Opportunity for Real-Time, Longitudinal Clinical Laboratory Data to Enhance Diabetes Disease Surveillance: A Cross-Sectional, Laboratory Database–Enabled Population Study

Abstract

Background: Population disease surveillance can contribute to focused interventions to promote better disease management and prevention of noncommunicable diseases. Methods: HbA1c results in TriCore Reference Laboratories’ (TriCore) data repository from residents in New Mexico (NM) from January 2014 to May 2019 were used in the study. Using the Behavioral Risk Factor Surveillance System (BRFSS) as the gold standard, a linear regression model was used to develop a model to estimate NM’s diabetes prevalence from HbA1cs. The American Diabetes Association guidelines HbA1c ranges were used to divide the population into groups according to their last HbA1c result, and patients were tracked by their TriCore identification number over the selected time period. Results: The derived NM diabetes rate of 10.63%, 95% CI [10.1%–11.1%] was compared to the derived 10.4%, 95% CI [9.8%–11%] by the CDC. Moreover, TriCore’s longitudinal data were able to track a large number of patients’ transition between the different HbA1cs cut offs from 2014 to 2019. Conclusion: Findings of this study substantiate the value of the laboratory outside of the traditional fee per service lab result model and support a possible novel role for clinical laboratories to play in population health.