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Universiti Sains Malaysia

Digital Health Sciences Unit at the School of Medical Sciences,
Universiti Sains Malaysia

Digital Health

Understanding Digital Health

Digital technologies are now integral to daily life, and the world’s population has never been more interconnected. Innovation, particularly in the digital sphere, is happening at unprecedented scale. Even so, its application to improve the health of populations remains largely untapped, and there is immense scope for use of digital health solutions.

Healthcare in the digital age is a term that refers to the use of technology and data to improve the delivery and quality of medical care. Some aspects of healthcare in the digital age include connecting with patients remotely, making data work for diagnosis and treatment, and building a dashboard for health management.

The digital revolution has emerged with considerable changes in the healthcare sector. It has paved the way for the development of highly personalized medicine, which is now a reality.

Collaboration among medical institutions, corporations, and governments is required for healthcare digitization. Big Data, mobile devices, and other breakthroughs are propelling medicine forward, as seen by the COVID-19 pandemic.
Hospital USM

Hospital USM

Hasrat menubuhkan Fakulti Perubatan di Universiti Sains Malaysia telah wujud seawal April 1974 namun tertangguh sehinggalah dengan resminya diumumkan pada awal tahun 1979 oleh Y.A.B. Timbalan Perdana Menteri ketika itu di bawah Projek Kompleks Perubatan.

Selaras dengan keputusan tersebut kerajaan memutuskan supaya kompleks Pusat Pengajian Sains Perubatan di empatkan di Kubang Kerian dan hospital yang sedang dibina bermula 1977 di bawah Kementerian Kesihatan diambil alih oleh Universiti Sains Malaysia untuk dijadikan hospital pengajar dengan kos pembiayaan sebesar RM 29.5 juta. Dari situ, Universiti Sains Malaysia mempertingkatkan kerja-kerja pembinaan di samping menyegerakan pengambilalihan kawasan tanah yang telah disediakan oleh kerajaan Negeri Kelantan seluas 72.84 hektar ( 180 ekar persegi) untuk pembinaan Kompleks Perubatan Universiti Sains Malaysia. 

Digital Health Shapes Future of Health

Research

A study aummarized research progress in the field of digital health literacy and revealed the context, trends, and trending topics of digital health literacy research through statistical analysis and network visualization. The authors found that digital health literacy has a significant potential to improve health outcomes, bridge the digital divide, and reduce health inequalities. Our work can serve as a fundamental reference and directional guide for future research.

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Disease Modelling : A case study in UK

Digital health was given impetus by the COVID-19 pandemic and demonstrated its potential for the delivery of safe care in the community. Remote monitoring and virtual wards are becoming mainstreamed across the UK. Artificial intelligence (AI) software has the potential to transform healthcare delivery but its trustworthiness is a key challenge. Positive staff attitudes towards digital health and new ways of working require staff education and engagement. Continued attention is required to meet the needs of those without access to digital technology and its use.

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Collaboration

We are open to collaboration. 

Data Entry Using REDCap

REDCap is a secure web application for building and managing online surveys and databases. While REDCap can be used to collect virtually any type of data in any environment (including compliance with 21 CFR Part 11, FISMA, HIPAA, and GDPR), it is specifically geared to support online and offline data capture for research studies and operations. The REDCap Consortium, a vast support network of collaborators, is composed of thousands of active institutional partners in over one hundred countries who utilize and support their own individual REDCap systems. Please visit the Join page to learn how your non-profit organization can join the consortium, or explore the first section on our FAQ for other options to use REDCap.

REDCap at USM

Read Some Resources

Here are some resources at the School of Medical Sciences, USM and elsewhere

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REDCap for Data Entry at USM

Research Electronic Data Capture (REDCap) is a web-based application developed by Vanderbilt University to capture data for clinical research and create databases and projects. It is Health Insurance Portability and Accountability Act (HIPAA)–compliant, highly secure, and intuitive to use. The databases use instruments such as surveys and forms as research capture tools. Projects are self-sufficient and secure databases that can be used for normal data entry or for surveys across multiple distinct time points.

The USM REDCap System is hosted and managed by the School of Medical Sciences, Universiti Sains Malaysia. 

If you would like to request a REDCap account, fill out the online form accessible here [ online form ] or use this QR 

Important:

  1. Check your email to verify your REDCap account
  2. Email This email address is being protected from spambots. You need JavaScript enabled to view it. if your account is not created after 7 working days (from the date you fill out the form)
London Region

R Programming Language

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.

Highlands

NVIDIA and Analytics

Healthcare demands new computing paradigms to meet the need for personalized medicine, next-generation clinics, enhanced quality of care, and breakthroughs in biomedical research to treat disease. With NVIDIA, healthcare institutions can harness the power of AI and high-performance computing (HPC) to define the future of medicine.

London Region

Analytics in Medical Imaging

or diagnostic imaging alone, the number of publications on AI has increased from about 100–150 per year in 2007–2008 to 1000–1100 per year in 2017–2018. Researchers have applied AI to automatically recognizing complex patterns in imaging data and providing quantitative assessments of radiographic characteristics. In radiation oncology, AI has been applied on different image modalities that are used at different stages of the treatment. i

USM, where you heart is at

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