Afiq Izzudin A Rahim

@usm.my

Medical Lecturer and Public Health Physician
Universiti Sains Malaysia

Afiq Izzudin A Rahim


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https://researchid.co/afiqrahim
A public health physician by practise and a medical lecturer at Universiti Sains Malaysia. My interests are in health system management, health informatics, health technology, epidemiology, and disaster management.

EDUCATION

MB, BCH, BAO, LRCP & SI (RCSI)
MPH (USM)
DrPH (USM)

RESEARCH, TEACHING, or OTHER INTERESTS

Public Health, Environmental and Occupational Health, Health Informatics, Epidemiology, Health Information Management
11

Scopus Publications

386

Scholar Citations

9

Scholar h-index

8

Scholar i10-index

Scopus Publications

  • Challenges in delivering healthcare services among immigrants from Southeast Asia: A scoping review
    Medical Journal of Malaysia, 2026
  • The intersection of quality improvement, artificial intelligence and patient safety in healthcare—current applications, challenges and risks, and future directions: a scoping review
    Mohd Hanif Mohd Nawawi, Muhammad Solehuddin Ishak, Rizq Fazzali Abdul Raes, Ihsan Abdul Razak, Suhana Hasan, Afiq Izzudin A. Rahim
    Journal of Medical Artificial Intelligence, 2025
  • A scoping review of digital health applications for managing noncommunicable diseases in primary care post-pandemic: Lessons from the Western Pacific Region
    Muhammad Solehuddin Ishak, Rizq Fazzali Abdul Raes, Ihsan Abdul Razak, Mohd Hanif Mohd Nawawi, Suhana Hasan, et al.
    Malaysian Family Physician, 2025
    Introduction: The global rise of digital health is reshaping healthcare delivery and improving outcomes, especially for noncommunicable diseases (NCDs) post-pandemic. Guided by the World Health Organization (WHO) Global Strategy on Digital Health 2020–2025, this study examined digital health applications in Western Pacific Region (WPR) primary care, focusing on NCD management and related challenges. Methods: A scoping review following the Arksey and O’Malley framework and Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines was conducted. Using the PICO framework, studies on digital interventions in WPR primary care were identified through PubMed, Scopus, ScienceDirect, Web of Science and the Journal of Medical Internet Research (2022–2024). Eighteen studies were synthesized using the WHO digital health intervention and Health System Challenge frameworks. Results: The review included studies from Australia (n=10), Singapore (n=5), South Korea (n=1), and China (n=2), encompassing randomized, observational, qualitative, and pragmatic designs. Digital interventions—telehealth, mobile health (mHealth) and electronic health (eHealth)—targeted NCDs such as diabetes, mental health, and cardiovascular diseases, addressing information quality, acceptability, efficiency, cost, accountability, and equity. Conclusion: The scoping review identified several digital health interventions, predominantly telehealth, mHealth and eHealth, deployed across Australia, Singapore, South Korea and China for NCD management in primary care. The studies demonstrated improvements in information quality, acceptability and efficiency, while highlighting persistent barriers such as technology integration issues, data quality concerns and inequities.
  • PUBLIC HEALTH STRATEGIES FOR MANAGING MASS GATHERINGS AND INTERNATIONAL EVENTS: THE LANGKAWI INTERNATIONAL MARITIME AND AEROSPACE (LIMA) 2023 CASE STUDY
    Malaysian Journal of Public Health Medicine, 2025
  • Case Report: A Challenging Case of Tetanus Presenting with Headache
    Afiq Izzudin A. Rahim, Emir Afif Mohammad Azlan, Muhamad Ruslan Rahman, Nafiisah Mahmud Pathi, Mansor Ismail, Wan Aliaa Wan Sulaiman
    American Journal of Tropical Medicine and Hygiene, 2023
    Tetanus is a life-threatening infectious neurological condition that has become uncommon due to large-scale immunization campaigns. We describe a rare instance of generalized tetanus presenting with a headache on a tropical island in Malaysia. A 43-year-old woman presenting with headaches and generalized body weakness, which progressed into trismus and neck stiffness. Her medical history indicated a wound on the sole of her foot caused by shattered glass in an unhygienic area, but no tetanus prophylaxis had been administered. The patient was subsequently given immunoglobulin, tetanus toxoid, metronidazole, and sedatives in the recommended dosages. Her neurological condition improved remarkably, but she suffered blood pressure fluctuations due to dysautonomia. She was successfully discharged with complete recovery after 6 months of follow-up. The case demonstrates the significance of appropriate identification and care of tetanus, as well as the lethal effects of untreated wounds in vulnerable patients.
  • Hospital facebook reviews analysis using a machine learning sentiment analyzer and quality classifier
    Afiq Izzudin A. Rahim, Mohd Ismail Ibrahim, Sook-Ling Chua, Kamarul Imran Musa
    Healthcare Switzerland, 2021
    While experts have recognised the significance and necessity of social media integration in healthcare, no systematic method has been devised in Malaysia or Southeast Asia to include social media input into the hospital quality improvement process. The goal of this work is to explain how to develop a machine learning system for classifying Facebook reviews of public hospitals in Malaysia by using service quality (SERVQUAL) dimensions and sentiment analysis. We developed a Machine Learning Quality Classifier (MLQC) based on the SERVQUAL model and a Machine Learning Sentiment Analyzer (MLSA) by manually annotated multiple batches of randomly chosen reviews. Logistic regression (LR), naive Bayes (NB), support vector machine (SVM), and other methods were used to train the classifiers. The performance of each classifier was tested using 5-fold cross validation. For topic classification, the average F1-score was between 0.687 and 0.757 for all models. In a 5-fold cross validation of each SERVQUAL dimension and in sentiment analysis, SVM consistently outperformed other methods. The study demonstrates how to use supervised learning to automatically identify SERVQUAL domains and sentiments from patient experiences on a hospital’s Facebook page. Malaysian healthcare providers can gather and assess data on patient care via the use of these content analysis technology to improve hospital quality of care.
  • Patient satisfaction and hospital quality of care evaluation in malaysia using servqual and facebook
    Afiq Izzudin A. Rahim, Mohd Ismail Ibrahim, Kamarul Imran Musa, Sook-Ling Chua, Najib Majdi Yaacob
    Healthcare Switzerland, 2021
    Social media sites, dubbed patient online reviews (POR), have been proposed as new methods for assessing patient satisfaction and monitoring quality of care. However, the unstructured nature of POR data derived from social media creates a number of challenges. The objectives of this research were to identify service quality (SERVQUAL) dimensions automatically from hospital Facebook reviews using a machine learning classifier, and to examine their associations with patient dissatisfaction. From January 2017 to December 2019, empirical research was conducted in which POR were gathered from the official Facebook page of Malaysian public hospitals. To find SERVQUAL dimensions in POR, a machine learning topic classification utilising supervised learning was developed, and this study’s objective was established using logistic regression analysis. It was discovered that 73.5% of patients were satisfied with the public hospital service, whereas 26.5% were dissatisfied. SERVQUAL dimensions identified were 13.2% reviews of tangible, 68.9% of reliability, 6.8% of responsiveness, 19.5% of assurance, and 64.3% of empathy. After controlling for hospital variables, all SERVQUAL dimensions except tangible and assurance were shown to be significantly related with patient dissatisfaction (reliability, p < 0.001; responsiveness, p = 0.016; and empathy, p < 0.001). Rural hospitals had a higher probability of patient dissatisfaction (p < 0.001). Therefore, POR, assisted by machine learning technologies, provided a pragmatic and feasible way for capturing patient perceptions of care quality and supplementing conventional patient satisfaction surveys. The findings offer critical information that will assist healthcare authorities in capitalising on POR by monitoring and evaluating the quality of services in real time.
  • Assessing patient-perceived hospital service quality and sentiment in malaysian public hospitals using machine learning and facebook reviews
    Afiq Izzudin A. Rahim, Mohd Ismail Ibrahim, Kamarul Imran Musa, Sook-Ling Chua, Najib Majdi Yaacob
    International Journal of Environmental Research and Public Health, 2021
    Social media is emerging as a new avenue for hospitals and patients to solicit input on the quality of care. However, social media data is unstructured and enormous in volume. Moreover, no empirical research on the use of social media data and perceived hospital quality of care based on patient online reviews has been performed in Malaysia. The purpose of this study was to investigate the determinants of positive sentiment expressed in hospital Facebook reviews in Malaysia, as well as the association between hospital accreditation and sentiments expressed in Facebook reviews. From 2017 to 2019, we retrieved comments from 48 official public hospitals’ Facebook pages. We used machine learning to build a sentiment analyzer and service quality (SERVQUAL) classifier that automatically classifies the sentiment and SERVQUAL dimensions. We utilized logistic regression analysis to determine our goals. We evaluated a total of 1852 reviews and our machine learning sentiment analyzer detected 72.1% of positive reviews and 27.9% of negative reviews. We classified 240 reviews as tangible, 1257 reviews as trustworthy, 125 reviews as responsive, 356 reviews as assurance, and 1174 reviews as empathy using our machine learning SERVQUAL classifier. After adjusting for hospital characteristics, all SERVQUAL dimensions except Tangible were associated with positive sentiment. However, no significant relationship between hospital accreditation and online sentiment was discovered. Facebook reviews powered by machine learning algorithms provide valuable, real-time data that may be missed by traditional hospital quality assessments. Additionally, online patient reviews offer a hitherto untapped indication of quality that may benefit all healthcare stakeholders. Our results confirm prior studies and support the use of Facebook reviews as an adjunct method for assessing the quality of hospital services in Malaysia.
  • Facebook reviews as a supplemental tool for hospital patient satisfaction and its relationship with hospital accreditation in malaysia
    Afiq Izzudin A. Rahim, Mohd Ismail Ibrahim, Kamarul Imran Musa, Sook-Ling Chua
    International Journal of Environmental Research and Public Health, 2021
    Patient satisfaction is one indicator used to assess the impact of accreditation on patient care. However, traditional patient satisfaction surveys have a few disadvantages, and some researchers have suggested that social media be used in their place. Social media usage is gaining popularity in healthcare organizations, but there is still a paucity of data to support it. The purpose of this study was to determine the association between online reviews and hospital patient satisfaction and the relationship between online reviews and hospital accreditation. We used a cross-sectional design with data acquired from the official Facebook pages of 48 Malaysian public hospitals, 25 of which are accredited. We collected all patient comments from Facebook reviews of those hospitals between 2018 and 2019. Spearman’s correlation and logistic regression were used to evaluate the data. There was a significant and moderate correlation between hospital patient satisfaction and online reviews. Patient satisfaction was closely connected to urban location, tertiary hospital, and previous Facebook ratings. However, hospital accreditation was not found to be significantly associated with online reports of patient satisfaction. This groundbreaking study demonstrates how Facebook reviews can assist hospital administrators in monitoring their institutions’ quality of care in real time.
  • Factors associated with poor perceptions of graphic warning signs (gws) on cigarette package among adult smokers in kelantan
    Malaysian Journal of Medicine and Health Sciences, 2020
  • Health information engagement factors in Malaysia: A content analysis of facebook use by the ministry of health in 2016 and 2017
    Afiq A. Rahim, Mohd Ibrahim, Faizul A. Salim, Mohd Ariffin
    International Journal of Environmental Research and Public Health, 2019

RECENT SCHOLAR PUBLICATIONS

  • Development and Comparative Analysis of Predictive Length of Stay Models Using Machine Learning in Malaysian Tertiary Hospitals
    S Hasan, EKM Hashim, AIA Rahim, MI Ibrahim, Z Zakaria
    2026
  • Challenges in delivering healthcare services among immigrants from Southeast Asia: A scoping review
    MPH Azulaikha Alias, IAM Idrus
    Med J Malaysia 81 (1), 163 , 2026
    2026
  • A scoping review of digital health applications for managing noncommunicable diseases in primary care post-pandemic: Lessons from the Western Pacific Region
    MS Ishak, RFA Raes, IA Razak, MHM Nawawi, S Hasan, AIA Rahim
    Malaysian Family Physician: the Official Journal of the Academy of Family … , 2025
    2025
  • Translation and validation of the malay doctor–patient communication questionnaire: a cross-sectional study among patients receiving hemodialysis in Kelantan, Malaysia
    AFF Ab Aziz, MI Ibrahim, NM Yaacob, AI A Rahim
    Healthcare 13 (16), 2037 , 2025
    2025
    Citations: 1
  • PUBLIC HEALTH STRATEGIES FOR MANAGING MASS GATHERINGS AND INTERNATIONAL EVENTS: A LANGKAWI INTERNATIONAL MARITIME AND AEROSPACE (LIMA) 2023 CASE
    AIA Rahim, NM Pathi, MFM Marzuki, AHA Shushami, TW Leong, R Omar, ...
    Malaysian Journal of Public Health Medicine 25 (1), 115-127 , 2025
    2025
  • The intersection of quality improvement, artificial intelligence and patient safety in healthcare—current applications, challenges and risks, and future directions: a scoping …
    MHM Nawawi, MS Ishak, RFA Raes, IA Razak, S Hasan, AIA Rahim
    Journal of Medical Artificial Intelligence 8, 57 , 2025
    2025
    Citations: 4
  • Silent Diabetes: Key Risk Factors Among the Low-Income Population of Langkawi Island, Kedah, Malaysia (2022-2023)
    SAA Kamarudin, AIA Rahim, MSM Shueib, M Ismail, AIA Rahim
    Cureus 16 (10) , 2024
    2024
  • Case Report: A Challenging Case of Tetanus Presenting with Headache
    AIA Rahim, EAM Azlan, MR Rahman, NM Pathi, M Ismail, WAW Sulaiman
    The American Journal of Tropical Medicine and Hygiene 109 (6), 1242 , 2023
    2023
    Citations: 1
  • Knowledge, attitude, practice and perceived barriers on palliative care pain management among the healthcare providers: A single centre study
    NAM Azmi, LA Mukmin, F Taib, AIA Rahim, S Ali
    Asian Journal of Medicine and Biomedicine 6 (2), 154-163 , 2022
    2022
    Citations: 3
  • Hospital facebook reviews analysis using a machine learning sentiment analyzer and quality classifier
    AIA Rahim, MI Ibrahim, SL Chua, KI Musa
    Healthcare 9 (12), 1679 , 2021
    2021
    Citations: 21
  • Facebook Reviews as a Supplemental Tool for Hospital Patient Satisfaction and Its Relationship with Hospital Accreditation in Malaysia: A Nationwide Study
    NMY Afiq Izzudin A Rahim, Mohd Ismail Ibrahim, Kamarul Imran Musa, Sook-Ling ...
    14th National Conference for Clinical : Medical Journal of Malaysia 76 (5), 16 , 2021
    2021
  • Patient satisfaction and hospital quality of care evaluation in malaysia using servqual and facebook
    AIA Rahim, MI Ibrahim, KI Musa, SL Chua, NM Yaacob
    Healthcare 9 (10), 1369 , 2021
    2021
    Citations: 95
  • A, Ibrahim MI, Musa KI, Chua SL, Yaacob NM. Assessing patient-perceived hospital service quality and sentiment in malaysian public hospitals using machine learning and Facebook …
    AI Rahim
    Int J Environ Res Public Health 18 (9912), 10.3390 , 2021
    2021
    Citations: 3
  • Assessing patient-perceived hospital service quality and sentiment in malaysian public hospitals using machine learning and facebook reviews
    AI A. Rahim, MI Ibrahim, KI Musa, SL Chua, NM Yaacob
    International journal of environmental research and public health 18 (18), 9912 , 2021
    2021
    Citations: 57
  • Facebook reviews as a supplemental tool for hospital patient satisfaction and its relationship with hospital accreditation in Malaysia
    AI A. Rahim, MI Ibrahim, KI Musa, SL Chua
    International Journal of Environmental Research and Public Health 18 (14), 7454 , 2021
    2021
    Citations: 33
  • An Epidemiological Analysis of COVID-19 cases from Jan to July 2020 in Kelantan, Malaysia
    HM Hatta, N Fuzi, NDM Zin, AIA Rahim, NM Zakria, S Sulaiman, ...
    Ulum Islamiyyah 33, 149-165 , 2021
    2021
    Citations: 2
  • Patient satisfaction and hospital quality of care evaluation in Malaysia using SERVQUAL and Facebook. Healthcare, 9 (10), 1369
    AIA Rahim, MI Ibrahim, KI Musa, SL Chua, NM Yaacob
    2021
    Citations: 12
  • Hospital Facebook Reviews Analysis Using a Machine Learning Sentiment Analyzer and Quality Classifier. Healthcare 2021, 9, 1679
    A Rahim, M Ibrahim, S Chua, K Musa
    s Note: MDPI stays neu-tral with regard to jurisdictional claims in … , 2021
    2021
    Citations: 1
  • Factors Associated with Poor Perceptions of Graphic Warning Signs (GWS) on Cigarette Package among Adult Smokers in Kelantan.
    AIA Rahim, MI Ibrahim
    Malaysian Journal of Medicine & Health Sciences 16 (3) , 2020
    2020
  • Health information engagement factors in Malaysia: a content analysis of Facebook use by the Ministry of Health in 2016 and 2017
    AI A. Rahim, MI Ibrahim, FN A. Salim, MAI Ariffin
    International journal of environmental research and public health 16 (4), 591 , 2019
    2019
    Citations: 98

MOST CITED SCHOLAR PUBLICATIONS

  • Health information engagement factors in Malaysia: a content analysis of Facebook use by the Ministry of Health in 2016 and 2017
    AI A. Rahim, MI Ibrahim, FN A. Salim, MAI Ariffin
    International journal of environmental research and public health 16 (4), 591 , 2019
    2019
    Citations: 98
  • Patient satisfaction and hospital quality of care evaluation in malaysia using servqual and facebook
    AIA Rahim, MI Ibrahim, KI Musa, SL Chua, NM Yaacob
    Healthcare 9 (10), 1369 , 2021
    2021
    Citations: 95
  • Assessing patient-perceived hospital service quality and sentiment in malaysian public hospitals using machine learning and facebook reviews
    AI A. Rahim, MI Ibrahim, KI Musa, SL Chua, NM Yaacob
    International journal of environmental research and public health 18 (18), 9912 , 2021
    2021
    Citations: 57
  • Facebook reviews as a supplemental tool for hospital patient satisfaction and its relationship with hospital accreditation in Malaysia
    AI A. Rahim, MI Ibrahim, KI Musa, SL Chua
    International Journal of Environmental Research and Public Health 18 (14), 7454 , 2021
    2021
    Citations: 33
  • Hospital facebook reviews analysis using a machine learning sentiment analyzer and quality classifier
    AIA Rahim, MI Ibrahim, SL Chua, KI Musa
    Healthcare 9 (12), 1679 , 2021
    2021
    Citations: 21
  • Managerial perspectives on success and failure of post-acquisition processes
    KM Bijlsma-Frankema, E Prins, B Weber, A Rahim, RT Golembiewski
    Current topics in management 4, 155-179 , 1999
    1999
    Citations: 18
  • Changing trends in incidence and indications of caesarean section.
    A Khan, T Ghani, A Rahim, MM Rahman
    Mymensingh medical journal: MMJ 23 (1), 52-55 , 2014
    2014
    Citations: 17
  • Patient satisfaction and hospital quality of care evaluation in Malaysia using SERVQUAL and Facebook. Healthcare, 9 (10), 1369
    AIA Rahim, MI Ibrahim, KI Musa, SL Chua, NM Yaacob
    2021
    Citations: 12
  • The psychology of compliance: revisiting the notion of a psychological contract
    A Carr, A Rahim, R Golembiewski, C Lundberg
    Current topics in management 1, 69-83 , 1996
    1996
    Citations: 9
  • Finite Element Modelling of Structures Subjected to Thermal Loading
    A Hisham, GH Mahmoud, NE Nasr, A Mohamed, A Rahim
    IOSR J. Mech. Civ. Eng 15 , 2018
    2018
    Citations: 5
  • Keep off! Private! Enter at your own risk!(De-) Constructing the organization as private sphere
    A Kersten, M Sidky, A Rahim, R Golembiewski
    Current Topics in Management 2, 287-304 , 1997
    1997
    Citations: 5
  • The intersection of quality improvement, artificial intelligence and patient safety in healthcare—current applications, challenges and risks, and future directions: a scoping …
    MHM Nawawi, MS Ishak, RFA Raes, IA Razak, S Hasan, AIA Rahim
    Journal of Medical Artificial Intelligence 8, 57 , 2025
    2025
    Citations: 4
  • Knowledge, attitude, practice and perceived barriers on palliative care pain management among the healthcare providers: A single centre study
    NAM Azmi, LA Mukmin, F Taib, AIA Rahim, S Ali
    Asian Journal of Medicine and Biomedicine 6 (2), 154-163 , 2022
    2022
    Citations: 3
  • A, Ibrahim MI, Musa KI, Chua SL, Yaacob NM. Assessing patient-perceived hospital service quality and sentiment in malaysian public hospitals using machine learning and Facebook …
    AI Rahim
    Int J Environ Res Public Health 18 (9912), 10.3390 , 2021
    2021
    Citations: 3
  • An Epidemiological Analysis of COVID-19 cases from Jan to July 2020 in Kelantan, Malaysia
    HM Hatta, N Fuzi, NDM Zin, AIA Rahim, NM Zakria, S Sulaiman, ...
    Ulum Islamiyyah 33, 149-165 , 2021
    2021
    Citations: 2
  • Translation and validation of the malay doctor–patient communication questionnaire: a cross-sectional study among patients receiving hemodialysis in Kelantan, Malaysia
    AFF Ab Aziz, MI Ibrahim, NM Yaacob, AI A Rahim
    Healthcare 13 (16), 2037 , 2025
    2025
    Citations: 1
  • Case Report: A Challenging Case of Tetanus Presenting with Headache
    AIA Rahim, EAM Azlan, MR Rahman, NM Pathi, M Ismail, WAW Sulaiman
    The American Journal of Tropical Medicine and Hygiene 109 (6), 1242 , 2023
    2023
    Citations: 1
  • Hospital Facebook Reviews Analysis Using a Machine Learning Sentiment Analyzer and Quality Classifier. Healthcare 2021, 9, 1679
    A Rahim, M Ibrahim, S Chua, K Musa
    s Note: MDPI stays neu-tral with regard to jurisdictional claims in … , 2021
    2021
    Citations: 1
  • Interactive Implementation of Axial Stiffness Reduction Factors in Thermal Analysis of Multistory Buildings
    A Hisham, GH Mahmoud, NE Nasr, A Mohamed, A Rahim
    IOSR J. Mech. Civ. Eng 16 , 2019
    2019
    Citations: 1
  • Development and Comparative Analysis of Predictive Length of Stay Models Using Machine Learning in Malaysian Tertiary Hospitals
    S Hasan, EKM Hashim, AIA Rahim, MI Ibrahim, Z Zakaria
    2026

CONSULTANCY

Medical Statistics, Biostatistics, Machine Learning and AI Applications in Healthcare, Digital Health Promotion, Health Business & Management

Industry, Institute, or Organisation Collaboration

MOH of Malaysia
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