Journal
DECISION SUPPORT SYSTEMS
Volume 50, Issue 2, Pages 439-448Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.dss.2010.11.001
Keywords
Hemodialysis; Temporal abstract; Data mining; Healthcare quality
Categories
Funding
- National Science Council [NSC97-2221-E-415-008-MY3]
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Hemodialysis patients might suffer from unhealthy care behaviors or long-term dialysis treatments and need to be hospitalized. If the hospitalization rate of a hemodialysis center is high, its service quality will be low. Therefore, decreasing hospitalization rate is a crucial problem for health care centers. This study combines temporal abstraction with data mining techniques for analyzing dialysis patients' biochemical data to develop a decision support system. The mined temporal patterns are helpful for clinicians to predict hospitalization of hemodialysis patients and to suggest immediate treatments to avoid hospitalization. (C) 2010 Elsevier B.V. All rights reserved.
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