A study on patient data sharing acceptability among Malaysian with data mining techniques
The Coronavirus Disease (Covid-19) is a major stress test for the healthcare sector. Malaysia is one of the countries that quickly adopted telehealth in a large-scale. Sharing personal information and health records with healthcare providers are required in telehealth. During interactive video confe...
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| Format: | Final Year Project / Dissertation / Thesis |
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2023
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| Online Access: | http://eprints.utar.edu.my/5810/ http://eprints.utar.edu.my/5810/1/BI_1801629_Final_LEE_XIN_YING.pdf |
| _version_ | 1848886510774910976 |
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| author | Lee, Xin Ying |
| author_facet | Lee, Xin Ying |
| author_sort | Lee, Xin Ying |
| building | UTAR Institutional Repository |
| collection | Online Access |
| description | The Coronavirus Disease (Covid-19) is a major stress test for the healthcare sector. Malaysia is one of the countries that quickly adopted telehealth in a large-scale. Sharing personal information and health records with healthcare providers are required in telehealth. During interactive video conference, patient data transmission happens at all sites. Growing interest and adoption in telemedicine bring cybersecurity pressure to the healthcare industry. Legal and ethical aspects are imperative in telemedicine. In Malaysia, Telemedicine Act 1997 has been promogulated and passed but is yet to be enforced. Patients must acknowledge the risks of private health information being exposed. Patient acceptability is essential to propel telehealth quality and adoption. This study aims to explore patient data sharing acceptability among Malaysian using data mining techniques. This study may lay a foundation for all authorities, highlighting current ambiguity and implementing effective interventions. Ultimately, state-of-the-art healthcare services could be accessed and delivered. Actual execution of questionnaire distribution yielded 162 respondents. Data analysis and data mining were conducted on survey results with SPSS and Python for closed-ended questions and open-ended questions respectively. Latent Dirichlet Allocation (LDA) topic modeling alongside term frequencyinverse document frequency (TF-IDF) score are used for analyzing unstructured texts collected from open-ended questions which allows true insights collection. More than 61% of respondents responded willing to disclose information on family contacts, phone numbers, email addresses, and geolocation. Additionally, more than 58% of respondents were willing to provide their medical prescription, medical history, and diagnostic results. Age, work or study field, income and marital status were found to be associated with data sharing attitude. Malaysians expressed privacy breach concerns and worried about the digital literacy of the elderly. Information and Technology (IT) industry received the lowest level of trust. Data privacy, transparent communication and education were suggested ways to enhance data sharing willingness. |
| first_indexed | 2025-11-15T19:39:39Z |
| format | Final Year Project / Dissertation / Thesis |
| id | utar-5810 |
| institution | Universiti Tunku Abdul Rahman |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:39:39Z |
| publishDate | 2023 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utar-58102023-08-08T12:14:49Z A study on patient data sharing acceptability among Malaysian with data mining techniques Lee, Xin Ying R Medicine (General) The Coronavirus Disease (Covid-19) is a major stress test for the healthcare sector. Malaysia is one of the countries that quickly adopted telehealth in a large-scale. Sharing personal information and health records with healthcare providers are required in telehealth. During interactive video conference, patient data transmission happens at all sites. Growing interest and adoption in telemedicine bring cybersecurity pressure to the healthcare industry. Legal and ethical aspects are imperative in telemedicine. In Malaysia, Telemedicine Act 1997 has been promogulated and passed but is yet to be enforced. Patients must acknowledge the risks of private health information being exposed. Patient acceptability is essential to propel telehealth quality and adoption. This study aims to explore patient data sharing acceptability among Malaysian using data mining techniques. This study may lay a foundation for all authorities, highlighting current ambiguity and implementing effective interventions. Ultimately, state-of-the-art healthcare services could be accessed and delivered. Actual execution of questionnaire distribution yielded 162 respondents. Data analysis and data mining were conducted on survey results with SPSS and Python for closed-ended questions and open-ended questions respectively. Latent Dirichlet Allocation (LDA) topic modeling alongside term frequencyinverse document frequency (TF-IDF) score are used for analyzing unstructured texts collected from open-ended questions which allows true insights collection. More than 61% of respondents responded willing to disclose information on family contacts, phone numbers, email addresses, and geolocation. Additionally, more than 58% of respondents were willing to provide their medical prescription, medical history, and diagnostic results. Age, work or study field, income and marital status were found to be associated with data sharing attitude. Malaysians expressed privacy breach concerns and worried about the digital literacy of the elderly. Information and Technology (IT) industry received the lowest level of trust. Data privacy, transparent communication and education were suggested ways to enhance data sharing willingness. 2023 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/5810/1/BI_1801629_Final_LEE_XIN_YING.pdf Lee, Xin Ying (2023) A study on patient data sharing acceptability among Malaysian with data mining techniques. Final Year Project, UTAR. http://eprints.utar.edu.my/5810/ |
| spellingShingle | R Medicine (General) Lee, Xin Ying A study on patient data sharing acceptability among Malaysian with data mining techniques |
| title | A study on patient data sharing acceptability among Malaysian with data mining techniques |
| title_full | A study on patient data sharing acceptability among Malaysian with data mining techniques |
| title_fullStr | A study on patient data sharing acceptability among Malaysian with data mining techniques |
| title_full_unstemmed | A study on patient data sharing acceptability among Malaysian with data mining techniques |
| title_short | A study on patient data sharing acceptability among Malaysian with data mining techniques |
| title_sort | study on patient data sharing acceptability among malaysian with data mining techniques |
| topic | R Medicine (General) |
| url | http://eprints.utar.edu.my/5810/ http://eprints.utar.edu.my/5810/1/BI_1801629_Final_LEE_XIN_YING.pdf |