But this promise will only be realized if clinicians trust and act on the tool’s outputs.
Without strong clinical accuracy, digital triage risks producing duplication of work, undermining trust, and ultimately failing. In short: accuracy is not a “nice to have.” It is the core of a triage tool’s value.
One of the primary motivations for automating triage is to reduce clinician workload: fewer unnecessary calls or appointments, less time on low-acuity cases, more consistent triage decisions, faster routing to the right care level. In theory this should free up resources for higher-value work.
A recent systematic review of patient-facing online triage tools in primary care found exactly this: clinicians frequently perceived the digital tools as an “additional step” rather than a replacement of existing workflow. In many cases clinicians hesitated to make decisions based solely on the online report, due to concerns over incomplete or low-quality information, leading to follow-up calls or appointments. PMC+1In practice, however, if triage outputs are not trusted, clinicians often duplicate the process — repeating assessments by phone or in person, or overriding automated recommendations. That negates any efficiency gains; in some cases, it increases workload.
In other words: a poorly trusted triage tool can become a liability — triggering duplication, inefficiency, and clinician frustration — rather than delivering the resource savings it was intended for.
What builds or erodes clinician trust in triage tools? Studies — including recent investigations from Sweden — make clear that perceived accuracy and clinical alignment are central.
In a qualitative study of health professionals and patients using AI-based triage in Swedish primary care, both groups emphasized that trust depended heavily on (1) provision of accurate patient information and (2) alignment with clinical expertise. Frontiers+1
If the triage outcome diverges from what a clinician would expect — especially in safety-critical or time-sensitive situations — confidence in the system erodes rapidly. Indeed, legal and liability concerns reinforce this: if a decision support system errs, clinicians fear they may be held responsible. OUP Academic+1
Moreover, beyond accuracy per se is explainability and “clinical sense-making.” Research shows that even highly sophisticated decision-support systems (CDSSs) must balance predictive performance with transparency. When clinicians cannot understand or rationalize why a system made a recommendation, trust drops — even if the system is statistically “right.” arXiv+1
Thus, clinical accuracy — defined not only as correct prioritization or diagnosis, but also as proper escalation, safe recommendations, and alignment with real-world clinical reasoning — is the critical enabler of trust.
The Swedish case around 1177 illustrates starkly how belief in efficiency-driven triage can collapse without sufficient accuracy. The national telehealth and triage service 1177 has deployed digital symptom checkers and chat-based triage platforms across many regions, aiming to streamline primary-care access. JMIR Publications+2regionorebrolan.se+2
Despite early optimism, research confirmed that integration of the AI-based triage application into routine workflows was limited: organisational barriers, lack of clarity about roles, and insufficient trust meant that the innovation never became normalized. PubMed
Together, these findings show that when a triage tool fails to meet clinicians’ standards of clinical soundness, the result is not only under-use or partial use — but potential patient safety concerns and erosion of legitimacy.
The stakes go beyond inefficiency. In emergency or urgent-care settings, inaccurate triage can lead to undertriage (delayed care, deterioration) or overtriage (overloading emergency services, misallocation of scarce resources). A scoping review protocol published in 2025 recognises that emergency triage practice errors — many of them linked to triage decisions — remain a significant patient safety concern. ScienceDirect+1
Thus, a triage solution that is not clinically accurate may:
That outcome is the inverse of what purchasers hoped to achieve.
Given this, what should decision-makers in health systems prioritise when evaluating triage solutions? Among others:
In short: the best triage solution is not necessarily the “shiniest,” most feature-rich, or most automated — but the one clinicians trust, use, and integrate meaningfully into their workflows.
Digital triage holds great promise for improving access, easing demand pressure, and streamlining care delivery. But those benefits remain hypothetical until clinicians — nurses, GPs, emergency staff — trust and act on the outputs. Clinical accuracy is not a box to tick — it is the foundation of that trust. Without it, redundancy, duplication, under-use, or unsafe patient care may result.
As the experience of 1177 in Sweden demonstrates, a triage solution that fails to deliver reliable, clinically coherent, and safe outcomes may do more harm than good — even if it offers speed, convenience, or cost savings.
For health systems evaluating triage tools, the message is clear: prioritize clinical accuracy above all else.