Keona Health has released practical ROI guidance for nursing leaders, patient access directors, and healthcare operations teams evaluating the true cost of manual triage processes. The analysis examines the operational and financial considerations associated with both manual and AI-supported triage workflows, drawing on Keona Health customer data and the company's experience working with healthcare organizations.
The guidance arrives at a time when healthcare organizations are facing compounding pressure on patient access operations. Staffing shortages, rising call volumes, and increasing clinical complexity have exposed structural weaknesses in triage workflows that were not designed to scale. For many organizations, the cost of those weaknesses remains invisible until it surfaces as an avoidable emergency department visit, a documentation error, or a staff turnover event.
The recently published guidance includes a before-and-after performance comparison, a breakdown of the cost centers most affected by outdated triage infrastructure, and a Triage ROI Calculator that organizations can use to estimate savings based on their current call volume and staffing model. It is designed for nursing and operations leaders who want a structured way to quantify triage performance and evaluate the case for investment.
When non-clinical staff handle calls that require clinical judgment, consequences compound across departments. Organizations relying on paper-based triage protocols frequently experience inconsistent clinical decisions, extended onboarding timelines, and elevated downstream risk. Healthcare organizations relying on manual triage protocols frequently report extended nurse onboarding timelines before staff reach independent proficiency. In high-volume patient access environments where staffing capacity is already constrained, that delay creates operational drag that compounds across every shift.
Misclassified calls in these environments can generate avoidable emergency department visits, documentation errors, unnecessary callbacks, and liability exposure. These outcomes are structural byproducts of workflows that were not designed to scale. When triage decisions depend on the judgment of undertrained or inexperienced staff working from paper protocols, the margin for error is wide, and the downstream consequences are difficult to contain.
“These are not isolated inefficiencies,” said Stephen Dean, COO of Keona Health. “These failures are caused by structural problems. A manual triage model is not designed to scale efficiently.”
The clinical stakes of triage accuracy are significant. A 2024 evidence-based review published in the Journal of Emergency Nursing reported human triage accuracy ranging from approximately 59% to 82%, with performance varying significantly based on clinician experience, environment, and case complexity. According to Keona Health's internal data, AI-assisted triage has demonstrated an accuracy rate of 93% in directing patients to the appropriate level of care. At volume, that gap translates into meaningful clinical and operational risk.
AI-supported triage systems address the workflow gaps that manual processes leave open. According to Keona Health customer data, organizations that have implemented AI-guided triage have reported measurable operational improvements within 90 days. Observed outcomes include a 20% to 30% reduction in call handling time, documentation time reductions of up to 50%, reduced nurse onboarding timelines with staff reaching independent proficiency in as little as 2 to 3 weeks, and observed reductions in unnecessary emergency department referrals following implementation.
“Healthcare call centers are not only experiencing a staffing problem. They're facing a workflow problem,” said Stephen Dean. “When triage decisions depend on paper binders and non-clinical judgment calls, you're not managing risk. You're absorbing it.”
These outcomes reflect a broader pattern Keona Health has observed across its customer base: organizations that modernize triage infrastructure do not simply reduce cost per call. They reduce systemic clinical risk, improve staff retention by lowering cognitive burden on nurses, and create a foundation for scalable patient access operations. The cost of manual triage is not limited to the triage encounter itself; it accumulates in downstream care coordination, staff turnover, documentation remediation, and avoidable utilization.
The full Nursing Triage ROI analysis, including the ROI Calculator, is available at KeonaHealth.com. Nursing directors and operations leaders can use the calculator to generate estimates based on their organization's current call volume and staffing model.
