https://he03.tci-thaijo.org/index.php/jtmi/issue/feed Journal of the Thai Medical Informatics Association 2022-10-22T16:42:58+07:00 Siriwan Suebnukarn siriwan.suebnukarn@gmail.com Open Journal Systems <p class="p1">The Journal of the Thai Medical Informatics Association (J Thai Med Inform Assoc; JTMI) aims to promote the fundamental understanding of healthcare informatics and advance knowledge and application systems in healthcare fields. It covers high-quality original research articles, reviews, case reports, and communications in the area of design, development, implementation, and evaluation of information systems in healthcare fields. It also includes health policy, education, quality, managerial, cognitive and behavioral aspects of healthcare informatics as well as health information infrastructure such as standardization, security, biomedical engineering, and bioinformatics.</p> https://he03.tci-thaijo.org/index.php/jtmi/article/view/478 Pseudonymization for the Protection of Personal Data Necessary to Conduct Corporate Transactions Using Encryption and Tokenization Methods 2022-10-22T15:59:14+07:00 Nontawatt Saraman surasak.mu@spu.ac.th Surasak Mungsing mu@spu.ac.th <p>Personal data is any information that can be directly or indirectly linked to an individual. It is the information that is necessary to carry out the transaction. The best way to protect personal information is to make that information become anonymous without the identity of the person anymore and cannot be reversed regardless of any additional information. This article objective is to present presents methods for creating pseudonymisation for protecting personal information by means of encryption and tokenization.&nbsp;</p> 2022-10-22T00:00:00+07:00 Copyright (c) 2022 https://he03.tci-thaijo.org/index.php/jtmi/article/view/479 Analysis of Risk Factors and Severity of Osteoarthritis from Risk Behaviors to Osteoarthritis Using Data Mining Techniques 2022-10-22T16:07:16+07:00 Benyapha Srisawang surasak.mu@spu.ac.th Surasak Mungsing surasak.mu@spu.ac.th <p>The purpose of this research was to study and analyze the data of those at risk of osteoarthritis and the severity of those suffering from osteoarthritis from behaviors at risk of developing osteoarthritis. Data were collected from a sample of 151 patients with osteoarthritis of the knee and a sample of 113 without osteoarthritis. The data used in the analysis were collected between March and June 2021 and were analyzed using four data mining techniques: Decision tree (J48), Naïve bayes, SMO and Neural network to find correlation between behavioral data and knee pain levels in people with osteoarthritis The results showed that the Naïve bayes algorithm was able to generate the most efficient models with an accuracy of 95.8115 %</p> 2022-10-22T00:00:00+07:00 Copyright (c) 2022 https://he03.tci-thaijo.org/index.php/jtmi/article/view/480 Rebalancing Clinical Data with Probabilistic Random Oversampling 2022-10-22T16:12:29+07:00 Thanakorn Pasangthien boonsit.yim@mahidol.ac.th Boonsit Yimwadsana boonsit.yim@mahidol.ac.th <p>Data analysis has become a popular tool to obtain knowledge and create useful application for various business areas. However, often, this is not the case for healthcare industry. This is because the data collected by hospitals and health centers are often bias. Either most data consist of similar patients or most data sets do not contain sufficiently interesting disease data. As a result, prediction and classification on healthcare data usually suffers from the problem of data bias. Since most machine learning algorithms assume sufficiently balanced data which essentially based on general statistics, the prediction performance of the algorithms is largely affected by this bias. There are several well-known methods which offer solution to this data imbalanced problem such as SMOTE and random oversampling. However, most of them do not make use of knowledge hidden in the data. We propose probability model-based random oversampling technique which makes use of the knowledge (probability distribution) of the data so that we can perform random oversampling better than existing methods. The data generated will be based on the probability models of the data portion we are interested in. This will reduce the chance of generating a rigid or strict sample of data which can strongly alter the statistical information of the data in the experiment. We tested our method using widely known data set such as the UCI diabetes and beast cancer data set. We found that our technique outperforms SMOTE and random oversampling technique in terms of sensitivity and specificity performance.</p> 2022-10-22T00:00:00+07:00 Copyright (c) 2022 https://he03.tci-thaijo.org/index.php/jtmi/article/view/481 A Survey of Literature and Case Studies to Summarize Factors in Selecting a Cloud Service Provider for Healthcare Organizations in Thailand 2022-10-22T16:21:07+07:00 Songsak Rongviriyapanich songsak_r@sci.tu.ac.th <p>Cloud has gained interest in being used in building information systems for healthcare agencies around the world, including Thailand. However, the transition to the cloud requires consideration of many factors including security and organizational readiness. In order to make the information system of public health agencies in the cloud secure and safe in accordance with the laws of Thailand. This paper explores the literature related to cloud safety standards and cloud use for public health agencies in order to summarize recommendations for cloud adoption approaches for public health agencies in Thailand.</p> 2022-10-22T00:00:00+07:00 Copyright (c) 2022 https://he03.tci-thaijo.org/index.php/jtmi/article/view/482 Data Literacy for Staff in Healthcare and Medical Industry 2022-10-22T16:25:17+07:00 Boonsit Yimwadsana boonsit.yim@mahidol.ac.th <p>Companies today collect a large amount of data thanks to the advancement in information technology and business process improvement. However, the collected data are often not used effectively. This is due to the lack of understanding about the benefits of data. Therefore, there is a worldwide effort led by OECD to push companies to use data more effectively and efficiently in order to improve business operation. Everyone now knows about the benefit of data, however, companies still feel that they are not making the best use of data they have. This problem is even more severe in healthcare and medical institutions since there are an immense amount of a variety of data that flow into the system every second. In this paper, we show that the staff in healthcare institutions can cope with this problem using the concept of research methodology which most staff do not have since it was not usually offered as a required course in undergraduate level. Research methodology covers all areas of data literacy. We identify that research methodology could only be provided through project-based or interactive learning and it cannot be learnt in a short period of time. From our findings, we also found that work environment greatly affected the ability to apply data literacy concept greatly as low-level staff did not have the opportunity to take part in the business problem establishment process. This discourage staff from learning and using data literacy concept. We also propose that companies should allow staff in different departments to have autonomy to conduct their own research and improvement strategy so that they can fully see the need of data literacy and apply it successfully.</p> 2022-10-22T00:00:00+07:00 Copyright (c) 2022 https://he03.tci-thaijo.org/index.php/jtmi/article/view/483 The Characteristics of Hospital Logistics in Thailand 2022-10-22T16:29:41+07:00 Thitarree Sirisrisornchai thitarree.sir@mahidol.ac.th <p>Hospitals have utilised logistics management as a critical management tool. The efficient logistics management will support hospital to be able to save life in time, reduce resources utilization, reduce time, reduce cost, reduce mistake, reduce waste. So, logistics management can lead organization to quality development and add value in patients’ treatment.</p> <p>The contents in this article derived from reviewing literatures in logistics management in healthcare organisations in order to study logistics’ characteristics, the differences between logistics and supply chain management, logistics dimensions, critical components and efficiencies of logistics in healthcare organizations (accuracy, time reduction and cost reduction).</p> <p>This study is qualitative research. Secondary data is analyzed by using Taxonomy and Typology techniques to pursue Domain Analysis and identify Pattern Matching, and then, critique the contents. The sample of this study is 20 research articles regarding logistics management in hospitals.</p> <p>The results from the study found that characteristics and situation of hospital logistics operation such as high cost of raw materials, various medical suppliers need special care (temperature control, UV protection, humidity control), high service cost, congestion in hospital, long waiting time, utilizing technologies are not in full capability, the lack of logistics knowledge of staff, the lack of in-depth cooperation with all stakeholders. All these result in emerging opportunities for further increasing efficiency in hospital logistics management. Based on literature review and the outcomes of the study, this study critiques characteristics of logistics, concludes procedures of hospital logistics management, proposes existing logistics system analysis form for communication and development, and synthesizes efficient logistics factors under the context of hospital (economics of scale, economics of scope, economics of density, economics of transportation round and economics of workforce utilisation).</p> 2022-10-22T00:00:00+07:00 Copyright (c) 2022