‘Upskill and Get Recruited’ – How Techolution Revolutionized Nurse Recruitment with AI

At a time when looking for a job feels like a chore, many can only dream of it being as easy as a swipe on your phone. Facing a growing nursing shortage, nurse.com by Relias, a leading platform for nurses to continue education and get certified, aimed to turn this dream into reality. Partnering with Techolution, an innovative AI-driven job matching system was born that seamlessly connects qualified nurses with healthcare employers. This innovative approach revolutionized the recruitment process, underscoring the potential of real-world AI solutions in healthcare.

Bridging The Gap Between Hospitals In Need And Qualified Nurses On Nurse.Com

Nurse.com, known for serving over 200,000 registered nurses with essential certification tracking, upskilling, and continuing education, identified a significant opportunity. With a nationwide nursing shortage, hospitals struggled to fill vacancies promptly and effectively. Traditional recruitment methods led to prolonged hiring times and mismatched placements, creating an urgent need for an efficient solution. Relias envisioned an AI-based approach to streamline this process. However, they faced challenges integrating legacy systems and ensuring precise matches. This is where Techolution’s expertise became a game changer.

For the blueprint of the idea to materialize, it was important to understand what the platform’s purpose and revenue model would be. We learned that the platform could enable nurses to learn, gain expertise,track their certifications and licenses, and also look for jobs. Revenue would be generated from hospitals that subscribe to the platform to list job openings, not from the nurses. This paved the way for a revolutionary AI-powered job matching platform.

Techolution’s AI-Driven Model

Techolution’s AI model, central to their proprietary engine, includes three layers:

With that, the job matching and filtering process became far easier. Hospitals could post job descriptions with specific details such as required licenses, experience, pay grade, and other criteria. The platform’s elastic search and lexical understanding would match these with nurse resumes based on location, licenses, and relevant experience. That said, the nurses’ profiles would automatically update and they completed their courses and got their certificates and licenses. This readily available database with nurse profiles and their qualifications facilitated jobs to be shown only to nurses who meet specific requirements, preventing a flood of irrelevant applications.

In addition to eliminating irrelevance, selective job visibility also made things easier for nurses looking for jobs. Nurses could see how well their profile matches job postings, e.g., 90%, 85% match, and express interest by swiping right or left, providing them with an experience similar to a dating app.

Creating A Transformational Impact By Improving Recruitment Efficiency

The project started with basic applications for nurses and recruiters and iteratively enhanced the platform. Integrating the job matching service into nurse.com, which enabled nurses to track their certifications and licenses, provided a cohesive experience. This integration expanded the project scope but ensured a truly effective and seamless experience for nurses and recruiters.

The app serves both employers looking for candidates and nurses seeking jobs by facilitating interaction. Employers can invite candidates for interviews, reject profiles with specific reasons (e.g., lack of experience), and communicate directly through personalized messages. Nurses can receive interview requests, view job details, and indicate their interest or disinterest in job postings. A notable feature of the platform is Techolution’s integration of Reinforcement Learning Expert Feedback (RLEF) to train the model. When a match is rejected, the platform asks for the reason and uses this feedback to improve future matches, ensuring that similar candidates or positions are not suggested again. RLEF is also applied to approved matches, so that when similar jobs open in the future, the platform has a refined understanding of whom to consider and what criteria to filter, further enhancing the accuracy and efficiency of the matching process.

Both parties benefit from video resumes, where nurses can upload 30-second bios and hospitals can create videos about the organization and job role. Video content is transcribed into text for lexical matching, ensuring relevance despite varying accents.

Additionally, iterative development paved the way for more enhanced features. Over time, the platform grew to include features like job finding, swiping through job cards, and shortlisting top matches. The system integrates job postings and learning management systems (LMS) to provide a well-sewn-together experience for nurses. The integration of features was collaborative, with innovative ideas like dating-app-like swiping enhancing user engagement. Techolution’s AI-powered job matching system transformed nurse recruitment by creating a seamless, efficient, and highly accurate process. This innovative solution not only bridged the gap between qualified nurses and healthcare employers but also set a new standard for AI applications in healthcare recruitment.