At 2:30am on a Tuesday, an 82-year-old woman arrives in the emergency department (ED) by ambulance. She hasn’t fallen. She’s not short of breath. She isn’t obviously “sick” in the way EDs are trained to spot quickly. She’s confused. A little dehydrated. Her daughter says she “just isn’t right.”
The ED team begins the slow, careful work: blood tests, imaging, medication review, conversations with family, calls to the GP and the aged care provider. There’s a mental checklist of risks: delirium, infection, medication toxicity, unsafe discharge.
This patient will take hours -not because anyone is inefficient, but because the consequences of getting it wrong are enormous. On paper, it looks like a long stay. In reality, it’s high-stakes, complex care done properly. And yet our funding system struggles to recognise that difference.
The Story We Keep Telling Ourselves
For decades, the narrative around ED pressure has been simple: more people are coming, demand is rising, and the system can’t keep up. Funding has followed this story. We count patient arrivals. We reward throughput. We measure success by speed of how quickly they can be offloaded or discharged.
That may have worked well when emergency care was simpler. But today, EDs are not necessarily getting busier —they’re getting harder. Patients are older, sicker, and more socially vulnerable. They often have multiple chronic conditions, cognitive impairment, mental health needs, or fragile social supports. Discharging them safely can take as much work as admitting them.
Yet these demands don’t show up in headline attendance figures. They appear in clinician fatigue, access block, ambulance ramping, rising complaints, and the quiet accumulation of risk.
Why Current Funding Falls Short
Australia’s activity-based funding system brought transparency and discipline to hospital budgets. But in emergency care, its limitations are becoming increasingly obvious. This is because the model assumes that:
- All ED presentations are broadly comparable
- Time is a proxy for inefficiency
- Longer stays reflect poor flow
The trouble is that complex care doesn’t work like that. It involves uncertainty, coordination, communication, and judgment, most of which is invisible to existing funding formulas. The result therefore ends up quite perverse: because EDs caring for the most complex patients appear inefficient, even as they deliver exactly the care needed.
Three Shifts That Leaders Must Consider
Shift 1: Make complexity explicit
Funding models must recognise patient complexity directly, not infer it from crude metrics like length of stay. Frailty, multimorbidity, mental health needs, and social vulnerability should be named, measured, and weighted. When complexity is explicit, boards can plan for it, leaders can defend it, and funders can no longer ignore it.
Shift 2: Stop punishing time spent doing the right thing
Complex care takes time, and that is appropriate. Rushing decisions for frail older patients or those without safe discharge options hides risk. It is therefore important that the funding models are equipped to distinguish between what may be unnecessary delays versus the appropriate length of time needed for safe, high-quality care.
Shift 3: Acknowledge that EDs carry system gaps
EDs are the catchment for failures across the healthcare system when primary care isn’t accessible, when aged care collapses, and when mental health and disability supports are fragmented. Funding models need to reflect that complexity spans across all these systems and sectors. Which is why shared pools, bundled payments, and integration incentives are not optional models, they’re essential.
Aligning Funding with Complexity: Four Models That Work
If we accept that EDs are doing the hardest and/or high complexity work in the health system, current funding models need to evolve. We propose four practical models that can be implemented today to align funding with the reality of modern emergency care.
Model 1: Complexity-Adjusted Activity Funding
The concept
Instead of funding all ED presentations equally, funding is weighted by the complexity of the patient.
How it works
- Define measurable complexity metrics by developing frailty scores, chronic disease counts, mental health conditions, social vulnerability indexes.
- Assign funding weights to these factors. For example, a patient with high frailty and multiple chronic conditions could attract 1.5× the base ED funding.
- Pilot the model in select EDs, calibrate weights based on clinical outcomes and financial sustainability, then scale with ongoing monitoring.
Why it matters
This approach recognises the invisible work clinicians do —the thinking, the coordinating, and the managing risk — and ensures funding matches the equivalence of the effort required.
Model 2: Bundled Payments Across Care Settings
The concept
Complex patients rarely stay in the ED alone. Care spans multiple settings, from inpatient wards to community services, aged care, and primary care. Funding models that utilise bundled payments can effectively link these services financially to support continuity of care. This helps to avoid financial savings in one part of the system only being able to be realised at the cost of another part of the system.
How it works:
- Identify patient cohorts who require multi-setting care, e.g., frail older adults with multiple chronic conditions.
- Map the patients’ full care pathway and calculate the total cost across all involved services.
- Allocate a single bundled payment that is then shared across all responsible providers.
- Monitor outcomes, readmissions, and patient experience to ensure quality.
Why it matters
Bundled payments reduce the siloed “ED pays, community loses” problem and encourage providers to coordinate, share the risks as well as the gains, rather than simply focus on push patients through out of their system.
Model 3: Integrated System Incentives
The concept
Reward hospitals and community providers for safe, high-quality care, rather than just throughput.
How it works
- Define measurable outcomes such as safe discharge, reduced readmissions, and/or improved patient experience.
- Set targets and link financial incentives to achieving them.
- Evaluate regularly and adjust targets to ensure equity and sustainability.
Why it matters
Clinicians and organisations are motivated by outcomes. Incentives for integration encourage proactive care coordination, reducing the downstream risks that EDs absorb today.
Model 4: Workforce & Care Coordination Funding
The concept
Complex patients require expert teams. Funding must support the right skill mix, not just more beds or throughput.
How it works
- Map the roles needed: senior ED clinicians, allied health, mental health specialists, care coordinators.
- Allocate funding proportional to patient complexity and staffing requirements. Take into account the length of time and effort required by each role in quantifying.
- Integrate workforce funding into ED budgets explicitly rather than relying on general operating funds.
- Monitor impact on clinician workload, burnout, and patient outcomes to refine allocations.
Why it matters
Recognising the cost of expertise prevents burnout and ensures patients receive safe, high-quality care.
From Theory to Practice
Implementing these models requires pragmatism: start small, pilot in a few EDs, collect data, and refine. Engage clinicians, finance teams, policymakers, and patient representatives early. Leverage electronic health records and national datasets to measure complexity accurately. And crucially, align incentives so that doing the right thing — not just doing things fast — is financially supported.
Complexity isn’t seasonal. Frailty, multimorbidity, and social vulnerability are structural trends that will continue to intensify. Emergency departments aren’t inefficient, they’re doing the hardest work in the system under funding models designed for a simpler time. Until funding aligns with reality, ED pressure will keep being misdiagnosed, and the people carrying that pressure, both clinicians and patients, will continue to pay the price.
For a detailed exploration of implementing these models in real-world settings, read our White Paper here.
