Developing Treatment Plan Support in Outpatient Health Care Delivery with Decision Trees Technique
This paper presents treatment plan support (IPS) development with the aim to support treatment decision making for physicians during outpatient-care giving to patients. Evidence-based clinical data from system database was used. The TPS predictive modeling was generated using decision trees technique, which incorporated predictor variables: patients age, gender, racial, marital status, occupation, visit complaint, clinical diagnosis and final diagnosed diseases; while dependent variable: treatment by drug, laboratory, imaging and/or procedure. Six common diseases which are coded as J02.9, J03.9, J06.9, J30.4, M62.6 and N39.0 in the International Classification of Diseases 10th Revision (ICD-10) by World Health Organization were selected as prototypes for this study. The good performance scores from experimental results indicate that this study can be used as guidance in developing support specifically on treatment plan in outpatient health care delivery.
User acceptance Continuous quality improvement Treatment equity
Shahriyah Nyak Saad Ali Ahmad Mahir Razali Azuraliza Abu Bakar Nur Riza Suradi
School of Mathematical Sciences,Faculty of Science and Technology, Universiti Kebangsaan Malaysia, M Centre for Artificial Intelligence Technology,Faculty of Information Science and Technology, Univers
国际会议
6th International Conference on Advanced Data Mining and Applications(第六届先进数据挖掘及应用国际会议 ADMA 2010)
重庆
英文
475-482
2010-11-19（万方平台首次上网日期，不代表论文的发表时间）