A smart medication recommendation model for the electronic prescription

Shabbir Syed-Abdul; Alex Nguyen; Frank Huang; Wen-Shan Jian; Usman Iqbal; Vivian Yang; Min-Huei Hsu; Yu-Chuan Li

doi:10.1016/j.cmpb.2014.06.019

A smart medication recommendation model for the electronic prescription

Comput Methods Programs Biomed. 2014 Nov;117(2):218-24. doi: 10.1016/j.cmpb.2014.06.019. Epub 2014 Jul 9.

Authors

Shabbir Syed-Abdul¹, Alex Nguyen², Frank Huang³, Wen-Shan Jian⁴, Usman Iqbal⁵, Vivian Yang⁶, Min-Huei Hsu⁷, Yu-Chuan Li⁸

Affiliations

¹ Taipei Medical University, College of Medical Science and Technology, Graduate Institute of Biomedical Informatics, Taiwan. Electronic address: drshabbir786@gmail.com.
² Taipei Medical University, College of Medical Science and Technology, Graduate Institute of Biomedical Informatics, Taiwan. Electronic address: alexnthhp@gmail.com.
³ Taipei Medical University, College of Medical Science and Technology, Graduate Institute of Biomedical Informatics, Taiwan. Electronic address: frank0202@gmail.com.
⁴ Taipei Medical University, School of Health Care Administration, Taiwan. Electronic address: jj@tmu.edu.tw.
⁵ Taipei Medical University, College of Medical Science and Technology, Graduate Institute of Biomedical Informatics, Taiwan. Electronic address: usman.iqbal85@gmail.com.
⁶ College of Medical Science and Technology, Institute of Biomedical Informatics, Taiwan. Electronic address: vyang@tmu.edu.tw.
⁷ Taipei Medical University, College of Medical Science and Technology, Graduate Institute of Biomedical Informatics, Taiwan. Electronic address: 701056@gmail.com.
⁸ Taipei Medical University, College of Medical Science and Technology, Graduate Institute of Biomedical Informatics, Taiwan. Electronic address: jaak88@gmail.com.

PMID: 25092226
DOI: 10.1016/j.cmpb.2014.06.019

Abstract

Background: The report from the Institute of Medicine, To Err Is Human: Building a Safer Health System in 1999 drew a special attention towards preventable medical errors and patient safety. The American Reinvestment and Recovery Act of 2009 and federal criteria of 'Meaningful use' stage 1 mandated e-prescribing to be used by eligible providers in order to access Medicaid and Medicare incentive payments. Inappropriate prescribing has been identified as a preventable cause of at least 20% of drug-related adverse events. A few studies reported system-related errors and have offered targeted recommendations on improving and enhancing e-prescribing system.

Objective: This study aims to enhance efficiency of the e-prescribing system by shortening the medication list, reducing the risk of inappropriate selection of medication, as well as in reducing the prescribing time of physicians.

Method: 103.48 million prescriptions from Taiwan's national health insurance claim data were used to compute Diagnosis-Medication association. Furthermore, 100,000 prescriptions were randomly selected to develop a smart medication recommendation model by using association rules of data mining.

Results and conclusion: The important contribution of this model is to introduce a new concept called Mean Prescription Rank (MPR) of prescriptions and Coverage Rate (CR) of prescriptions. A proactive medication list (PML) was computed using MPR and CR. With this model the medication drop-down menu is significantly shortened, thereby reducing medication selection errors and prescription times. The physicians will still select relevant medications even in the case of inappropriate (unintentional) selection.

Keywords: Diagnosis-Medication association; Inappropriate prescription; Medications; NHI database; Smart medication recommendation model.

MeSH terms

Adverse Drug Reaction Reporting Systems / organization & administration*
Clinical Pharmacy Information Systems / organization & administration*
Decision Support Systems, Clinical / organization & administration*
Decision Support Techniques*
Drug Therapy, Computer-Assisted / methods
Electronic Prescribing*
Medical Order Entry Systems / organization & administration*
Medical Records Systems, Computerized / organization & administration*
Medication Errors / prevention & control
Taiwan