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National University Hospital to Launch Singapore’s First 3D Point-of-Care Printing Lab

Singapore’s National University Hospital (NUH) and a medical manufacturing company have jointly opened a 3D printing lab to produce personalised anatomical models for preoperative planning and surgical simulation.  The collaboration e aims to push the boundaries of surgical 3D printing in Singapore, elevate the standard of care for patients and deliver better patient outcomes. This initiative is supported by the Singapore Economic Development Board (EDB) to accelerate healthcare innovation in Singapore.

The 3D Printing (3DP) Point of Care Lab is the first of its kind in Singapore. In this Point-of-Care model, biomedical engineers will work closely with NUH clinicians to design and produce personalised anatomical models for preoperative planning and surgical simulation.

Surgery can often cause stress to patients and their families. With patient-specific anatomical models, surgeons can use them as visual tools to educate patients and their families and prepare them for their procedures. This helps reassure patients and reduce stress and anxiety ahead of the surgery

As a leading academic healthcare institution that greatly values and excels in research in innovation, NUH will tap on the 3D Printing Point of Care Lab to improve our clinical outcomes with personalised anatomical models and pioneer the development of new surgical techniques to deliver incredible care to our patients. The facility will also enhance our training and education of new surgeons and clinicians.

– Professor James Hui, Head and Senior Consultant, Department of Orthopaedic Surgery, NUH

Preoperative planning plays a critical role in the success of surgeries. With the 3DP Point of Care collaboration, surgeons and clinicians will gain access to the company’s expertise in 3D Printing development for their preoperative planning. The presence of a dedicated lab within the hospital is pivotal in allowing clinicians to easily discuss cases with the biomedical engineers and fine-tuning their surgical plans using 3D printed models.

Using anatomical models specific to the patient, surgeons can now explore optimal surgical procedures via surgical simulations to pre-empt possible complications before conducting the actual surgery. This can also enable the surgery to be completed in a shorter time.

The lab can currently produce patient-specific anatomical models such as hips and knee joints, with plans to produce other medical devices and instruments such as surgical guides for complex surgery in the near future. Primed for the digital age, the lab will also explore mixed reality (MR) technology to support the development of next-generation clinical applications and better improve patient safety in surgery.

As reported by OpenGov Asia, Singapore stands out among countries across the world due to its stable economy, social inclusivity, and its technological achievement in healthcare. Singapore is a densely connected city-state where the complexities of an internet-enabled telehealth consultation compete with the standard physical visit to the doctor.

According to Associate Professor Lew, Group Chief Data & Strategy Officer, National Healthcare Group, telehealth must be contextualised for value, grounded on trust-based relationships, in areas such as real-time biological monitoring, and round-the-clock trusted advice and alerts.

For the healthy population, the potential of health coaching for individuals and organisations has yet to be fully realised.  In order to envision telehealth beyond transactional efficiency, much remains to be done.

Artificial intelligence (AI) and automation services and systems also significantly benefit healthcare. Yet, Associate Professor Lew believes, while AI is not in the consciousness of mainstream healthcare workers, it is ubiquitous without their realisation.

The lower hanging fruits for AI inclusion in direct care interventions continue to be mundane and predictable tasks, as well as assistive robots in ancillary or health facility production systems. AI and machine learning are probably most valuable as augmented intelligence for narrowly defined use-cases with adequate digital guardrails so that the basis for interpretation is understood and trusted. In this context, experts have recommended that, in addition to deep learning, more traditional hierarchical models of reasoning be used.


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