As one of the US's largest and most respected healthcare providers, this healthcare provider is a multi-specialty academic medical center that integrates clinical and hospital care with research and education with more than 48,000 employees.
Surgical equipment left inside patients doesn’t happen often. But in those rare instances where surgical equipment is present inside the patient post-surgery, the experience and cost can be traumatic.
Seeking to ensure that such an event never happens, this healthcare provider embarked on an image processing and real-time data analytics project. The goal was to leverage Matlab to track the surgical equipment from start to finish while warning staff in real-time should something be missing.
But setting up a system to track surgical equipment required subject matter expertise, which the provider lacked in-house. Rather than onboard a consulting firm or undergo a two-month process to find the right person for the initiative, the healthcare provider decided to take an alternative approach by exploring on-demand talent acquisition.
After learning about Graphite’s pool of 8,900+ subject matter experts and the ability to use the platform to quickly find an independent expert within 24-48 hours, the healthcare provider engaged an Account Executive (AE) to establish next steps.
Once connected, the AE provided additional context into how Graphite worked, the two-tier vetting process, and how Graphite ensured that the best subject matter expert was matched to its project. The provider then set up a subsequent meeting with the AE to discuss the scope of work for the Matlab initiative.
Understanding the technology and healthcare industry skills required to complete the project successfully, the AE presented four hand selected experts within hours. The provider used Graphite in-app messaging tools to vet each candidate before moving forward with an expert with proven Matlab experience with a deep background in designing and implementing deep learning models for tracking objects in images and videos using Matlab, Python, Tensorflow, and PyTorch.
Before getting started, the healthcare provider set up an onboarding meeting with the expert to review the scope of work. Together they clarified any questions and reviewed the current state and workflows being used to track surgical equipment.
The expert also worked with the team to understand desired workflows and methodologies for tracking equipment. This enabled the expert to configure Matlab to develop a proof of concept and facilitated the launch of a pilot program before rolling out the program to the entire organization.
After completing the pilot program, the expert collected feedback from the team to further optimize the configuration. With feedback implemented, the healthcare provider could move forward with a full-scale implementation based on the superior results accomplished.