Handheld Ultrasound Devices for Peripheral Intravenous Cannulation: A Scoping Review.
Gillian Ray-BarruelPriscilla PatherJessica A SchultsClaire M RickardPublished in: Journal of infusion nursing : the official publication of the Infusion Nurses Society (2024)
Ultrasound-guided insertion of peripheral intravenous catheters (PIVCs) is recommended for patients with difficult intravenous access, but access to ultrasound equipment is often limited to specialty departments. Compact, affordable handheld ultrasound devices are available, but the extent of their clinical adoption and impact on patient outcomes is unknown. This scoping review aimed to explore evidence regarding handheld and pocket ultrasound devices for PIVC insertion. Databases were searched for studies published in English between January 2000 and January 2023 evaluating handheld or pocket ultrasound devices weighing ≤3 kg for PIVC insertion. Data were extracted using standardized forms and summarized using descriptive statistics. Seventeen studies reporting the use of handheld or pocket ultrasound devices were identified. Most studies were conducted in adult inpatient facilities; 3 included pediatrics, and 2 reported out-of-hospital use. Participants with difficult intravenous access featured in 9 studies. Ultrasound training programs were described in 12 studies, with competency defined by number of successful PIVC insertions. Five studies reported clinician and/or patient perspectives. Ultrasound for PIVC insertion is not widely accessible in nonspecialist areas, but more compact and affordable handheld models could provide a solution, especially for patients with difficult access. More research evidence using handheld ultrasound is needed.
Keyphrases
- ultrasound guided
- magnetic resonance imaging
- contrast enhanced ultrasound
- case control
- high dose
- healthcare
- emergency department
- mental health
- computed tomography
- palliative care
- electronic health record
- cross sectional
- extracorporeal membrane oxygenation
- adverse drug
- young adults
- deep learning
- artificial intelligence