Background and Objectives: Difficult venous access (DVA) affects 10–26% of hospitalized patients and up to 60% in high-risk populations, leading to increased patient discomfort, delayed diagnosis, and substantial healthcare costs estimated at 4. 7 billion annually in the United States. This meta-analysis aimed to systematically evaluate the effectiveness, safety, and implementation considerations of traditional and emerging strategies for obtaining blood samples in patients with DVA. Materials and Methods: We conducted a comprehensive systematic review and meta-analysis following PRISMA guidelines. We searched MEDLINE, Embase, CINAHL, and Cochrane databases from January 2016 to December 2023. Inclusion criteria encompassed randomized controlled trials, systematic reviews, and observational studies examining DVA interventions in adult and pediatric populations. Primary outcomes included first-attempt success rates, overall success rates, and complication rates. Statistical analysis used random-effects models with risk ratios and 95% confidence intervals. Results: Forty-seven studies involving 12, 847 patients met the inclusion criteria. Technology-assisted approaches demonstrated superior outcomes compared to traditional techniques. Ultrasound guidance showed the highest effectiveness with a first-attempt success increase of 42% (RR 1. 42, 95% CI 1. 26–1. 58, p < 0. 001), followed by near-infrared visualization with a 28% increase (RR 1. 28, 95% CI 1. 14–1. 42, p < 0. 001). Population-specific approaches yielded significant benefits, including the use of scalp veins for infants and external jugular approaches for extreme DVA cases. Cost-effectiveness analysis revealed that ultrasound guidance achieved break-even within 8–14 months in high-volume centers. Conclusions: A systematic, stepwise approach integrating appropriate technology and techniques significantly improves success rates while reducing patient discomfort and healthcare costs. Healthcare institutions should implement comprehensive DVA protocols with adequate training, equipment access, and quality monitoring. The proposed algorithm achieved a 93% overall success rate in validation studies, representing a substantial improvement over traditional approaches.
Mussa et al. (Mon,) studied this question.