cause harm if not used properly .

“ It ’ s also based on human data in general and not specific to the Malaysian population . Therefore , we can ’ t rely totally on technology like ChatGPT . One has to know what information is useful .”

The Group Chief Information Officer of TMC Life Science Berhad , G Saravanan , feels AI and robotics will transform healthcare systems by improving diagnostics , treatment , and efficiency while expanding access to care .

“ Although some healthcare jobs may be displaced , many will be transformed or created as professionals adapt to new roles and technologies . Emphasising reskilling and upskilling will help mitigate job displacement while maximising the benefits of AI and robotics in healthcare .”

SHAPING GLOBAL HEALTHCARE

The use of robots , artificial intelligence , and digitalisation is revolutionising healthcare worldwide by delivering effective , focused , and individualised care to patients . Adopting these technologies can help healthcare providers stay current and competitive . The main benefits are :

• Increased efficiency : By automating routine processes like appointment scheduling , billing , and record-keeping , digitalisation and robots has increased

Dr Muruga Raj

Dr Rashid Khan

THE incorporation of Artificial Intelligence ( AI ) in the local healthcare sector has the potential to revolutionise the way healthcare is delivered and improve patient outcomes , said Deputy Director-General ( Public Health ), Ministry of Health ( MoH ), Datuk Dr Norhayati Rusli .

“ However , there are also concerns and limitations associated with this technology that must be considered . For example , concerns about data privacy , security , and system compatibility must be addressed more fully .”

The main privacy concerns surrounding AI are the potential for data breaches and unauthorised access to personal information .

“ Recent cyber-attacks and data breaches have further complicated the incorporation of AI ,” noted Digital Health Malaysia committee member Dr Rashid Khan .

Apart from data privacy and security , other concerns surrounding AI include :

• Bias and discrimination : AI systems are only as good as the data they are trained on , and if the data is biased , then the AI system will also be biased . This can lead to discrimination against certain groups of patients and exacerbate existing health disparities .

• Privacy and security risks : The use of AI in healthcare requires access to sensitive patient data , which can be vulnerable to cyber-attacks and data breaches . This could result in unauthorised access to patient information and potentially harm patients .

• Over-reliance on technology : There is a risk that healthcare providers may become too reliant on AI and neglect their clinical judgment , leading to inappropriate diagnosis or treatment decisions .

• Lack of transparency : The complexity of AI algorithms can make it difficult to understand how decisions are made . This can be problematic for healthcare providers and patients who want to know how a diagnosis or treatment plan was reached .

• Legal and ethical concerns : There are legal and ethical issues related to the use of AI in healthcare , such as liability for medical errors or the impact of AI on the doctor-patient relationship Association of Private Hospitals of

Malaysia ( APHM ) President Datuk Dr Kuljit Singh emphasised the ethical consideration when using AI in the healthcare sector .

“ Doctors and healthcare professionals must be aware and not share patient data without the patient ’ s permission on any medical AI systems or browser , such as ChatGPT . This is because these AI search engines may capture the patients ’ personal details .”

It should be noted that Malaysia currently lacks a regulatory framework to control the use of AI generally or in the healthcare sector .

“ The Malaysian Medical Device Authority ( MDA ) released guidelines on the registration of AI medical devices , which outline the requirements for the registration of AI medical devices in Malaysia . But there is no specific guideline for cloud-based AI technology ,” shared Dr Rashid .

LIMITATIONS OF AI ADOPTION

AI technology is expensive . Funding , developing , and maintaining AI systems can be costly , which is another major issue in Malaysia .

Dr Kuljit highlighted that Malaysia lacked a robust digital platform to unify the healthcare sector .

Dr Kuljit Singh

G . Saravanan

“ Most private hospitals and clinics out there are digitalised concerning healthcare records . The only drawback is that these health information systems are isolated and cannot share data with other healthcare institutions , which hinders the continuity of care .

Group Chief Information Officer of TMC Life Science Berhad , G . Saravanan , said : “ Malaysia is with various systems , and has major complexities when planning to implement AI systems within existing healthcare infrastructures .

“ Resource constraints , infrastructure limitations , and lack of standardised data exchange protocols are some of the challenges that hinder the widespread adoption of digital health solutions in Malaysia .

“ To align with Healthcare Information and Management Systems Society ( HIMSS ) standards and achieve higher levels of technological maturity , Malaysia needs to focus on improving the interoperability of health information systems , promoting the standardisation of data exchange , and investing in digital infrastructure and workforce development .

“ This will enable the country to fully harness the potential of digital health technologies and ensure that the benefits are equitably distributed across the population .”

Regarding the workforce , Saravanan feels Malaysia does not have the skills for AI technology and is also worried about job displacement and the need for healthcare professionals to acquire new skills .

Dr Kuljit noted that many AI systems were available on the market and emphasised that healthcare providers should seek out credible services and take part in seminars and conferences run by experts if they wished to develop their AI skills and incorporate AI systems into their services .

“ Healthcare providers must be well equipped with this knowledge , then guide patients on the usage of AI and the information they get from AI .”

Dr Kuljit and Saravanan also highlighted the disparity in digital health maturity when comparing urban and rural healthcare settings .

“ The overall adoption remains inconsistent across the nation . In the age of 5G and AI , such limitations of current healthcare can be overcome with concepts such as ‘ Housepital ’, the Hospital Services made in the house ,” said Saravanan .