Volume 9, Issue 2, September 2014, Pages 268–284
Hossein Ahmadi1, Mahdi Darvishi2, Mehrbakhsh Nilashi3, Alireza Almaee4, Othman Ibrahim5, Ali Hossein Zolghadri6, Mojtaba Alizadeh7, and Mohammadreza Farahmand8
1 Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia
2 Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia
3 Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia
4 Organization of Technical and Vocational Training, Lahijan, Guilan, Iran
5 Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia
6 Islamic Azad University Qeshm Branch, Qeshm, Iran
7 Malaysian-Japan International Institute of Technology Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia
8 Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia
Original language: English
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Using Electronic Medical Records (EMRs) has a great possibility for rising physician's performance in their daily work which improves quality, safety and efficiency in healthcare that are slowly being adopted throughout the world. The adoption of EMRs as a new technology in healthcare system is an important issue which has to be scrutinized as well. In physician practices, the rate of EMRs adoption has been slow and restricted in spite of the cost savings through lower administrative costs and medical errors related to EMR systems. Hence, this research is conducted to identify, categorize, and analyze Meso-level dimension which introduced by [27], for the adoption of EMRs in the healthcare context. To collect data, Likert-based and pairwise questionnaires were designed and distributed among the public experts and physicians healthcare organizations. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS) and Fuzzy Analytic Hierarchy Process (F-AHP) was applied involves in quantitative approach in the ranking and weighting of the factors presented in Meso-level dimension framework. As a result, in this study, we develop a Multi Criteria Decision Making (MCDM) framework for healthcare industry improvement and adoption of EMR. The purpose of ranking and weighting using the F-TOPSIS and F-AHP is to inspect which factors are most imperative in EMRs adoption among primary care physicians. Performing F-TOPSIS and F-AHP is as novelty methods in this study for identifying the critical factors of EMRs adoption to assist healthcare organizations specifically hospitals setting in pursuing their key users' behavior towards accepting of this new technology. We find that seven factors, namely time investment, screen/room, hybrid system, planning, resource training, workflow, and weight, are the most influential criteria and strongest drivers in the adoption of EMR in Malaysia's primary care setting.
Author Keywords: EMRS, Adoption, Fuzzy TOPSIS, Fuzzy AHP, Meso-Level Adoption Factors, HIS.
Hossein Ahmadi1, Mahdi Darvishi2, Mehrbakhsh Nilashi3, Alireza Almaee4, Othman Ibrahim5, Ali Hossein Zolghadri6, Mojtaba Alizadeh7, and Mohammadreza Farahmand8
1 Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia
2 Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia
3 Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia
4 Organization of Technical and Vocational Training, Lahijan, Guilan, Iran
5 Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia
6 Islamic Azad University Qeshm Branch, Qeshm, Iran
7 Malaysian-Japan International Institute of Technology Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia
8 Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia
Original language: English
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Using Electronic Medical Records (EMRs) has a great possibility for rising physician's performance in their daily work which improves quality, safety and efficiency in healthcare that are slowly being adopted throughout the world. The adoption of EMRs as a new technology in healthcare system is an important issue which has to be scrutinized as well. In physician practices, the rate of EMRs adoption has been slow and restricted in spite of the cost savings through lower administrative costs and medical errors related to EMR systems. Hence, this research is conducted to identify, categorize, and analyze Meso-level dimension which introduced by [27], for the adoption of EMRs in the healthcare context. To collect data, Likert-based and pairwise questionnaires were designed and distributed among the public experts and physicians healthcare organizations. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS) and Fuzzy Analytic Hierarchy Process (F-AHP) was applied involves in quantitative approach in the ranking and weighting of the factors presented in Meso-level dimension framework. As a result, in this study, we develop a Multi Criteria Decision Making (MCDM) framework for healthcare industry improvement and adoption of EMR. The purpose of ranking and weighting using the F-TOPSIS and F-AHP is to inspect which factors are most imperative in EMRs adoption among primary care physicians. Performing F-TOPSIS and F-AHP is as novelty methods in this study for identifying the critical factors of EMRs adoption to assist healthcare organizations specifically hospitals setting in pursuing their key users' behavior towards accepting of this new technology. We find that seven factors, namely time investment, screen/room, hybrid system, planning, resource training, workflow, and weight, are the most influential criteria and strongest drivers in the adoption of EMR in Malaysia's primary care setting.
Author Keywords: EMRS, Adoption, Fuzzy TOPSIS, Fuzzy AHP, Meso-Level Adoption Factors, HIS.
How to Cite this Article
Hossein Ahmadi, Mahdi Darvishi, Mehrbakhsh Nilashi, Alireza Almaee, Othman Ibrahim, Ali Hossein Zolghadri, Mojtaba Alizadeh, and Mohammadreza Farahmand, “Evaluating the Critical Factors for Electronic Medical Record Adoption Using Fuzzy Approaches,” International Journal of Innovation and Scientific Research, vol. 9, no. 2, pp. 268–284, September 2014.
