Year 12 – Health and Movement Science

3.2 Investigate new technologies and treatments in the healthcare system

About the dot point

The modern healthcare system increasingly depends on health technology and evolving treatments to prevent disease, detect conditions earlier, deliver care more efficiently, and improve health outcomes. Newer technologies, such as health apps, artificial intelligence and assistive technology, are changing how information is collected, interpreted, and acted on across hospitals, clinics, and community care. At the same time, rapid advances in treatments are expanding what can be treated and how precisely care can be matched to individual needs, while also raising important questions about safety, cost, privacy, and equitable access.

How to approach it

In this dot point, the directive verb is Investigate. This means you need to inquire into new technologies and treatments by gathering and using relevant evidence, exploring a range of current examples, and considering how and why they matter within the healthcare system. As you work through the content on this page, focus on what each development does, how it is used in real healthcare settings, and the key advantages, limitations, and implications (for example reliability, bias, regulation, privacy, affordability, and access) that determine whether it improves health outcomes in practice.

1. New technologies in the healthcare system

A health technology is any tool, device, system, or software-based product used to improve healthcare and health outcomes. New refers to technologies that have emerged very recently or to major recent developments that have changed what healthcare can do, how quickly it can respond, or how easily care can be delivered.

1.1 Health apps

Health apps are software programs used on phones, tablets, watches, or other digital devices to support health-related decisions and behaviours. Not all health apps are genuinely new, but the major recent development is the growth of apps that are more closely integrated with monitoring devices, remote care, and, in some cases, therapeutic support.

In the healthcare system, newer forms of health apps can include:

  • app-linked monitoring apps: apps connected to devices such as glucose monitors or wearable sensors that display trends, alerts, and summaries
  • digital mental health tools: apps or platforms that provide structured assessment, symptom monitoring, or therapeutic support
  • medication and care-management apps: apps that support reminders, treatment tracking, and communication with health professionals
  • remote patient support apps: apps that allow information to be shared more easily between patients and healthcare providers

These apps matter because they can support self-management, improve continuity of care, and make changes in health easier to identify earlier. However, their value depends on whether they are accurate, clinically appropriate, and safe to use. Some apps are regulated medical devices, while others are not, which means quality and reliability can vary. Privacy and data security are also major concerns because these apps often collect sensitive personal information.

App-linked monitoring apps are health apps that connect to a medical device or wearable sensor and display health information on a phone or tablet. They can show readings, trends, alerts, and summaries that help the user and their health professional understand what is happening over time.

A clear example is an app linked to a continuous glucose monitor (CGM). The sensor measures glucose levels regularly, and the app displays the results in a more usable form.

They are used in healthcare to:

  • support self-management between appointments
  • make changes in health easier to notice
  • give health professionals clearer information than relying on memory alone
  • support earlier action when readings move outside the target range

Main advantage
  • Provides continuous health data rather than occasional one-off readings.
  • Makes patterns and trends easier to see over time.
  • Gives users and health professionals clearer information for decision-making.

Why it matters

Can improve self-management and make care more personalised because decisions can be based on real patterns over time, not just memory or guesswork.

Main limitation

Only useful if the device is accurate and the user understands the data properly.

Key implications
  • Reliability matters because inaccurate readings can lead to poor decisions.
  • Regulation matters because not all apps are tested to the same standard.
  • Privacy matters because these apps often collect sensitive health data.
  • Access matters because not everyone can afford the device, app, or internet connection needed to use it effectively.

1.2 Artificial intelligence

Artificial intelligence (AI) refers to computer systems that can analyse large amounts of data, recognise patterns, and support decision-making. In healthcare, AI is mainly used to assist health professionals rather than replace them.

Recent and major current uses of AI in the healthcare system include:

  • AI-assisted image analysis: using AI to examine scans and other images to help identify abnormalities more quickly or accurately
  • AI-supported diagnosis: comparing patient data with recognised patterns to assist clinical decision-making
  • risk prediction tools: identifying patterns in records, test results, or monitoring data that suggest future complications or deterioration
  • medication safety systems: checking for risky prescribing patterns, unsafe combinations, or potential medication errors
  • workflow and documentation tools: helping organise information, prioritise cases, and reduce repetitive administrative work
  • drug discovery: using AI to test possibilities more quickly and support the development of new medicines

AI is a strong example of a genuinely current technology because its clinical use, regulation, and real-world implementation have accelerated very recently. Its main strengths are speed, consistency, and the ability to process very large and complex datasets. However, AI also creates important concerns. It can reproduce bias if the data used to train it is not representative, it may produce errors, and it raises questions about privacy, transparency, and accountability. This means AI should be used as a support tool, with professional judgement remaining central.

AI-assisted image analysis uses artificial intelligence to examine medical images and help identify abnormalities more quickly or accurately. This can include X-rays, CT scans, MRI scans, and digital pathology images.

In healthcare, AI-assisted image analysis can:

  • highlight suspicious areas on a scan or image
  • support faster triage, meaning deciding which cases need urgent attention first
  • help manage large imaging workloads
  • assist clinicians in making more efficient decisions

Main advantage
  • Processes large numbers of images quickly.
  • Applies the same pattern-recognition process consistently.
  • Can help highlight abnormalities that need closer clinical review.

Why it matters

May support earlier diagnosis and more efficient use of specialist time.

Main limitation

Depends heavily on the quality and representativeness of the data used to train the AI.

Key implications
  • Bias matters because AI may perform less accurately for some groups if the training data is not representative.
  • Clinical oversight matters because AI should support, not replace, professional judgement.
  • Accuracy matters because incorrect results can delay diagnosis or lead to unnecessary follow-up.
  • Accountability matters because health professionals and health systems still remain responsible for the final decision.

1.3 Assistive technology

Assistive technology includes products, equipment, and systems that improve functioning, independence, and participation for people with disability, chronic conditions, injury, or age-related decline. Assistive technology itself is not new, but many of the most important developments in recent years are newer digital, sensor-based, connected, or highly personalised forms of assistive support.

Examples of newer assistive technology include:

  • smart prosthetics: prosthetic limbs that use sensors or microprocessors to improve control, movement, and safety
  • eye-gaze and advanced AAC systems: communication tools that allow users to interact and communicate through screen-based or eye-controlled systems
  • voice-controlled digital access tools: systems that help users control devices and online environments without standard typing or touch
  • smart home assistive systems: connected systems that allow safer and easier control of lights, doors, alarms, and appliances
  • wearable alert and fall-detection devices: tools that can detect emergencies and support safer independent living
  • brain-computer interfaces: emerging systems that create a direct link between neural activity and an external device, with recent advances aimed at restoring communication or device control

These technologies matter because they can improve independence, communication, safety, and quality of life. They also show that healthcare technology is not only about diagnosis and treatment, but also about participation and inclusion. However, access remains a major issue. The WHO highlights the importance of improving access to assistive technology through its GATE initiative and 5P framework, and in Australia this area links closely to Australia’s Disability Strategy 2021–2031.

Brain-computer interfaces create a direct link between brain activity and an external device. The system detects neural signals and translates them into commands that can control something outside the body, such as a computer or communication device.

In healthcare, brain-computer interfaces are being developed to:

  • restore communication for people who cannot speak
  • support device control for people with severe paralysis
  • improve independence in daily life
  • expand participation for people with major neurological impairment

Main advantage
  • May restore communication for people who cannot speak.
  • May allow control of external devices through brain signals.
  • Can improve independence and participation in daily life.

Why it matters

Can improve independence, participation, and quality of life.

Main limitation

Many systems are still emerging and not yet routine in clinical practice.

Key implications
  • Long-term safety matters because these systems may involve invasive procedures or ongoing device use.
  • Cost matters because advanced systems are likely to be expensive to develop and deliver.
  • Access matters because only a small number of people may be able to use them at first.
  • Support needs matter because users often require training, follow-up, and technical assistance.
  • Ethics also matters because expectations, consent, and appropriate use must be managed carefully.

2. New treatments in the healthcare system

New treatments are new or significantly improved ways of treating, managing, or repairing a health condition. They include advances in medicines, biological therapies, procedures, and emerging interventions such as gene therapies, gene editing, and regenerative medicine.

New treatments are different from new technologies because they focus on the intervention used to improve the patient’s condition, rather than the tools or systems that support healthcare. In reality, the two are closely connected, because new technologies often help develop or deliver new treatments.

2.1 Pharmaceutical and biological treatments

New treatments in the healthcare system include recent advances in pharmaceuticals, biologics, and other targeted therapies. These treatments aim to improve effectiveness, reduce side effects, and better match treatment to the specific needs of the patient.

Examples include:

  • mRNA-based therapies and vaccines: treatments that use messenger RNA technology to trigger a targeted biological response
  • targeted cancer therapies: treatments that act on specific molecules or pathways involved in cancer growth
  • gene therapies: treatments that alter, replace, or introduce genetic material to treat or prevent disease
  • cell-based therapies: treatments that use living cells, such as engineered immune cells, to target disease
  • treatments designed for specific biological pathways: therapies that target particular immune, inflammatory, or cellular processes to improve precision

These developments can improve health by making treatment more precise and, in some cases, more effective than older approaches. They may improve survival, reduce adverse effects, and provide better quality of life for some patients. Recent regulatory milestones, including approvals for gene therapies and the first approved CRISPR-based treatment, show how quickly this area is moving. However, these treatments can also be very expensive, may require strict regulation and monitoring, and are not always equally accessible to all patients.

mRNA-based therapies and vaccines use messenger RNA, or mRNA, to give cells instructions to make a specific protein that triggers a biological response. In vaccines, this helps the immune system learn how to respond more effectively in the future.

A key point is that mRNA does not change a person’s DNA. It provides temporary instructions that are later broken down.

These therapies matter because they can:

  • be developed relatively quickly
  • create a targeted biological response
  • be adapted more easily than some older treatment platforms
  • support rapid responses to changing infectious diseases

Main advantage
  • Can be developed relatively quickly.
  • Produces a targeted biological response.
  • Can be adapted more easily than some older treatment platforms.

Why it matters

Useful when diseases change quickly or when a rapid treatment response is needed.

Main limitation

Requires strong evidence, careful regulation, and large-scale manufacturing capacity.

Key implications
  • Safety matters because newer treatment platforms need close monitoring.
  • Regulation matters because public trust depends on strong approval processes.
  • Access matters because some populations may receive these treatments later than others.
  • Cost and manufacturing matter because rapid development still depends on large-scale production and distribution systems.
  • Public confidence matters because misunderstanding or mistrust can reduce uptake and limit the health benefit.

2.2 Surgical and procedural treatments

New treatments also include major recent developments in surgical and procedural care. These developments aim to improve accuracy, reduce invasiveness, and shorten recovery time.

Examples include:

  • robotic-assisted surgery: surgery in which the surgeon uses robotic systems to improve precision, control, and access during complex procedures
  • advanced image-guided interventions: procedures that use more sophisticated real-time guidance and navigation to improve precision inside the body
  • augmented reality-assisted surgery: using digital overlays to improve visualisation during planning or procedures
  • virtual reality surgical simulation: using immersive simulations to practise, plan, or refine complex surgical procedures
  • patient-specific implants and 3D-printed surgical guides: devices designed for an individual patient to improve fit and surgical accuracy

These developments are best treated as major recent advances rather than completely brand-new ideas. Their significance lies in how much they have improved precision, planning, training, and recovery in recent years. The main advantage of these treatments is that they can make procedures safer, more precise, and less physically demanding on the patient. However, they often require expensive equipment, specialist training, and ongoing maintenance, so access can still vary across hospitals and regions.

Robotic-assisted surgery is surgery in which the surgeon controls robotic instruments from a console to improve precision, control, and access during complex procedures. The robot does not operate independently. The surgeon remains in control throughout the procedure.

In healthcare, robotic-assisted surgery may:

  • allow smaller incisions
  • improve movement in tight or hard-to-reach areas
  • reduce damage to surrounding tissue
  • support faster recovery in some procedures

Main advantage
  • Improves precision and control during complex procedures.
  • Can reduce tissue damage in some operations.
  • May support smaller incisions and faster recovery.

Why it matters

May improve surgical outcomes, reduce recovery time for some patients and make certain complex procedures safer or more effective.

Main limitation

Requires expensive equipment, specialist training, and ongoing maintenance.

Key implications
  • Affordability matters because only well-resourced hospitals may be able to provide it.
  • Training matters because outcomes still depend on the skill of the surgical team.
  • Equity of access matters because patients in rural, remote, or lower-resourced areas may miss out.
  • Suitability matters because robotic-assisted surgery is not the best option for every condition or patient.
  • System capacity matters because hospitals need the staff, equipment, and infrastructure to use it safely.

2.3 Regenerative and emerging treatments

Some of the newest treatment areas focus on repairing or replacing damaged tissues rather than only managing symptoms.

Examples include:

  • regenerative medicine: treatments that aim to repair, replace, or regrow damaged cells, tissues, or organs
  • 3D bioprinting: the use of specialised printing technology to create tissue-like structures, implants, or body parts for medical use
  • gene editing: techniques that alter DNA sequences to correct, remove, or replace faulty genetic material
  • nanotechnology-based treatments: the use of extremely small materials or devices to deliver treatment more precisely or improve how therapies work in the body
  • bioelectronic devices and smart implants: implantable systems designed to monitor, stimulate, or support body functions in more targeted ways

These treatments are important because they suggest future possibilities for conditions that are currently difficult to manage. Recent milestones in gene therapy and gene editing make this section much more genuinely current than older textbook examples that have been in healthcare for decades. However, many of these treatments are still emerging. Their long-term safety, effectiveness, cost, and ethical implications are still being explored, so they should be investigated as promising developments rather than assumed to be simple or universally available solutions.

Gene editing refers to techniques that make specific changes to DNA by adding, removing, or altering genetic material. One well-known method is CRISPR-Cas9, which allows a targeted change to be made to a specific part of the genetic code.

In healthcare, gene editing is important because it may:

  • target the cause of some inherited conditions
  • move treatment beyond symptom management alone
  • allow more precise, cause-based intervention
  • create new possibilities for conditions that were previously difficult to treat

Main advantage
  • Targets the underlying genetic cause of some diseases.
  • May move treatment beyond symptom management alone.
  • Has the potential to create more precise, cause-based interventions.

Why it matters

Could represent a major shift in how some inherited conditions are treated.

Main limitation

Safety risks remain, including unintended changes to DNA.

Key implications
  • Ethics matters because changing genetic material raises questions about what should and should not be altered.
  • Regulation matters because gene editing requires strict oversight and clear limits.
  • Equity matters because very expensive treatments may only be available to some groups.
  • Long-term monitoring matters because effects may not be fully understood straight away.
  • Safety matters because unintended genetic changes could create new health risks.

Brief Summary

About the dot point and how to approach it

  • The modern healthcare system increasingly depends on health technology and evolving treatments to improve health outcomes.
  • Investigate means to inquire by gathering and using evidence and considering implications such as reliability, bias, regulation, privacy, affordability, and access.

1. New technologies in the healthcare system

  • Health apps support health decisions and behaviours, and their value depends on accuracy, regulation status, privacy, and access.
  • Artificial intelligence (AI) assists health professionals with speed and consistency, but creates concerns about bias, privacy, transparency, and accountability.
  • Assistive technology improves functioning, independence, and participation, but access remains a major issue.

2. New treatments in the healthcare system

  • Pharmaceutical and biological treatments aim to improve effectiveness and precision, but can be expensive and not equally accessible.
  • Surgical and procedural treatments improve precision and recovery, but require expensive equipment and specialist training.
  • Regenerative and emerging treatments focus on repair and replacement, but are still emerging and need evidence on long-term safety, effectiveness, cost, and ethics.