Developing treatment plan support in outpatient health care delivery with decision trees technique

  • Authors:

  • Shahriyah Nyak Saad Ali;Ahmad Mahir Razali;Azuraliza Abu Bakar;Nur Riza Suradi

  • Affiliations:

  • School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Malaysia;School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Malaysia;Centre for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Malaysia;School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Malaysia

  • Venue:
  • ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
  • Year:
  • 2010

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Abstract

This paper presents treatment plan support (TPS) development with the aim to support treatment decision making for physicians during outpatientcare 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: patient's 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.