Abstract
Due to rapidly ageing population, the need for care and attention homes for the elderly and patient with chronic illnesses has increased significantly in recent years. However, the continuous increase in operation and medical costs and the problem of drugs shortages bring increasing pressure to care and attention homes in regard to medical resource allocation. In such situations, patients may not receive appropriate treatment and hence dissatisfaction with the quality of service may result. Therefore, it is essential to have a decision support system to ensure that an optimal amount of medical resources are stored so as to maintain a sustainable healthcare service. In this paper, an intelligent medical replenishment system (IMRS) is proposed to assist healthcare workers in arranging the appropriate type and quantity of drugs, based on the needs of patients. In IMRS, artificial intelligent techniques, i.e. fuzzy association rules mining and fuzzy logic, are applied to evaluate the historical diagnosis records of patients and determine the amount and frequency of medical resources for replenishment. To validate the feasibility of the proposed system, a pilot study is conducted in a care and attention home located in Hong Kong. The result shows that the IMRS is effective in improving the healthcare service quality for the elderly in terms of the elderly satisfaction and medical resources fulfillment.
Original language | English |
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Title of host publication | 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016 |
Publisher | IEEE |
Pages | 154-161 |
Number of pages | 8 |
ISBN (Electronic) | 9781509006250 |
DOIs | |
Publication status | Published - 7 Nov 2016 |
Event | 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016 - Vancouver, Canada Duration: 24 Jul 2016 → 29 Jul 2016 |
Conference
Conference | 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016 |
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Country/Territory | Canada |
City | Vancouver |
Period | 24/07/16 → 29/07/16 |
Keywords
- Care and attention home service
- Fuzzy association rule mining
- Fuzzy logic
- Healthcare industry
- Medical resource replenishment
ASJC Scopus subject areas
- Control and Optimization
- Logic
- Modelling and Simulation