Reading the heart's warning signs through emergency department ECG orders
When influenza circulates widely each winter, hospitals brace for more than respiratory admissions. Cardiologists and emergency physicians across Melbourne, Sydney, and Perth have long observed a parallel rise in acute coronary syndrome presentations during the weeks when influenza-like illness peaks. This pattern has been documented in Australian and Northern Hemisphere cohorts, and it provides a compelling setting for syndromic surveillance: a way to detect surges in cardiac events linked to influenza activity without waiting for laboratory confirmation of either the virus or the myocardial infarction.
Syndromic surveillance operates on signals that appear before definitive diagnoses are coded. For influenza, those signals include fever-cough absenteeism in schools, pharmacy sales of antivirals, and ambulance dispatches for breathing difficulty. For acute coronary syndrome, the most informative pre-diagnostic signal in many emergency departments is the order for a 12-lead electrocardiogram. ECG orders happen at the very first step of a cardiac work-up, often within minutes of a patient arriving with chest pain. When those orders climb during a week when influenza is also surging, public-health teams gain a window into an indirect but measurable burden of cardiac complications.
Australia's federated health system, with separate state health departments and a national surveillance framework coordinated through organisations such as the Australian Institute of Health and Welfare, is well placed to integrate these signals. Combining ECG order data from emergency departments with sentinel flu surveillance and pharmacy sales offers a richer picture than any single stream. The result is an early warning that can prompt hospitals, primary care, and aged-care facilities to prepare for an overlapping surge in respiratory and cardiac demand.
The cardiac shadow of influenza season
The link between influenza infection and acute coronary syndrome is biological, not merely coincidental. Influenza triggers a systemic inflammatory response, increases platelet aggregation, and destabilises atherosclerotic plaques. Population studies from Australia and overseas have repeatedly shown a measurable rise in myocardial infarction rates within the first one to two weeks after a respiratory viral infection. For older Australians and for Aboriginal and Torres Strait Islander people, who already carry a higher baseline burden of cardiovascular disease, the additional risk during peak flu weeks is clinically meaningful.
Seasonal patterns reinforce the connection. Influenza in southern Australian states typically peaks between June and August, while tropical regions such as far north Queensland may see activity across a longer window. When ED presentations for chest pain and troponin-positive admissions rise alongside general practice fever-cough consultations, the correlation is strong enough to act on. Syndromic surveillance formalises this clinical intuition, turning an observed pattern into a monitored, alertable signal.
The value of capturing this signal is twofold. It gives cardiology and emergency teams advance notice to adjust staffing, ensure bed availability, and reinforce triage protocols for high-risk patients. It also informs public-health messaging, encouraging earlier antiviral use in at-risk groups and reinforcing the secondary benefit of annual influenza vaccination in reducing cardiac events.
ECG orders as a pre-laboratory signal
Most modern emergency departments generate digital ECG orders as part of electronic medical record workflows. In a hospital such as the Royal Melbourne or Westmead, every chest pain presentation triggers a near-immediate ECG request, often before blood tests are drawn or a bed is assigned. The order itself, stripped of patient identifiers and aggregated by hour or shift, becomes a sensitive indicator of suspected cardiac presentations.
What makes ECG orders particularly useful for syndromic surveillance is their immediacy. Troponin results take an hour or more, and final diagnosis codes may not be assigned until discharge. By contrast, ECG orders appear in real time, allowing automated systems to count them, compare them against a rolling baseline, and flag statistically significant deviations. When those deviations align with rising influenza indicators, the signal becomes a candidate for a cardiac-influenza alert.
Implementing this requires close collaboration between emergency physicians, cardiology, IT teams, and the public-health epidemiologists who manage the surveillance platform. Each ED must define a consistent way to identify an ECG order linked to chest pain or cardiac-sounding complaints, excluding pre-operative or routine screening ECGs. Once defined, the data feed can be automated, with daily counts streamed to a central dashboard.
Building the detection pipeline
A robust pipeline begins with data extraction from the hospital information system. ED ECG orders are filtered by presenting complaint, age group, and arrival mode, then aggregated into hourly or four-hourly bins. These counts are compared with a historical baseline derived from the same hospital over the previous two to three years, adjusted for day of week, public holidays, and school terms. The latter is particularly relevant in Australia, where school holiday periods shift patient mix and demand.
Statistical algorithms such as the modified Farrington method or adaptive Poisson regression generate an expected range, and observed counts above a threshold trigger an alert. The alert is then evaluated in context: is influenza activity rising at sentinel GP clinics? Are pharmacy chains such as Chemist Warehouse reporting higher sales of oseltamivir or ibuprofen combination products? Are school absenteeism feeds from New South Wales or Victorian education departments showing increased fever-cough notes? When several streams move together, confidence in a true surge increases.
A useful reference for related multi-channel approaches is this analysis of monitoring-influenza-vaccination-coverage-using-syndromic-signals-of-vaccine-preventable-disease-decline, which illustrates how vaccination uptake can be inferred indirectly through declining disease signals. The same logic applies when ECG orders substitute for confirmed myocardial infarction counts.
Calibration against Australian hospital data
Calibration matters. A 20 percent rise in ECG orders during a quiet influenza week may reflect a change in triage protocol or a software upgrade, not a true surge. Australian surveillance teams typically spend several seasons tuning baselines, accounting for hospital-specific factors such as catchment population, cardiology service availability, and proximity to major events. Royal Adelaide and Sir Charles Gairdner hospitals, for example, serve very different demographic catchments and will show different baseline cardiac volumes.
Local realities shape signal interpretation. Pharmacies in remote Western Australia, often supplied through the Royal Flying Doctor Service or by air freight, may show delayed antiviral restocking that distorts pharmacy-surveillance streams. Indigenous health services in the Northern Territory may see different peak timings due to household crowding and mobility patterns. Calibration means working with these realities rather than smoothing them away, ensuring alerts are meaningful for the populations they are meant to protect.
Validation is equally important. Comparing predicted and observed cardiac admissions during past influenza seasons helps refine sensitivity and specificity. If a system fires too often, clinicians ignore it. If it fires too rarely, it adds little value. The goal is a steady, trusted rhythm of alerts that integrate with existing hospital command structures, such as the daily situational awareness meetings held by state health departments during winter.
Cross-channel validation and confounders
No single signal is reliable on its own. Heatwaves in Adelaide or Brisbane drive up ED presentations for a range of conditions, including cardiac events in older adults. Bushfire smoke seasons, increasingly part of the Australian summer-to-autumn calendar, can mimic or mask influenza-related respiratory and cardiovascular strain. Cross-channel validation against temperature, air quality, and pollen data keeps the signal specific.
Pharmacy surveillance adds another useful layer, though interpreting it during influenza peaks requires care. Sales of cough and cold mixtures spike for many reasons, and stockpiling behaviour around long weekends or natural disasters can distort counts. Pairing pharmacy data with school absenteeism feeds, as described in resources on school absence data, helps filter out background noise and highlight clusters that genuinely reflect circulating infection.
For ECG-specific analysis, confounders include sporting events that draw large crowds and transiently increase presentations, hospital accreditation visits that may shift workflow, and media coverage of high-profile cardiac events that heightens public awareness. None of these invalidate the signal, but they require careful annotation. A well-maintained surveillance dashboard treats these confounders as contextual metadata rather than noise to be removed.
From alert to action in emergency departments
An alert is only as useful as the response it triggers. In a mature Australian syndromic surveillance system, an ECG-and-influenza alert would prompt emergency department directors to review staffing rosters, ensure rapid troponin testing capacity, and reinforce clinical pathways for high-risk presentations. Pharmacy wholesalers might be notified to confirm antiviral stock, and general practitioners in the catchment could receive a brief advisory encouraging earlier review of patients with chest discomfort during flu season.
The downstream effects reach aged care. Influenza outbreaks in residential aged-care facilities are a recurring winter challenge, and cardiac complications among frail residents are a major driver of mortality. A timely alert lets facilities preemptively review care plans, ensure aspirin and statin availability, and coordinate with local hospitals to streamline transfers when needed. School-based signals can also guide parental communication, reminding families that children with congenital heart disease or severe asthma warrant prompt review if influenza circulates in their classroom.
Operationalising the alert requires governance. Each hospital and health service needs a written protocol describing who receives the alert, what thresholds warrant action, and how feedback flows back to the surveillance team. Without this, even a perfectly tuned signal stalls in an inbox.
Every winter, the quiet rise in ECG orders tells a story that laboratory data alone cannot. By treating the emergency department's first move in a cardiac work-up as a public-health signal, Australia can integrate cardiac and respiratory surveillance in ways that protect the most vulnerable during the season when risk converges. Explore the full range of syndromic signals shaping early outbreak detection at syndromic-surveillance.net, and consider how your service or facility might contribute data to strengthen the national picture.