Paper
Monday, November 14, 2005
A Decision Support System for Cancer Pain Management
Wonshik Chee, PhD, Mechanical Engineering and Biomechanics, The University of Texas at San Antonio, San Antonio, TX, USA, Hsiu-Min Tsai, PhD, Associate Professor, Dean of Academic Affairs, Chang Gung Institute of Technology/Nursing, Kwei-Shan, Tao-Yuan, Taiwan, and Eun-Ok Im, RN, MPH, PhD, CNS, School of Nursing, University of Texas at Austin, Austin, TX, USA.
| Learning Objective #1: Understand the evaluation process of a decision support system |
| Learning Objective #2: Explore the effectiveness of the Internet intervention study in order to evaluate a decision support system |
PURPOSE: To assist nurses' decision making on cancer pain management, a decision support system for cancer pain management was recently developed. However, the decision support system has rarely been evaluated among nurses working with cancer patients. The purpose of this study was to evaluate the decision support system among nurses working in oncology units through the Internet. THEORETICAL FRAMEWORK: Fuzzy logic guided the study theoretically. METHOD: 111 self-identified registered nurses who were working with cancer patients in oncology units were recruited using a convenience sampling method. A project website was developed for the data collection. When a participant agreed to participate, she/he was asked to register by entering her/his answers for the questions for registration through the Internet. Then, she/he was asked to answer the questions for refinement and to generate cancer pain management strategies by using the decision support system. After generating the strategies, she/he was asked to answer the evaluation questions on appropriateness, accuracy, and acceptability of the decision support system. DATA ANALYSIS: The data entered for refinement were automatically uploaded and used to upgrade the decision support system through the self-adaptation module included in the system. The data entered for registration and evaluation of the decision support system were analyzed using descriptive statistics. FINDINGS & IMPLICATIONS: The decision support system was successfully upgraded and refined with the data from 111 nurses. 89% of the participants evaluated the decision support computer program as appropriate; 90% evaluated it as accurate; and 97% reported it as acceptable. The findings support that the decision support system can assist nurses' decision making on cancer pain management with more culturally competent guidelines.