To develop and psychometrically test the triage decision-making instrument, a tool to measure Emergency Department Registered Nurses decision-making. Five phases: (1) defining the concept, (2) item generation, (3) face validity, (4) content validity and (5) pilot testing. Concept definition informed by a grounded theory study from which four domains emerged. Items relevant to the four domains were generated and revised. Face validity was established using three focus groups. The target population upon which the reliability and validity of the triage decision-making instrument was explored were triage registered nurses in emergency departments. Three expert judges assessed 89 items for content and domain designation using a 4-point scale. Psychometric properties were assessed by exploratory factor analysis, following which the names of the four domains were modified. The triage decision-making instrument is a 22-item tool with four factors: clinical judgement, managing acuity, professional collaboration and creating space. Focus group data indicated support for the domains. Expert review resulted in 46 items with 100% agreement and 13 with 66% agreement. Fifty-nine items were distributed to a convenience sample of 204 triage nurses from six hospitals in 2019. The Kaiser-Meyer-Olkin measures indicated that the data were sufficient for exploratory factor analysis. Bartlett's test indicated patterned relationships among the items (X 2 (231) = 1156.69). An eigenvalue of >1.0 was used and four factors explained 48.64% of the variance. All factor loadings were ≥0.40. Internal consistency was demonstrated by Cronbach's alphas of .596 factor 1, .690 factor 2, .749 factor 3 and .822 for factor 4. The triage decision-making instrument meets the criteria for face validity, content validity and internal consistency. It is suitable for further testing and refinement. The instrument is a first step in quantifying triage decision-making in real-world clinical environments. The triage decision-making instrument can be used for targeted triage interventions aimed at improving throughput and staff education. Dr. Tak Fung who is a member of the research team is a statistician. Development, validation and assessment of instruments/scales. Descriptive statistics. STROBE cross-sectional checklist. The TDI makes the complexity of triage decision-making visible. Identifying the influence of decision-making factors in addition to acuity that affect triage decisions will enable nurse managers and educators to develop targeted interventions and staff development initiatives. By extension, this will enhance patient care and safety.