ArticleRisk management and healthcare policy2025
Optimizing Strategies for Managing Difficult Intravenous Access.
Article in Risk management and healthcare policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- A Novel 3D-Printed Pediatric Cardiac Model for Teaching Catheterization Anatomy and Access Pathways.Cureus · 2025Article
- The Role of Artificial Intelligence in Managing Central Line-Associated Bloodstream Infection (CLABSI) for Patient Safety and Quality of Care.Risk management and healthcare policy · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Difficult intravenous (IV) access (DIVA) remains a significant challenge in healthcare, leading to treatment delays, patient discomfort, and adverse outcomes. Contributing factors include patient conditions (eg, obesity, dehydration, anatomical variations) and provider-related challenges (eg, inadequate training, improper technique). Addressing DIVA requires a structured, data-driven approach. Purpose: This study examines the root causes of IV access complications, their prevalence, and distribution across healthcare settings. It evaluates the impact of an escalation pathway and data-driven strategies to improve IV success rates, provider training, and process standardization. Patients and Methods: A retrospective analysis was conducted on 311 DIVA patients at Sheikh Shakhbout Medical City (SSMC), Abu Dhabi, UAE, over seven months (June-December 2023). Data were obtained from electronic medical records (EMR) and Intensive Care Outreach Nurse (ICON) consultation forms. A novel IV escalation pathway and documentation system facilitated data collection on patient demographics, IV access reasons, and primary diagnoses. Results: Among ICON-assisted patients, 74.6% had a known DIVA history, with cancer and renal disease being common conditions. ICONs achieved a first-attempt success rate of 68.8%, underscoring the need for improved floor nurse training. The most frequent IV access indications were medication administration, antibiotics, laboratory tests, and analgesia. Additionally, 57.3% of ICON consultations occurred outside standard hours, highlighting resource allocation challenges. Conclusion: Structured escalation pathways, advanced nurse training, and data-driven decision-making are critical in addressing DIVA. Recommendations include a dedicated IV access team, ultrasound-guided cannulation, and predictive analytics to identify high-risk patients, ultimately enhancing patient outcomes and healthcare efficiency.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.