optimization model that minimizes the k-medians cost function and regression error simultaneously. Thus, we use a semi-supervised clustering approach to identify patient groups based on HSU patterns and their association with total cost. To solve the optimization problem, we introduce an evolutionary algorithm using stochastic gradient descent and Pareto optimal solutions. As a result, we find the best optimal clusters by minimizing both objective functions. The results show that the proposed semi-supervised approach identifies distinct groups of HSUs and contributes to predict total cost. Also, the experiments prove the performance of the multi-objective approach in comparison with single-objective approaches.
Original language | English |
---|---|
Title of host publication | Digital Health: Changing the Way Healthcare is Conceptualised and Delivered |
Subtitle of host publication | Selected Papers from the 27th Australian National Health Informatics Conference (HIC 2019) |
Editors | Elizabeth Cummings, Mark Merolli, Louise K. Schaper |
Place of Publication | Amsterdam Netherlands |
Publisher | IOS Press |
Pages | 1-6 |
Number of pages | 6 |
ISBN (Electronic) | 9781643680071 |
ISBN (Print) | 9781643680064 |
DOIs | |
Publication status | Published - 8 Aug 2019 |
Event | Health Informatics Conference 2019 - Melbourne, Australia Duration: 12 Aug 2019 → 14 Aug 2019 Conference number: 27th https://www.hisa.org.au/hic2019/ |
Publication series
Name | Studies in Health Technology and Informatics |
---|---|
Volume | 266 |
ISSN (Print) | 0926-9630 |
ISSN (Electronic) | 1879-8365 |
Conference
Conference | Health Informatics Conference 2019 |
---|---|
Abbreviated title | HIC 2019 |
Country/Territory | Australia |
City | Melbourne |
Period | 12/08/19 → 14/08/19 |
Internet address |
Keywords
- Health service patterns
- Injured patients
- Injury outcomes
- Multi-objective optimization
- Semi-supervised clustering