Month: August 2026

Lab data flows through your health system every hour of every day, from inpatient units, ambulatory clinics, pre-surgical screenings, and reference labs. Most organizations lack the infrastructure to act on that stream the moment it matters.

So care gaps persist. Not because clinicians lack skill or dedication, but because the signal is buried under volume. A pre-surgical patient’s low hemoglobin. A diabetic patient overdue for screening. A redundant panel ordered three times in a week. Each of these lives inside a data set too large for any human team to monitor in real time.

By the time a gap surfaces through manual review, it has often already widened: the anemic patient reaches the OR untreated, the chronic condition escalates, the unnecessary test has already been billed and forgotten. In my conversations with health system leaders across patient blood management, anemia, women’s health, and lab stewardship programs, the same story repeats. Up to 30% of all lab tests and blood transfusions performed in the United States are considered unnecessary or avoidable. That represents billions of dollars in wasted resources and exposes patients to potential complications and delayed care. To solve it, healthcare leaders must shift from retrospective reporting to proactive diagnostic stewardship.

What Lab Intelligence Actually Does

The pattern is consistent: data exists, but no process connects it to action at the right moment. Clinical IQ closes that gap by ingesting EHR data, lab results, and full clinical history, then applying patented AI to interpret that information the way an expert clinician would, at machine scale and machine speed. Instead of waiting for a person to notice a risk, it continuously analyzes data, flags what matters, and triggers coordinated action inside workflows your teams already use.

That intelligence focuses on four areas where gaps most often hide.

Four Areas Where Care Gaps Hide

1. Anemia management for pre-surgical patients. Preoperative anemia is a common and preventable driver of poor surgical outcomes, raising infection risk, lengthening stays, and increasing transfusion rates. Identifying and treating these patients before surgery typically requires a time-intensive, multidisciplinary effort across the EHR, phone, and paperwork. Lab intelligence automates that entire pathway, identifying affected patients, prioritizing the most urgent cases, and initiating treatment coordination well before they reach the hospital door.

2. Maternal health and obstetric risk. Risk during pregnancy and the postpartum period, including hemorrhage, hypertensive disorders, and thromboembolic events, can escalate rapidly. Most care teams still rely on point-in-time assessments at scheduled visits. Lab intelligence screens patients for risk as soon as pregnancy is documented in the EHR, capturing signals from the first trimester and updating risk scores continuously against ACOG-defined thresholds. Every alert surfaces with ICD-10-coded recommendations and named guideline citations from ACOG Practice Bulletins and SABM anemia thresholds, so teams can act with confidence, not just awareness.

3. Lab test utilization. A significant share of lab orders are unnecessary, redundant, or outdated. Lab intelligence analyzes ordering patterns across providers, specialties, and locations to identify exactly where overutilization is happening and why, giving teams the visibility to eliminate waste without compromising tests that genuinely guide care.

4. Chronic condition screening. Chronic conditions demand ongoing monitoring, but screening gaps accumulate quietly when data sits in disparate systems. By cross-referencing lab values and clinical history, the Clinical IQ platform flags patients who are overdue, at risk, or trending toward complications, enabling proactive intervention rather than reactive response.

From Alert to Action

Most clinical decision support stops at the alert. Lab intelligence goes further. When a pre-surgical patient with untreated anemia is identified, it does not simply raise a flag. It initiates evidence-based treatment recommendations, supports care coordination and insurance authorization, and schedules follow-up labs post-optimization, all automatically, inside existing workflows. Clinicians stay in control of the decision. The platform absorbs the coordination work that causes gaps to widen.

Outcomes Across Deployments

Across health system deployments, Clinical IQ consistently delivers measurable results:

• 40% improvement in care gap closure rates, moving overdue and at-risk patients back into active care
• 30-50% decrease in unnecessary blood transfusions, reducing patient risk and pressure on a scarce resource
• 70% reduction in inappropriate test ordering from baseline
• $500K to $2M in annual test utilization savings per health system

These outcomes build on each other. Fewer unnecessary transfusions mean safer patients and lower acquisition costs. Fewer inappropriate tests mean faster, more accurate results and lower spend. Higher care gap closure means stronger quality scores and better patient outcomes.

Built Into Your EHR

Technology only delivers value if your teams use it. Clinical IQ integrates natively with Epic and athenahealth, with no new logins, no parallel systems, and no added clicks. Insights and automated actions appear where teams already work, keeping adoption high and reducing change management friction. Most health systems see measurable ROI within 90 days of go-live.

Frequently asked questions

Healthcare systems are generating more data than ever before. Every day, millions of data points, from test results and utilization patterns to patient clinical histories, flow through laboratories.

Yet despite this volume, much of the intelligence remains locked away in disconnected systems and manual workflows. That fragmentation leads to a costly and persistent problem: clinical waste that erodes both patient outcomes and health system margins.

In my conversations with health system leaders across patient blood management, anemia, women’s health, and lab stewardship programs, the same story repeats. Up to 30% of all lab tests and blood transfusions performed in the United States are considered unnecessary or avoidable.^1,2 That represents billions of dollars in wasted resources and exposes patients to potential complications and delayed care. To solve it, healthcare leaders must shift from retrospective reporting to proactive diagnostic stewardship.

The cost of clinical variability

Clinical variability occurs when there is a lack of standardized, evidence-based, data-driven decision-making across providers and locations. Without clear visibility into ordering patterns, health systems struggle to identify duplicate testing, inappropriate workups, and excessive blood utilization.

An incomplete anemia workup during pregnancy might lead to repeated patient visits and delayed surgical procedures. An unnecessary blood transfusion introduces inherent clinical risks and added cost. The challenge is rarely a lack of clinical guidelines, since organizations like the AABB provide robust frameworks.³ What health systems lack is the ability to surface those guidelines seamlessly at the point of care, where they can actually change a clinician’s next decision.

Sources: Zhi et al., PLOS ONE 2013; Shrank et al., JAMA 2019; van der Sijs et al., JAMIA 2006; hc1 client results.

The challenge is rarely a lack of clinical guidelines. It is the inability to surface them at the moment they can change a clinician’s next decision.

Why traditional stewardship programs fall short

Most stewardship programs run on a monthly or quarterly review cycle. A utilization committee reviews aggregate data, identifies patterns, and issues guidance to department chairs. That model has three structural failures.

Latency. Clinical decisions happen in real time. A committee that meets monthly cannot interrupt a transfusion ordered this morning for a stable patient who does not meet evidence-based thresholds.

Visibility gaps. Duplicate testing happens across departments and facilities inside the same system. Without integrated cross-system data, a morning ICU team orders a panel the overnight team drew three hours earlier.

Alert fatigue. Stewardship alerts delivered through the EHR are routinely dismissed. Research published in JAMIA found clinicians overrode 90 to 96% of drug safety alerts.⁴ When alerts fire indiscriminately, the ones that matter disappear into the noise.

Introducing clinician-built AI

To address these challenges, hospitals require more than generic analytics dashboards. They need actionable, agentic intelligence built around the clinical questions that actually move outcomes and cost.

hc1 Clinical IQ™ is designed specifically to translate predictive intelligence into proactive patient care. Across four service lines, the platform leverages patented, clinician-built AI algorithms to continuously analyze EHR data, lab results, and patient records. It identifies anomalies and flags risks before they impact patient outcomes, and before they impact the bottom line.

Instead of waiting for a monthly utilization committee meeting to review stale data, clinical leaders receive near real-time insights. That allows organizations to monitor inappropriate testing, track duplicate test reductions, and measure the impact of their stewardship programs on both patient safety and the bottom line.

Moving from insight to automated action

Identifying waste is only the first step. The true value of hc1 Clinical IQ™ lies in its ability to automate workflows, close care gaps, and drive intervention where it matters most, at the bedside.

When the AI detects an incomplete diagnostic workup or an overdue screening, it triggers automated actions. That can include sending a secure SMS to a patient, initiating an insurance authorization, or scheduling a follow-up laboratory appointment. By handling the manual administrative burden, the platform allows clinical teams to focus entirely on patient care.

The outcomes are highly measurable, and they matter to both the CMO and the CFO. Health systems utilizing this approach have documented a 30% to 50% decrease in blood transfusions, improved compliance with evidence-based guidelines, and an average of $500K to $2M in annual savings through unnecessary test elimination. A health-system-wide patient blood management program studied in Transfusion reported a 28% reduction in units transfused alongside a significant improvement in patient mortality, which is consistent with what we see in the field.⁵

A strategic asset for health systems

Diagnostic data is a strategic asset, not an operational byproduct. When properly refined and integrated, it has the power to close care gaps, personalize treatment, and significantly improve hospital margins.

That is the thesis behind our Clinical IQ suite. By embracing AI-powered intelligence across anemia, patient blood management, women’s health, and lab stewardship, healthcare systems can eliminate the friction of disconnected workflows, standardize clinical practice, and ensure every patient receives the precise care they need, at a cost the system can sustain.

Frequently asked questions