Key result
Using the ESC 0/1-h algorithm in low-risk patients in emergency primary care reduced health care costs by €1794 per patient and decreased length of stay by 18.9 hours compared to standard hospital management.
Why the study?
Hospital admissions of chest pain patients at low risk for ACS drive up costs and ED crowding, prompting evaluation of primary care emergency assessment.
Does assessing low-risk chest pain patients using the ESC 0/1-h algorithm in a primary care emergency setting improve cost-effectiveness compared to routine hospital management?
Observational (n=2,052)
No
Does assessing low-risk chest pain patients using the ESC 0/1-h algorithm in a primary care emergency setting improve cost-effectiveness compared to routine hospital management?
Effect estimate: Cost reduction of €1794 and QALY gain of 0.0005
Implementing the ESC 0/1-h algorithm for high-sensitivity troponin T in a primary care emergency setting for low-risk chest pain patients is highly cost-effective, significantly reducing healthcare costs and length of stay compared to routine hospital admission.
Supports primary care rule-out for low-risk patients; leaves open prospective implementation trials before practice change.
AIMS: Hospital admissions of patients with chest pain considered as low risk for acute coronary syndrome contribute to increased costs and crowding in the emergency departments. This study aims to estimate the cost-effectiveness of assessing these patients in a primary care emergency setting, using the European Society of Cardiology (ESC) 0/1-h algorithm for high-sensitivity cardiac troponin T, compared to routine hospital management. METHODS: A cost-effectiveness analysis was conducted. For the primary care estimates, costs and health care expenditure from the observational OUT-ACS (One-hoUr Troponin in a low-prevalence population of Acute Coronary Syndrome) study were compared with anonymous extracted administrative data on low-risk patients at a large general hospital in Norway. Patients discharged home after the hs-cTnT assessment were defined as low risk in the primary care cohort. In the hospital setting, the low-risk group comprised patients discharged with a non-specific chest pain diagnosis (ICD-10 codes R07.4 and Z03.5). Loss of health related to a potential increase in acute myocardial infarctions the following 30-days was estimated. The primary outcome measure was the costs per quality-adjusted life year (QALY) of applying the ESC 0/1-h algorithm in primary care. The secondary outcomes were health care costs and length of stay in the two settings. RESULTS: Differences in costs comprise personnel and laboratory costs of applying the algorithm at primary care level (€192) and expenses related to ambulance transports and complete hospital costs for low-risk patients admitted to hospital (€1986). Additional diagnostic procedures were performed in 31.9% (181/567) of the low-risk hospital cohort. The estimated reduction in health care cost when using the 0/1-h algorithm outside of hospital was €1794 per low-risk patient, with a mean decrease in length of stay of 18.9 h. These numbers result in an average per-person QALY gain of 0.0005. Increased QALY and decreased costs indicate that the primary care approach is clearly cost-effective. CONCLUSION: Using the ESC 0/1-h algorithm in low-risk patients in emergency primary care appears to be cost-effective compared to standard hospital management, with an extensive reduction in costs and length of stay per patient.
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Johannessen et al. (2022) conducted an observational in Low-risk chest pain / suspected acute myocardial infarction (n=2,052). ESC 0/1-h algorithm for high-sensitivity cardiac troponin T in emergency primary care vs. Routine hospital management was evaluated on Costs per quality-adjusted life year (QALY) (Cost reduction of €1794 and QALY gain of 0.0005). Using the ESC 0/1-h algorithm in low-risk patients in emergency primary care reduced health care costs by €1794 per patient and decreased length of stay by 18.9 hours compared to standard hospital management.
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