{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/968a774590844ec595e0cfc87025d0bf\" frameborder=\"0\" width=\"1490\" height=\"1117\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1117,"width":1490,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1117,"thumbnail_width":1490,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/968a774590844ec595e0cfc87025d0bf-41d93b629e4abc56.gif","duration":502.145,"title":"Enhancing Caregiver-Client Matching with CareQB","description":"In this video, I explain how CareQB utilizes both hard filters and a qualitative matching system to effectively pair clients with caregivers. We analyze raw text information from intake forms and care plans, as well as caregiver profiles, to identify potential mismatches. I demonstrate how to view qualitative matches and the importance of driving time considerations in the matching process. I encourage you to edit the AI-generated assessments as needed to ensure they reflect your preferences and insights. Please take a moment to familiarize yourself with these features to enhance our matching accuracy."}