Clinical QA Nurse (RN) at

Bot MD · United States

About the role About the Role We're hiring a Registered Nurse with deep home health and hospice experience to own the clinical quality of the documentation flowing through our AI platform. Our automations review referrals, OASIS documentation, certifications, physician orders, hospice election forms, face-to-face documentation, and supporting clinical records before they reach billing and authorization workflows. Your job is to ensure those automations make clinically sound decisions, identify where they fail, and continuously improve their accuracy. You'll work at the intersection of clinical expertise, quality assurance, and AI. Rather than reviewing a handful of patient charts each day, you'll help build systems that review thousands correctly. This is not a bedside or utilization review position. It's an operations and quality role for a nurse who enjoys finding edge cases, improving processes, and translating clinical judgment into scalable automation. What You'll Do Audit clinical QA performance Review charts processed by our clinical automation platform for accuracy, completeness, and consistency. Validate whether documentation supports services, identify incorrect classifications, and investigate why automation errors occurred. Improve clinical automation logic Partner with engineering and product teams to refine how our AI evaluates clinical documentation. You'll identify where automations miss important clinical nuances, recommend decision rules, and validate improvements before they're deployed. Build clinical review standards Develop SOPs that define how clinical documentation should be reviewed across home health and hospice. Standardize quality expectations while accounting for agency-specific workflows and payer requirements. Support customer implementations Work directly with agencies to understand their documentation standards, clinical workflows, and compliance expectations. Help configure automations that align with each client's operational processes. Drive quality metrics Measure and improve documentation quality, automation accuracy, exception rates, clinical escalations, and rework. Continuously identify opportunities to improve automation performance. What We're Looking For Required Active RN license (NY or compact license preferred) 3+ years of home health and/or hospice clinical experience Strong understanding of OASIS documentation and home health eligibility requirements Experience reviewing physician orders, certifications, plans of care, face-to-face documentation, and hospice election paperwork Hands-on experience with HomeCare HomeBase (HCHB), Axxess, and WellSky; KanTime a plus Strong understanding of Medicare home health and hospice documentation requirements Experience writing SOPs, QA guidelines, or training documentation Excellent attention to detail and pattern recognition Comfortable working in a fast-paced startup environment Nice to Have QA, Clinical Documentation Integrity (CDI), or Compliance experience Experience with AI, workflow automation, or healthcare technology companies Familiarity with referral platforms including Careport and Forcura Experience implementing or optimizing EMR workflows Why This Role Scale your clinical expertise. Help AI review thousands of charts instead of reviewing them one at a time. Own quality. Your feedback directly improves the clinical accuracy of our platform across every customer. Influence the product. Work side-by-side with engineering to shape how AI understands home health and hospice documentation. Technology Our Technology Claim Health is solving one of healthcare's most complex and fragmented problems, revenue cycle management in at-home care, with a modern, AI-native tech stack. What We Use TypeScript across the stack Node.js and tRPC for backend services React with Tailwind LLMs and Voice AI to power real-time documentation, denials analysis, and agentic workflows Mastra and custom agents to build autonomous systems that take real actions to get claims reimbursed What We're Solving Fully automating complex multi-step billing workflows with minimal human input Parsing unstructured documentation and mapping it to payer-specific rules using AI Building scalable automation to integrate with disparate data sources Designing agentic systems that collaborate across human, API, and UI layer, with accountability, retries, and memory We're pushing the frontier of what AI can do in production, on real revenue, in highly regulated environments. If you're excited about building agents that do real work (not just demos) this is your playground.