As our technology improves and modernizes, so does our healthcare. But despite this, Malaysia is still drastically behind its neighbours when it comes to detecting cancer efficiently. The University Malaya Medical Centre conducted four projects with the aim of modernizing and digitizing its cancer care. By applying machine-learning, AI-based systems and other digital systems to our healthcare, will be able to better detect and treat cancer and other non-communicable diseases and thus reduce our premature mortality rates.
Image by maleni ferrari from Pixabay
Our world is becoming more modernized as various aspects of life are digitized or becoming technology-dependent. Malaysia is no exception; as the country slowly undergoes technological progression, we must reflect upon the enormous challenge in improving cancer outcomes in this nation. In spite of the progressive modernisation of our country, our ability to detect and treat non-communicable diseases, especially cancer, is still severely limited. Indeed, about 13,500 people had prematurely succumbed to cancer in 2019 with higher premature mortality rates expected in the next two to ten years. And according to the WHO global health observatory, our premature mortality rates are almost double that of Singapore and 4.71 points higher than in Thailand in 2019. For most Malaysians, boasting precision medicine to provide targeted therapy remains a pipedream, and real-time cancer data remains a significant challenge in the country. How then can we achieve those goals?
AP. Sarinder Kaur Dhillon and Prof. Nur Aishah Taib are both supervising cancer care digitalization research at the University Malaya Medical Centre (UMMC). From this research came four very impactful projects that aimed to modernize Malaysian cancer care.
Project 1: i-Pesakit Breast Cancer Module
i-Pesakit© is UMMC’s in-house electronic medical record (EMR) system, and the development of a breast cancer module for the system is one of UMMC’s primary cancer care projects. Completion of this module incorporated both clinical and research needs that comply with the Personal Data Protection Act, integrating data from multiple internal clinical departments and establishing a research-focused governance model. This multidisciplinary collaboration has enhanced the quality of data capture in clinical service, benefited hospital data monitoring, quality assurance, audit reporting and research data management, and created a framework for implementing a responsive EMR for a clinical and research organisation in a typical middle-income country setting. (See Figure 1)
Project 2: iSurvive – AI-enabled Breast Cancer Survival Prediction
iSurvive is a plan to develop a fully automated clinician-friendly Artificial intelligence (AI)-enabled database platform for breast cancer survival prediction. A case study of shared characteristics of breast cancer survivors (or cohorts) from UMMC was used to create and evaluate this plan’s development. The proposal is that iSurvive will serve as a one-stop centre to manage data, automate analytics using machine learning, automate scoring and produce explainable interactive visuals to enhance clinician-patient communication along the survivorship period to modify behaviours that relate to prognosis. (See Figures 2 and 3)
Project 3: Wearable biosensors for detecting lymphedema
Secondary lymphedema (a debilitating side-effect of breast cancer treatment) requires lifelong self-care in order to reduce exacerbations of swelling and infections, maintain arm function, and slow the condition’s progression. Currently, however, there is no device that can remotely monitor lymphedema progression, thus limiting our ability to treat this health issue. In light of this, Prof. Fatimah Ibrahim of the Centre for Innovation in Medical Engineering (CIME), UM in collaboration with Prof. Nur Aishah and the UM Cancer Research Institute (UMCRI), and with funding from Selangor R&D Innovation, have developed an Internet-of-Things (IoT)-assisted wearable sensor system for lymphedema treatment monitoring and early diagnosis. The developed wearable sensor allows self-measurement at home and is easy to use in clinical practice. The sensor is also bioimpedance-based (uses a weak electrical voltage to measure body composition, particularly body fat and muscle mass) making it non-invasive and user-friendly for daily monitoring and early diagnosis.
Project 4: REBUNG (Reducing Barriers in Early Cancer Diagnosis among Urban B40 Group)
REBUNG (Reducing Barriers in Early Cancer Diagnosis among Urban B40 Group) is a project funded by UM’s Impact Oriented Interdisciplinary Grant Cycle 2 and the Majilis Bandaraya Petaling Jaya community seed grant that seeks to understand the diagnostic pathways in Petaling Jaya and resources amongst the many organisations. By evaluating regulatory requirements under the Malaysian Personal Data Protection Act, 2010 and following international best practices shared by co-investigator Dr. Mohammad Ershadul Karim, the project will create a healthcare data management and sharing system that protects the patients’ data and medical records from cybersecurity breaches while also balancing the needs and interests of stakeholders in the field.
The digitalization of the Malaysian healthcare system will provide a strong foundation for a better tomorrow, providing long-lasting, good quality data for research and clinical care to curate. However, it will require a holistic approach from all stakeholders in order to produce a data-ready system that is well-prepared for the application of novel research techniques. Our research aims to reduce premature mortality in our country. Global health for us, must begin at home in Malaysia.
Figure 1: Architecture system of the UMMC i-Pesakit© Breast Cancer Module (adapted from Mohd Nor NA 2019)
Figure 2: iSurvive development workflow.
