Building decision confidence with a chest pain triage algorithm

• Chest pain triage is not only a clinical challenge, it is also a direct determinant of hospital flow, bed capacity, financial performance, and patient trust
• The real opportunity lies not just in having cardiology guidelines, but in operationalizing them consistently under pressure through intelligent, workflow-integrated clinical decision support algorithms
• Well-designed chest pain triage algorithms act as a scalable “digital mentor”, strengthening diagnostic confidence in cardiology, reducing cognitive burden, and elevating care quality

Every day, Emergency Departments around the world face a familiar but formidable challenge: the patient who presents with chest pain. Behind that single symptom lies a spectrum of possibilities, from benign causes to life-threatening myocardial infarction. For clinicians, the task is urgent and high-stakes. For hospitals, it is operationally decisive. And for patients, it is often one of the most frightening moments of their lives.

Chest pain triage today is no longer defined by instinct and prolonged observation alone. High-sensitivity troponin assays, rapid rule-out protocols, and the latest European Society of Cardiology (ESC) guidelines have transformed what is possible in early diagnosis. The question is no longer whether we can detect myocardial injury quickly, but whether we can translate that capability into consistent, evidence-based decisions under real-world pressure.

In this discussion, Healthcare Transformers sat down with Evangelos Giannitsis to hear his frontline insights into what it truly takes to operationalize ESC-aligned chest pain algorithms, how chest pain triage algorithms can reinforce guideline adherence, and why rapid rule-out strategies are as much about system resilience as they are about diagnosis.

HT: From your perspective, what are the most significant challenges or pain points that healthcare professionals in the emergency department (ED) face when managing patients with chest pain?

Dr. Giannitsis: Chest pain is one of the most common reasons for ED presentations worldwide, yet it is also one of the most diagnostically complex. The first challenge is the non-specific nature of symptoms. Chest pain varies widely by age, sex, and comorbidities. Diabetic patients, for example, may have impaired pain perception. Patients on analgesics may not experience typical pain. Women and younger patients often present atypically, and many patients do not present with chest pain at all but with equivalents such as dyspnea, epigastric discomfort, diaphoresis, or heart failure symptoms.

From a diagnostic standpoint, history and an electrocardiogram (ECG) alone are insufficient. ECG lacks sensitivity and specificity, and while high-sensitivity cardiac troponin assays are now the gold standard, they introduce their own complexity. Troponin is highly sensitive and highly specific for myocardial injury, but not for myocardial infarction per se. Elevated troponin can reflect heart failure, pulmonary embolism, myocarditis, or other cardiac stress states. Interpreting troponin, therefore, requires clinical context and an understanding of kinetics, not just absolute values.

Operationally, the sheer volume of chest pain and dyspnea presentations creates constant pressure on ED throughput. EDs cannot afford six to nine-hour observation windows for every patient. Fast, accurate triage is essential to avoid crowding, delays, and downstream bottlenecks. This combination of diagnostic uncertainty, assay complexity, and time pressure represents a major cognitive and operational burden for ED clinicians.

HT: How can the latest European Society of Cardiology (ESC) guidelines help overcome these challenges?

Dr. Giannitsis: I am a strong supporter of guidelines because they provide an evidence-based anchor for decision-making. The ESC guidelines are grounded in robust clinical data and give clinicians a defensible framework for diagnosis and management, particularly in acute coronary syndromes.

That said, the challenge is not the existence of guidelines but their translation into daily clinical practice. Guidelines are detailed, assay-specific, and continuously evolving. Not every healthcare system has the same infrastructure, logistics, or financial capacity to implement them perfectly. Adherence often fails at the level of operational detail, where complexity meets real-world constraints.

When implemented well, however, the ESC guidelines enable earlier and safer rule-out or rule-in of myocardial infarction using high-sensitivity troponin-based algorithms. They reduce diagnostic ambiguity, support faster decision-making, and ultimately improve patient outcomes. The key is not just publishing guidelines, but also operationalizing them in a way that fits clinical workflows.

HT: As a seasoned leader, how do you manage a team of junior doctors to ensure they adhere to the ESC guidelines, especially for the rapid rule-out of Myocardial Infarction (MI)?

Dr. Giannitsis: In our setting, this is facilitated by structure and proximity. I lead a cardiology-run chest pain unit that manages all acute cardiac presentations. I conduct several rounds per day and personally review every case with the team. Each patient is discussed in detail, and junior doctors receive immediate feedback on their interpretation of ECGs, troponin kinetics, and guideline application.

A critical factor is rapid feedback. Our catheterization laboratory is adjacent to the chest pain unit, so when we decide on immediate coronary intervention, we often know within 30 minutes whether our decision was correct. This creates real-time quality control and accelerates learning. Without that feedback loop, clinical learning is slower and less precise.

In addition, our unit is audited regularly, and staff are already experienced in emergency and cardiac care. Guideline adherence becomes part of the culture, reinforced through daily practice rather than abstract teaching alone.

HT: What are the tangible downstream impacts of the ESC rapid rule-out guidelines on hospital operational flow and patient psychological well-being?

Dr. Giannitsis: The benefits are multi-layered and affect all stakeholders. For patients, rapid rule-out protocols shorten the length of stay in the Emergency Department. Patients are either safely discharged earlier or transferred sooner to an inpatient bed, reducing anxiety, uncertainty, and discomfort. Faster resolution of uncertainty has a direct positive impact on psychological well-being.

For clinicians and staff, reduced ED length of stay alleviates crowding, decreases monitoring and observation time, and frees clinical capacity. This translates into more efficient use of staff resources and less operational stress.

For hospitals and payers, accurate and early diagnosis improves coding, reimbursement, and resource allocation. It prevents missed infarctions, avoids unnecessary admissions, and frees beds for patients who truly need specialized procedures. In systems with limited bed capacity, avoiding unwarranted admissions is critical to maintaining access to advanced interventions and preserving institutional capability.

HT: How does the chest pain triage algorithm help?

Dr. Giannitsis: The chest pain triage algorithm is directly derived from the ESC guidelines. It is a knowledge-based clinical decision support approach that translates guideline logic into structured, step-by-step triage. Each decision point can be traced back to its evidence base, ensuring transparency and medico-legal robustness.

By standardizing interpretation of troponin values, timing of measurements, and kinetic changes, the algorithm reduces variability in practice. It ensures that patients are appropriately ruled out, ruled in, or observed according to guideline-recommended pathways, rather than ad hoc judgment alone.

HT: How can clinical decision support (CDS) algorithms and tools, based on the ESC guidelines, aid in the risk stratification of complex chest pain patients?

Dr. Giannitsis: ESC-aligned CDS tools act as cognitive support systems. They automatically calculate absolute and relative troponin changes, integrate timing of blood draws, and apply assay-specific thresholds. This removes a significant mental load from clinicians, particularly in high-pressure ED environments.

These tools are not limited to fast protocols. They can also interpret later measurements when institutions still rely on three- or six-hour pathways. Importantly, they enforce guideline-recommended third measurements when initial results are inconclusive, a step that is frequently missed in routine practice.

By ensuring correct interpretation and protocol adherence, CDS tools improve risk stratification across the entire spectrum of suspected acute coronary syndrome patients.

HT: How do you view CDS tools and algorithms helping junior doctors, especially in the rapid rule-out of myocardial infarction and in building confidence in decision-making?

Dr. Giannitsis: High-sensitivity troponin has both diagnostic and prognostic value. Very low troponin levels are associated with a very low short-term risk of death or infarction. For junior physicians, this high negative predictive value provides reassurance and confidence.

CDS tools function as a form of digital mentorship. They guide clinicians through complex decision pathways, reinforce evidence-based practice, and reduce uncertainty. While some advocate combining troponin protocols with multiple clinical risk scores, this can sometimes add confusion rather than clarity. In practice, experienced clinicians rely heavily on clinical judgment and troponin kinetics, using CDS tools to support, not replace, that judgment.

The result is safer, more confident decision-making, particularly for less experienced physicians.

HT: Where do you see CDS algorithms for cardiology evolving over the next few years?

Dr. Giannitsis: I see a very strong future for CDS tools. Guideline adherence is suboptimal across almost all medical specialties, not just cardiology. Well-designed CDS systems can improve adherence, quality of care, efficiency, and resource utilization.

However, quality matters. Many tools on the market are poorly designed, time-consuming, or clinically irrelevant. Effective tools must be intuitive, fast, transparent in their evidence base, and integrated into existing workflows. Alarm fatigue must be minimized, and outputs must be clear and actionable.

Looking ahead, the most promising evolution will combine knowledge-based systems with artificial intelligence. AI has the potential to identify complex patterns in ECGs, imaging, and laboratory data that exceed human cognitive capacity. When combined with guideline logic and integrated laboratory and clinical data, these tools can significantly enhance acute cardiac care.

HT: What other kinds of digital health integration might be needed in acute care settings?

Dr. Giannitsis: Beyond cardiology, similar CDS approaches and digital health tools are needed across acute care, including hypertension, endocrinology, nephrology, and diabetes. The greatest value will come from systems that integrate laboratory data, electronic health records, timing information, and clinical context into a single decision environment.

The goal is not to replace clinicians, but to support them. High-quality digital solutions can reduce cognitive burden, improve consistency, and enable clinicians to focus on what matters most: clinical judgment, patient communication, and timely care.