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Related Experiment Video

Updated: Jun 25, 2026

A Training and Testing System for Performing Vascular Reconstruction In Vitro

A Training and Testing System for Performing Vascular Reconstruction In Vitro

Published on: October 26, 2019

Assessing the database needs of vascular surgeons.

Peter F Lawrence¹, Olivia I Lund, Frederick Eko

¹Division of Vascular Surgery, Gonda (Goldschmied) Vascular Center, University of California, Los Angeles, Los Angeles, CA, USA.

Journal of the American College of Surgeons

|February 21, 2009

Summary

Vascular surgeons desire clinical outcomes databases but face barriers like time and cost. Streamlined, portable data entry and sharing are key to widespread adoption.

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Pioneering Patient-Specific Approaches for Precision Surgery Using Imaging and Virtual Reality

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Published on: April 5, 2024

Area of Science:

Vascular Surgery
Health Informatics
Clinical Data Management

Background:

Vascular surgery is well-suited for shared databases due to precise outcome measures and established national standards.
Vascular surgeons have a history of data collection, making them amenable to database development.

Purpose of the Study:

To assess the current experience, needs, and barriers related to clinical outcomes databases among vascular surgeons.
To identify surgeon preferences for database features, including data entry time, cost, and portability.

Main Methods:

A survey was distributed to members of the Western Vascular Society and Rocky Mountain Vascular Surgical Society.
The questionnaire assessed database experience, needs, and barriers, and commercial database software was reviewed.

Main Results:

57% of surveyed vascular surgeons utilize functional databases, with common uses in research, quality control, and billing.
Time constraints (38%), cost (19%), and expertise (8%) are primary barriers to database use.
89% of surgeons without a database desire one, with strong interest in portable data entry and data sharing (98%).

Conclusions:

Vascular surgeons express significant interest in clinical outcomes databases, contingent on addressing current barriers.
Key factors for successful database implementation include short data entry times, manageable costs, portable entry systems, and data sharing capabilities.