APRIL 16 — Malaysia’s healthcare system has long been a source of national pride, particularly its network of public hospitals that provide affordable care to millions. However, overcrowded wards, long waiting times, and rising healthcare costs reveal a growing challenge: our system is largely designed for sick-care rather than preventative-care.

The National Health and Morbidity Survey (NHMS) 2023 outlines a silent pandemic that reveals around 2.3 million Malaysian adults live with at least three non-communicable diseases (NCDs) like diabetes, hypercholesterolaemia and hypertension.

As a biomedical engineering student, I believe the solution is not simply to build more hospitals, but to use artificial intelligence (AI), the Internet of Things (IoT), and remote patient monitoring to prevent avoidable illnesses from escalating into hospital admissions.

Many of the conditions that fill hospital beds today, such as diabetes, hypertension, heart disease, asthma, and chronic kidney disease, do not appear overnight. They worsen gradually, often silently, causing a patient to require emergency care. However, our current healthcare model relies heavily on episodic check-ups, where patients are assessed only when they visit a clinic or hospital. Between these visits, critical warning signs are often missed. This is where smart healthcare technologies can make a meaningful difference and overcome the physical visit of the patient to the hospital.

IoT-enabled medical devices enable the continuous collection of health data, rather than collecting it only occasionally. Wearable sensors can monitor heart rate, oxygen saturation, physical activity, and sleep patterns. For instance, smart blood pressure monitors and glucometers can transmit readings directly to healthcare providers, allowing healthcare providers to monitor the patient’s condition remotely.

For elderly patients living alone or in rural areas, these tools provide an extra layer of safety without requiring frequent hospital visits and physically attending a consultation, creating a safety net for patients in rural areas. Instead of waiting for symptoms to worsen, doctors can intervene early based on real-time data and can plan timely outpatient treatments, medication adjustments, or lifestyle interventions before a patient’s condition escalates into an emergency.

However, data alone is not enough. This is where AI plays a critical role. AI systems can analyse thousands of data points from multiple patients, detect abnormal trends, and predict health deterioration before it becomes life-threatening. For example, an AI model can identify subtle changes in heart rate variability that signal worsening heart failure, or recognise blood glucose patterns that suggest poor diabetes control. Early alerts allow healthcare teams to adjust medication, provide teleconsultations, or recommend lifestyle changes — often preventing hospitalisation altogether.

According to a recent study, machine learning algorithms are now being used in Malaysia to enhance diagnostic precision and catch early signs of life-threatening conditions through smart clinical decision tools. These tools improve diagnostic accuracy in several ways. For example, a critical event can be detected at an early stage. The AI system, like AI-powered electrocardiograms (AI-ECG), is able to identify early diagnosis of life-threatening conditions like ST-elevation myocardial infarctions. Also, these tools can significantly reduce diagnostic errors and standardise care protocols.

The benefits of this shift extend beyond patients. When hospitals are freed from preventable admissions, clinicians can focus resources on complex and critical cases such as trauma, advanced cancer treatment, and specialised surgeries. This allows for better allocation of beds, medical equipment and specialist expertise. Thus, care quality can be improved while reducing strain on healthcare workers, who are already facing burnout from overwhelming workloads.

On the contrary, healthcare providers can have more time to deliver higher-quality and strengthen the resilience of public hospitals facing increasing healthcare demand.

Importantly, adopting smart healthcare does not mean replacing hospitals or doctors. Rather, it provides them with evidence-based insights that help them to make correct decisions quickly and enhance their ability to deliver care. Technology acts as an early warning system and decision-support tool, while clinicians remain responsible for diagnosis and treatment. When used responsibly, AI and IoT can reduce human error, support clinical judgement, and improve patient outcomes.

Malaysia is well-positioned to embrace this transformation. Digital health and AI development reflect growing recognition that healthcare sustainability depends on prevention, not expansion alone. This shift is central to the Ministry of Health’s RESET initiative, which aims to strengthen digital health infrastructure and transition ambulatory care into community-based settings. By 2029, the ministry plans to establish a fully interoperable health information ecosystem that empowers patients while reducing unnecessary hospital admissions and strengthening national health security.

Of course, challenges will remain. Data privacy, cybersecurity, and equitable access must be addressed to ensure that smart healthcare does not widen existing inequalities. Clear regulations, strong data governance, and public education are essential. Patients must trust that their health data is secure and used ethically. Healthcare professionals must also be trained to work confidently with digital tools.

All in all, the question is not whether Malaysia needs hospitals. The real question is whether we can reduce the number of Malaysians who need to be in them. By shifting our focus from reacting to illness to preventing it, AI, IoT, and remote monitoring offer a practical and sustainable path forward. Smarter healthcare is not about technology for its own sake, but it is about keeping people healthier, longer, and closer to home.

* Ng Kheng Yean is a final year student at the Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, enrolled in an elective course entitled “Healthcare Technology and Clinical Management”, and may be reached at nahrizuladib@um.edu.my

** This is the personal opinion of the writer or publication and does not necessarily represent the views of Malay Mail.