Clinical laboratories generate vast amounts of patient data every day, but most of that diagnostic potential goes unused. When a test result arrives without systematic comparison to evidence-based guidelines, the lab ends up a reporter of facts rather than a predictor of risk.
A 2024 study of over 84,000 patient records at a large multi-state reference laboratory examined two common clinical scenarios: diabetic kidney disease screening and anemia workup. The data showed large measurable gaps in guideline-adherent follow-up testing.
There is growing pressure for clinical laboratories to help close care gaps, not just report results. That, however, depends less on better algorithms and more on whether referring clinicians know the insight exists and develop the habit of requesting it.
From clinical lab results to actionable population health insights
A single lab result answers a narrow question. When compared with what should have been ordered and benchmarked against population-level patterns, it becomes an early warning signal. A lab that flags testing gaps in real time gives clinicians a way to use the patient data they accumulate, independent of fragmented EMR systems.
However, most labs operate on an order-and-report model. A clinician orders a test, the lab performs it, and a result comes back. What happens next and whether the appropriate follow-up is triggered stays invisible to the lab. Algorithmic analysis of historical and real-time testing records changes this, turning the clinical lab into an active contributor to population health management.
What lab data reveals about population health
The 2024 study analyzed more than 84,000 records at AccuReference Medical Laboratory, a CLIA-certified, CAP-accredited reference lab operating across multiple states. Vivica LabReports was used to compare the data against US clinical guidelines, with a focus on measures defined by the Healthcare Effectiveness Data and Information Set (HEDIS), which assess healthcare quality and effectiveness.
Among 26,949 patients with elevated A1C and normal creatinine, only 4,037 patients (15%) received an albumin-to-creatinine ratio test. This test is the frontline screen for microalbuminuria, the earliest marker of kidney damage, and both the American Diabetes Association and HEDIS recommend it for this population. Among the patients who did get tested, 46% of males and 40% of females showed kidney damage, a combined positivity rate near 43%. Applying that rate to the 22,912 untested patients suggests roughly 9,850 people may carry undetected early kidney disease.
A second cohort of 57,310 patients had hemoglobin levels below the anemia threshold. Of these, 85% did not receive any of the recommended follow-up tests for iron, ferritin, or B12. This is clinically significant because misdiagnosing the type of anemia can mask more serious conditions, including occult gastrointestinal bleeding.
The clinical lab as a predictive engine
EMR-based gap tools depend on complete, standardized data entry across every provider a patient sees. That data is often fragmented. Clinical laboratory data is structured and centralized by design. Every result is coded, timestamped, and patient-linked in a consistent format. This gives lab-based analytics a structural edge over EMR-based tools at population scale.
Closing the gap between lab insights and clinical action
Surfacing a testing gap and closing it are two separate events. Inside vertically integrated health systems, the lab and the clinician share infrastructure and governance, allowing a flagged gap to move directly into the clinician’s workflow. Independent reference labs operate differently. They cannot add a test to an order or direct a clinician’s next clinical step; doing so would cross legal and relational boundaries. The lab can make the clinician aware that the insight exists, but it cannot make the clinician act on it, and most clinicians have no established habit of requesting a care gap report from their reference lab.
The economic case for closing testing gaps
Value-based care ties reimbursement to patient outcomes, not volume of interventions. For example, chronic kidney disease progression to stage 4 or 5 can drive dramatic cost increases. For cost of dialysis for patients with end-stage kidney disease varies by payer: annual spending is approximately $80,500 for Medicare patients, compared with $238,000 for privately insured patients, according to a 2024 study in JAMA Health Forum. The albumin-to-creatinine ratio test that can enable earlier intervention costs a fraction of that, yet 85% of eligible patients may never receive it.
Closing the gap requires clinician engagement
The technology to find testing gaps exists today. What most independent labs lack is a clinician base that knows how to ask for and act on those insights. Clinical labs that invest in clinician education alongside their analytics can turn detected gaps into closed ones. For everyone else, the gap remains where this study found it: visible, documented, and unaddressed.
