Pattern discovery from patient controlled analgesia demand behavior

Authors:
Yuh-Jyh Hu;Tien-Hsiung Ku
Affiliations:
Department of Computer Science, National Chiao Tung University, 1001 Tashuei Rd., Hsinchu, Taiwan and Institute of Biomedical Engineering, National Chiao Tung University, 1001 Tashuei Rd., Hsinchu ...;Department of Anesthesia, Changhwa Christian Hospital, Changhwa, Taiwan
Venue:
Computers in Biology and Medicine
Year:
2012

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Abstract

Unlike previous research on patient controlled analgesia, this study explores patient demand behavior over time. We apply clustering methods to disclose demand patterns among patients over the first 24h of analgesic medication after surgery. We consider demographic, biomedical, and surgery-related data in statistical analyses to determine predictors for patient demand behavior, and use stepwise regression and Bayes risk analysis to evaluate the influence of demand pattern on analgesic requirements. We identify three demand patterns from 1655 patient controlled analgesia request log files. Statistical tests show correlations of gender (p=.0022), diastolic blood pressure (p=.025), surgery type (p=.0028), and surgical duration (p