Laboratory medicine: The exemplar for value-based healthcare.

Value-Based Healthcare (VBHC) aims to improve the overall quality, safety, and sustainability of healthcare while reducing delivery costs of more effective care. Despite advantages associated with VBHC transformation, the road to its adoption has been lengthy. Laboratory Medicine (LM) is in a prime position to lead the transition to VBHC because of its key role in diagnosis and treatment of patients. Laboratory medicine results inform/influence 50% to 70% of all clinical decisions. This article summarizes some issues associated with adoption of VBHC and related healthcare innovations and suggests potential approaches using LM-specific examples to help accelerate adoption. Laboratory medicine is both a useful model for VBHC implementation and facilitator for related innovation adoption by helping to target patient populations that would benefit most from specific interventions. The critical value of rapidly adopted diagnostic technologies used during the COVID-19 pandemic and economic recovery provide important insights about the need to embrace and accelerate VBHC implementation.

Comparison of Fetal Fibronectin and Phosphorylated Insulin-Like Growth Factor Binding Protein-1 Testing to Predict Preterm Delivery in Symptomatic Women: A 10-Year Retrospective Study.

OBJECTIVE: To assess the diagnostic accuracy and cost-effectiveness of fetal fibronectin (fFN) and cervical phosphorylated insulin-like growth factor binding protein-1 (phIGFBP-1) tests, individually and in combination, to predict preterm delivery within 48 hours, 7 days and 14 days in symptomatic women. METHOD: We selected women in Victoria, British Columbia, who presented between January 2008 and December 2017 at <34 weeks gestation at intermediate risk for labour (intact membrane, cervical dilatation <3 cm, and >6 contractions per hour). We calculated sensitivity, specificity, and positive and negative predictive values (PPV, NPV) for independent and concurrent testing and conducted a cost-effectiveness analysis to ensure appropriate test utilization. RESULTS: We identified 2911 cases. Both fFN and phIGFBP-1 tests showed high and comparable NPV in predicting risk of delivery within 48 hours, 7 days and 14 days (fFN: 99.3%, 98.5% and 97.3%; phIGFBP-1: 98.8%, 97.9% and 96.1%). In 1976 cases, samples for fFN and phIGFBP-1 tests were collected and analyzed concurrently. Concurrent analysis increased specificity (90.8%, 91.4%, and 91.8%) and PPV (11.8%, 19.8% and 24.2%). Independently, both tests had comparable sensitivity, while the fFN test had higher specificity. Concurrent testing offered the highest PPV. The net gain in PPV comes with a clinically insignificant net loss (<1%) in NPV when compared with either of the tests individually. CONCLUSION: Clinical usefulness of PPV for either test is limited. Routine concurrent testing comes with additional costs, and fFN has additional collection requirements. Point-of-care phIGFBP-1 testing has proven to be cheaper, simpler, and equally effective. Ordering physicians should be provided with education on how to interpret test results and should have protocols to guide clinical decision making.

Validation of a proteomic biomarker panel to diagnose minor-stroke and transient ischaemic attack: phase 2 of SpecTRA, a large scale translational study.

OBJECTIVE: To validate our previously developed 16 plasma-protein biomarker panel to differentiate between transient ischaemic attack (TIA) and non-cerebrovascular emergency department (ED) patients. METHOD: Two consecutive cohorts of ED patients prospectively enrolled at two urban medical centers into the second phase of SpecTRA study (training, cohort 2A, n = 575; test, cohort 2B, n = 528). Plasma samples were analyzed using liquid chromatography/multiple reaction monitoring-mass spectrometry. Logistic regression models which fit cohort 2A were validated on cohort 2B. RESULTS: Three of the panel proteins failed quality control and were removed from the panel. During validation, panel models did not outperform a simple motor/speech (M/S) deficit variable. Post-hoc analyses suggested the measured behaviour of L-selectin and coagulation factor V contributed to poor model performance. Removal of these proteins increased the external performance of a model containing the panel and the M/S variable. CONCLUSIONS: Univariate analyses suggest insulin-like growth factor-binding protein 3 and serum paraoxonase/lactonase 3 are reliable and reproducible biomarkers for TIA status. Logistic regression models indicated L-selectin, apolipoprotein B-100, coagulation factor IX, and thrombospondin-1 to be significant multivariate predictors of TIA. We discuss multivariate feature subset analyses as an exploratory technique to better understand a panel's full predictive potential.