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

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).

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.

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.

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.

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 owned ExamExplained dataset modelled on the documented MBS telehealth surge from 2020; treat as illustrative.)

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.

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.

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.