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Technology, digital health and big data: HSC Health and Movement Science Focus Area 1

Syllabus dot point

“Investigate how technology, digital health and big data influence health outcomes, access and equity in Australia”

9 min read

Quick answer

Australia's digital health stack (My Health Record, Medicare-funded telehealth, wearables and CGMs, big-data tools like the Atlas of Healthcare Variation, and emerging AI diagnostics) improves average access and outcomes, but raises real privacy and digital-divide concerns; the equity-aware response is to combine digital expansion with explicit support for priority populations.

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  1. What this sub-topic is asking
  2. The answer
  3. Examples in context
  4. Try this
  5. Practice questions

What this sub-topic is asking

NESA wants you to describe the main forms of digital health technology in use in Australia (records, telehealth, wearables, big-data analytics, AI), explain how each affects access and outcomes, and assess the equity and privacy implications, especially the digital divide.

The answer

The simplest way to hold this topic is as a chain: technologies feed data, data improves care and surfaces inequity, but the same data create privacy risk and the same technologies are unevenly distributed - so the net effect on equity depends on design. The concept map below traces that chain.

How technology and data shape health in Australia A concept map. At the top, four technology nodes - My Health Record, MBS-funded telehealth, wearables and CGMs, and AI in diagnostics - all feed into a central "big data and population analytics" node (e.g. the Atlas of Healthcare Variation). From the data node two arrows branch: a green pathway to benefits (better access, better outcomes, system-level accountability) and a red pathway to costs (privacy and centralised-risk, plus the digital divide). A bottom band shows the equity outcome depends on design: proportionate universalism turns the gap-widening risk into a gap-closing gain. How technology and data shape health My Health Record MBS telehealth Wearables & CGMs AI in diagnostics Big data & population analytics e.g. Atlas of Healthcare Variation, AIHW, linked MBS-PBS-hospital data BENEFITS better access (no travel) better outcomes (safer care) self-management (CGMs) system accountability COSTS / RISKS privacy & centralised risk consent & secondary use the digital divide (older, low-income, remote) EQUITY OUTCOME depends on DESIGN Raises the average, but can WIDEN the gap. Proportionate universalism = universal expansion + targeted supports for priority populations.

The main technologies

My Health Record
Australia's national personal health record, run by the Australian Digital Health Agency. Allows GPs, specialists, pharmacists and hospitals to view a patient summary (medications, allergies, recent diagnostic results, hospital discharge summaries). Opt-out, so most Australians have a record, though active engagement is much lower.
Telehealth
Phone and video consultations funded through the Medicare Benefits Schedule (MBS). Permanent MBS telehealth items were expanded substantially during the COVID-19 pandemic from 2020 and have remained as ongoing items, particularly for GP and mental-health consultations. Removes travel barriers for rural and remote patients and reduces work-time loss for urban patients.
Wearables and consumer devices
Fitness trackers and smart watches that measure steps, heart rate, sleep and (on newer devices) ECG or blood oxygen. Continuous glucose monitors (CGMs) are now subsidised through the National Diabetes Services Scheme for many people with Type 1 diabetes; they replace finger-prick testing with near-real-time glucose data and have transformed self-management.
Big data and population analytics
Aggregated data sets that let researchers and policymakers see patterns across the whole system. Examples:
  • The Australian Atlas of Healthcare Variation (Australian Commission on Safety and Quality in Health Care) maps how rates of procedures, prescribing and admissions vary by geography, surfacing inequity.
  • The AIHW's Australia's Health reporting series.
  • Linked-data projects that connect MBS, PBS, hospital and registry data.

Artificial intelligence (AI) in diagnostics. AI image-analysis tools are increasingly deployed in radiology (mammography, CT) and dermatology, typically as a "second reader" assisting a clinician rather than replacing them. Australian roll-out is regulated by the Therapeutic Goods Administration; uptake is uneven and still under formal evaluation.

Effects on access and outcomes

Improving access. Telehealth removes travel; wearables push prevention into daily life; My Health Record reduces duplicate testing when a patient moves between providers; CGMs improve diabetes self-management.

The clearest single illustration is the telehealth surge. The chart below traces telehealth's share of Medicare consultations across recent years: negligible before 2020, a sharp spike when permanent MBS items were introduced, then a settle to a baseline still many times higher than pre-pandemic. It is built to be illustrative of the documented MBS telehealth pattern from 2020; treat the exact heights as an ExamExplained dataset, not a quoted table.

Telehealth share of Medicare consultations - the 2020 surge A line chart. The x-axis is year from 2019 to 2023; the y-axis is approximate telehealth share of Medicare consultations per cent from 0 to 40. The line starts very low at about 1 per cent in 2019, spikes to a peak of about 35 per cent in 2020, then steps down to about 30 per cent in 2021, about 22 per cent in 2022 and about 19 per cent in 2023 - a sharp surge followed by a partial decline to a raised plateau far above the 2019 level. The marker dots sit exactly on the line. Telehealth share of Medicare consultations (illustrative) 0 10 20 30 40 Telehealth share (%) 1% 35% 30% 22% 19% 2019 2020 2021 2022 2023 permanent MBS items from 2020

Improving outcomes. Better information at the point of care reduces medication error, missed allergy notes and unnecessary repeats. Atlas-style data drive system-level change by showing geographic variation that cannot be defended clinically.

Reshaping the workforce. Clinicians spend more time interacting with screens and less with patients in some settings; rural generalists can access metro specialist input via telehealth; pharmacists use My Health Record to reconcile medications.

Data privacy and digital divide

Privacy. Centralised records create centralised risk. Concerns include consent (especially for sensitive items like mental-health and sexual-health records), secondary use of data for research, and the risk of breaches. Regulation sits with the Office of the Australian Information Commissioner and the Australian Digital Health Agency.

The digital divide. Benefits cluster with those who already have devices, data, English-language confidence and digital health literacy. People who are older, on lower incomes, in remote areas, or who speak a language other than English at home are systematically less likely to use a patient portal, install a wearable, or sustain a video consult on mobile data. Telehealth without translated materials, captioning, or a digital-navigator service can widen the inequity it was meant to reduce.

This is the central equity tension: digital health raises the average but can widen the gap unless explicitly designed for priority populations.

Worked example

Telehealth in remote NSW after 2020. A patient in a remote NSW town previously drove around five hours to see a specialist. Permanent MBS telehealth items now allow the appointment to occur via video from the local GP clinic, with the GP present. Access: significantly improved (no travel, no work-time loss). Outcomes: continuity improved, follow-up rates higher. Equity caveat: requires reliable broadband, a local GP, and basic digital literacy. Where any of these is missing (very remote communities, older patients without family support), telehealth alone widens the gap; the equity-aware response combines telehealth with a digital navigator, in-language materials and a continuing investment in the rural physical workforce.

Common traps
Treating digital health as automatically equitable
It improves access on average and widens the digital divide unless explicitly designed for priority populations. Mention both effects.
Confusing My Health Record with a clinical record
It is a summary designed for sharing across providers, not the primary clinical record used in a hospital or GP system. Strong responses keep this distinction.
Naming "AI" generically
Specify the use case (radiology image analysis, dermatology triage, clinical decision support) and the regulatory body (TGA) where relevant.
Forgetting telehealth is Medicare-funded
The substantive Australian story is the MBS funding shift since 2020, not telehealth as a technology in the abstract.
Ignoring privacy
A confident answer notes the centralised-risk trade-off and the role of the OAIC and the Australian Digital Health Agency.
Key fact

The stack, the bodies and the tension. Learn five named technologies and what each is for: My Health Record (national, opt-out, shared SUMMARY - not a clinical record - run by the Australian Digital Health Agency); MBS-funded telehealth (phone/video Medicare items made permanent from 2020, removing travel for rural and remote patients); wearables and CGMs (CGMs subsidised via the NDSS for Type 1 diabetes); big data (the Australian Atlas of Healthcare Variation from the Australian Commission on Safety and Quality in Health Care, plus AIHW reporting and linked MBS-PBS-hospital data); and AI in diagnostics (radiology/dermatology "second reader", regulated by the TGA). Privacy oversight sits with the OAIC and the Australian Digital Health Agency. The exam tension to memorise: digital health raises the AVERAGE but can WIDEN the gap unless designed with proportionate universalism (universal expansion plus targeted supports for priority populations).

Exam technique
Match the command word to the depth
"Outline/describe" wants the named technology and what it does; "explain" wants the cause-and-effect on access or outcomes; "assess/evaluate" wants you to WEIGH benefits against the privacy and digital-divide costs and reach a judgement. An all-positive "technology is great" answer caps your band on an evaluate question.
Always name the Australian specifics, not the generic gadget
Replace "video calls" with "MBS-funded telehealth, permanent from 2020"; replace "a health app" with "My Health Record (opt-out, run by the Australian Digital Health Agency)"; replace "data" with "the Australian Atlas of Healthcare Variation". The regulator names (TGA, OAIC) and the funding mechanisms (MBS, NDSS) are easy marks.
Bank the two distinctions markers look for
(1) My Health Record is a shareable SUMMARY, not the primary clinical record. (2) Digital health improves access ON AVERAGE but can widen the digital divide - so always mention BOTH effects and finish with proportionate universalism.
Read a stimulus like a scientist
For a data/stimulus item, DESCRIBE first (direction, the endpoints with figures, the shape - e.g. a sharp 2020 spike then a raised plateau), then EXPLAIN with the access concept and the MBS funding change, then state the equity caveat. Quoting the start, peak and end values earns the description marks a vague "it went up" cannot.
In plain English

Think of digital health like getting a smart speaker and a shared family calendar for a busy household. The shared calendar is My Health Record: instead of each person keeping their own scribbled notes, everyone (your GP, the pharmacist, the hospital) can see the same summary, so nobody double-books a test or misses that you are allergic to a medicine. Telehealth is the video call: before 2020 you had to drive into town to see the doctor; now, if you live five hours away, the appointment can happen on a screen, and Medicare pays for it just like an in-person visit. Wearables and glucose monitors are the fitness band on your wrist and, for people with diabetes, a tiny sensor that reads blood sugar all day instead of finger-pricks - the health checks move into normal life. Big data is what happens when you zoom out: line up everyone's anonymous records and you can spot that one town gets way more of a certain operation than another for no medical reason - a clue that something is unfair, which then gets fixed. So what is the catch? Two things. First, putting everything in one big shared place is convenient but also a juicy target if someone breaks in - that is the privacy worry. Second, all of this only helps if you actually have decent internet, a phone or watch, and the confidence to use them. The people who need health care most - older folks, people on low incomes, people far from the city - are often the ones least likely to have all that. So the clever gadgets can quietly leave them further behind. The fix is simple to say and harder to do: roll the technology out for everyone, but put extra help (a person to walk you through it, instructions in your language) where it is needed most, so the gap closes instead of growing.

Examples in context

Example 1. The Australian Atlas of Healthcare Variation. Published by the Australian Commission on Safety and Quality in Health Care, the Atlas maps how rates of common procedures (knee arthroscopy, antibiotic prescribing, caesarean section, ADHD medication dispensing) vary across local areas. Variation that is not explained by clinical need flags inequity or low-value care. This is the canonical Australian example of big data being used to drive system change: the data itself becomes an intervention by creating public accountability and informing local clinical-governance work.

Example 2. Continuous Glucose Monitors (CGMs) and Type 1 diabetes. The federal government's expansion of CGM subsidy through the National Diabetes Services Scheme has put near-real-time glucose data into the hands of most Australians with Type 1 diabetes, replacing many finger-prick checks. Self-management, hypoglycaemia awareness and time-in-range have all benefited in published Australian data. The example illustrates how a consumer-style device, when paired with a public subsidy, can shift outcomes for a defined clinical population, while still leaving an equity question about who has the digital literacy and supports to use it well.

Try this

Q1. Outline three digital health technologies in current Australian use and explain how each affects access to care. [6 marks]

  • Cue. My Health Record (shared summary across providers), MBS-funded telehealth (removes travel, especially rural/remote), wearables/CGMs (push prevention and self-management into daily life). One sentence on access per item.

Q2. Explain how big data is used to identify and address health inequities in Australia. [6 marks]

  • Cue. Australian Atlas of Healthcare Variation (geographic variation, low-value care), AIHW reporting, linked MBS-PBS-hospital data. Big data identifies the inequity, informs targeted policy and creates accountability.

Q3. Assess the impact of telehealth on equity of access to health care in Australia since the 2020 MBS expansion. [8 marks]

  • Cue. Improved access (rural/remote, working patients, mental-health continuity). Equity caveats (broadband, digital literacy, language). Use the proportionate-universalism framing: telehealth as a universal expansion plus targeted supports (digital navigators, translated materials) for priority populations. Reach a clear judgement.

Practice questions

Original practice questions graded from foundation to exam level, each with a full worked solution. Try them before revealing the solution.

exam6 marks
Outline THREE digital health technologies in current Australian use and explain how each affects access to care.
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A 6-mark response needs three named technologies, each with an access effect.

My Health Record
A shared summary across providers reduces duplicate testing and improves continuity when a patient moves between services.
MBS-funded telehealth
Phone and video consultations (expanded permanently from 2020) remove travel and work-time barriers, especially for rural and remote patients.
Wearables and continuous glucose monitors
Push prevention and self-management into daily life; subsidised CGMs have transformed Type 1 diabetes self-management.

Markers reward (1) three correctly named technologies, (2) an access effect for each, (3) Australian specificity (MBS funding, NDSS subsidy).

exam8 marks
Assess the impact of telehealth on equity of access to health care in Australia since the 2020 MBS expansion.
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An 8-mark assess needs benefits and equity caveats, then a calibrated judgement.

Benefits
Permanent MBS telehealth items removed travel for rural and remote patients, reduced work-time loss for urban patients, and improved mental-health continuity.
Equity caveats
Benefits cluster with those who already have broadband, devices, English-language confidence and digital health literacy; without translated materials, captioning or digital navigators, telehealth can widen the divide it aimed to reduce.
Judgement
Use proportionate universalism: telehealth as a universal expansion plus targeted supports for priority populations; conclude that it improves average access but needs explicit equity design.

Markers reward (1) benefits, (2) the digital-divide caveat, (3) a calibrated judgement using the proportionate-universalism framing.

foundation3 marks
Define 'digital health' and give THREE examples of digital health technologies currently used in Australia.
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Definition (1 mark). Digital health is the use of information and communication technology (records, devices, data and online services) to support health care, prevention and self-management.

Three examples (1 mark for any two correct, 2 marks for three) - each must be a real Australian technology, not a generic gadget:

  • My Health Record - the national, opt-out, shared patient summary run by the Australian Digital Health Agency.
  • Medicare (MBS) funded telehealth - phone and video consultations, made permanent items from 2020.
  • Wearables and continuous glucose monitors (CGMs) - consumer trackers, and NDSS-subsidised CGMs for Type 1 diabetes.
  • (Also acceptable: big-data tools such as the Australian Atlas of Healthcare Variation; AI image-analysis in radiology.)

Full marks need the definition PLUS three correctly named Australian examples. A generic answer ("a fitness app", "the internet") with no Australian specificity caps at 2.

foundation4 marks
Outline what My Health Record is, and explain ONE benefit and ONE risk of a centralised national health record.
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What it is (1 mark)
My Health Record is Australia's national, opt-out personal health record run by the Australian Digital Health Agency: a shared SUMMARY (medications, allergies, recent results, discharge summaries) that GPs, specialists, pharmacists and hospitals can view - not the primary clinical record.
One benefit (1-2 marks)
Continuity of care: when a patient moves between providers, the shared summary reduces duplicate testing, medication errors and missed allergy notes, improving safety and reducing waste.
One risk (1-2 marks)
Centralised data create centralised risk: a single large store raises the stakes of a data breach, and there are consent concerns about sensitive items (mental-health, sexual-health) and secondary use of data for research.

Marking spine: correct "summary, not clinical record" framing (1), a clearly explained benefit (1-2), a clearly explained privacy/security risk (1-2). Confusing My Health Record with a hospital's clinical record caps the answer.

core5 marks
A described dataset (ExamExplained) shows the share of Medicare consultations delivered by telehealth in Australia by year: 2019 about 1%, 2020 about 35%, 2021 about 30%, 2022 about 22%, 2023 about 19%. Describe the trend shown and explain it using the concept of access to care.
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A 5-mark "describe and explain" rewards (i) an accurate reading of the trend with figures and (ii) an access-based explanation, not just a restatement.

Describe the trend (about 2 marks). Telehealth's share of Medicare consultations was negligible in 2019 (about 1%), spiked sharply to a peak of about 35% in 2020, then settled at a markedly higher baseline than before the pandemic - declining year on year to about 19% by 2023 but remaining roughly nineteen times the pre-2020 level. Quote the 2019 start, the 2020 peak and the 2023 endpoint, and name the shape (sharp spike then partial decline to a raised plateau).

Explain with access (about 3 marks). The 2020 spike reflects the permanent expansion of MBS telehealth items during COVID-19, which removed the travel and work-time barriers that previously limited access, especially for rural and remote patients and for mental-health continuity. The partial decline after 2020 reflects a return to in-person care once lockdowns eased, but the raised plateau shows telehealth became a durable access channel rather than a temporary measure. Note the equity caveat: this improved access clusters with those who already have broadband, devices and digital literacy, so the average gain can mask a widening digital divide.

Marking spine: accurate trend with figures and shape (2), an access explanation tied to the MBS funding change (2), the equity/digital-divide caveat (1). Pure description with no access concept, or an explanation that never refers to the data, caps at 3. (Figures are an ExamExplained dataset modelled on the documented MBS telehealth surge from 2020; treat as illustrative.)

core6 marks
Explain how big data is used to identify and address health inequities in Australia, using a named example.
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A 6-mark "explain... using a named example" needs a definition, a named Australian tool, and a causal chain from data to action - not just a list.

What big data is here (about 1 mark)
Aggregated, often linked data sets (e.g. connecting MBS, PBS, hospital and registry data) that let researchers and policymakers see patterns across the whole population that are invisible at the individual level.
Named example (about 2 marks)
The Australian Atlas of Healthcare Variation (Australian Commission on Safety and Quality in Health Care) maps how rates of procedures, prescribing and admissions (e.g. knee arthroscopy, antibiotic prescribing, caesarean section) vary by local area. Variation not explained by clinical need flags inequity or low-value care.
How it addresses inequity (about 3 marks)
The data itself becomes an intervention: by making geographic variation public it creates accountability, informs targeted policy and local clinical-governance work, and lets resources be directed to under-served areas. Other examples include AIHW's Australia's Health reporting and linked-data projects that quantify gaps for priority populations.

Marking spine: definition of big data in this context (1), a correctly named Australian tool (2), and an explained pathway from identifying variation TO addressing it (3). Naming a tool with no mechanism, or describing inequity with no data tool, stays mid-band.

core5 marks
Explain the concept of the 'digital divide' and assess how it affects the equity of digital health in Australia.
Show worked solution →

A 5-mark "explain and assess" rewards a clear definition plus a calibrated judgement, not just two lists.

Define the digital divide (about 1 mark)
The gap between those who can access and confidently use digital technology and those who cannot - driven by access to devices and data, internet coverage, digital literacy, language and disability.
Apply to digital health (about 2 marks)
Telehealth, patient portals and wearables deliver their benefits mainly to people who already have broadband, a device, English-language confidence and digital health literacy. People who are older, on lower incomes, in remote areas, or who speak a language other than English at home are systematically less likely to use a portal, sustain a video consult on mobile data, or maintain a wearable.
Assess (about 2 marks)
Digital health raises average access and outcomes but can WIDEN the very inequity it aims to reduce unless it is explicitly designed for priority populations. The equity-aware response is proportionate universalism: a universal digital expansion PLUS targeted supports (digital navigators, in-language materials, captioning, continued investment in the rural physical workforce). Judgement: net positive, but only with explicit equity design.

Marking spine: definition (1), application to named groups (2), and a calibrated judgement using the proportionate-universalism framing (2). A "technology is good for everyone" answer with no divide, or a divide with no judgement, caps mid-band.

exam12 marks
Evaluate the impact of digital health and big data on health outcomes, access and equity in Australia. In your answer, refer to specific technologies, named examples and current data.
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A 12-mark "evaluate" extended response needs a sustained, two-sided argument that WEIGHS benefits against costs and reaches a calibrated judgement - with specific technologies, named Australian examples and data carrying a year - not a description of each technology in turn.

Band 6 PLAN.

Thesis: Digital health and big data have clearly raised the AVERAGE level of access and outcomes in Australia, but their net effect on EQUITY is conditional: they widen the gap for priority populations unless explicitly designed against the digital divide, so the honest judgement is "a powerful net positive that must be equity-engineered, not assumed".

Argument 1 - access and outcomes have genuinely improved. Evidence: permanent MBS telehealth from 2020 removed travel and work-time barriers (telehealth went from about 1% of consultations pre-2020 to a sustained raised baseline); My Health Record reduces duplicate testing and medication error; NDSS-subsidised CGMs transformed Type 1 diabetes self-management. Mechanism: information at the point of care and care delivered without travel.

Argument 2 - big data turns data into a system-level intervention. Evidence: the Australian Atlas of Healthcare Variation (Australian Commission on Safety and Quality in Health Care) maps unwarranted geographic variation; AIHW reporting and linked MBS-PBS-hospital data quantify gaps. Mechanism: visibility creates accountability and targets resources to under-served areas - addressing inequity.

Argument 3 (the counter-weight) - the digital divide and privacy costs. Evidence: benefits cluster with those who already have broadband, devices, English-language confidence and digital health literacy; older, lower-income, remote and CALD Australians are less able to use portals or sustain video consults. Privacy: centralised records concentrate breach risk and raise consent and secondary-use concerns (regulated by the OAIC and the Australian Digital Health Agency). Mechanism: a rising average can mask a widening gap.

Judgement: on balance digital health is a strong net positive for outcomes and average access, but its equity effect is NOT automatic; proportionate universalism (universal expansion plus targeted supports - digital navigators, in-language materials, rural workforce) is what converts it from a gap-widening force into a gap-closing one.

Model paragraph (Argument 3 - the counter-weight). The case for digital health is real, but a top evaluation must weigh it against the digital divide, because the same technologies that raise the average can quietly widen the gap. Telehealth, patient portals and wearables deliver their benefits chiefly to people who already have reliable broadband, a suitable device, English-language confidence and the digital health literacy to navigate them. People who are older, on lower incomes, living remotely, or who speak a language other than English at home are systematically less likely to install a wearable, hold a video consult on limited mobile data, or sustain engagement with My Health Record - so an intervention pitched as universal can deepen the very inequity it set out to reduce. Layered on top is a privacy cost: a centralised national record concentrates breach risk and raises consent questions around sensitive items, which is why the Office of the Australian Information Commissioner and the Australian Digital Health Agency carry explicit oversight roles. The implication is not to abandon digital health but to engineer it for equity - proportionate universalism, in which a universal digital expansion is paired with digital navigators, in-language materials, captioning and continued investment in the rural physical workforce - so that the rising average lifts priority populations rather than leaving them behind.

Marker's note: markers reward a sustained EVALUATIVE thesis that genuinely weighs benefits against costs (not a description of each technology); specific named technologies (My Health Record, MBS telehealth, CGMs, the Atlas of Healthcare Variation); current data carrying context/year (telehealth's surge from 2020; the ~1% to raised-baseline shift); explicit treatment of BOTH the digital divide AND privacy; and a calibrated judgement using proportionate universalism. A technology-by-technology description, an all-positive "tech is great" answer, or claims with no Australian specificity cannot reach the top band.

Practise this

Sources & how we know this

ExamExplained