# CombineHealth — Full Site Content > AI-powered Revenue Cycle Management (RCM) platform for healthcare. > CombineHealth automates medical coding, billing, denial management, > appeals, and clinical documentation using autonomous AI agents. > Founded in San Francisco. SOC 2 Type II certified. HIPAA compliant. > Contact: info@combinehealth.ai | 2261 Market Street, #22878, San Francisco, CA 94114 --- ## Homepage — https://www.combinehealth.ai ### What CombineHealth Does CombineHealth is an AI Revenue Cycle Automation Platform for healthcare. It deploys autonomous AI agents that work across the full revenue cycle — from clinical documentation and medical coding through billing, denial management, and appeals. ### Key Results - 30% Higher Collections - 20% Reduction In A/R Days - 30% Lower Cost - 75% Reduction In Claim Denials ### AI Agents Overview CombineHealth's AI workforce consists of seven specialized agents: - **Amy** — AI Medical Coder: 99.2%+ ICD-10 & CPT coding accuracy - **Mark** — AI Medical Biller: automated claim generation and payer submission - **Jessica** — AI Medical Scribe: real-time clinical note generation - **Adam** — AI Denial Manager: autonomous payer portal navigation and denial resolution - **Taylor** — AI Revenue Cycle Analyst: RCM bottleneck identification and KPI reporting - **Penny** — AI Policy Reviewer: CMS manual and payer policy search with citations - **Rachel** — AI Appeals Manager: payer-specific appeal letter drafting in minutes ### Customer Testimonial Jon Gerber, CEO with 30+ years of RCM experience: "CombineHealth's AI platform transformed our revenue cycle operations." ### Who We Serve Hospitals & Health Systems, Clinics & Physician Groups, FQHCs, ASCs & Specialty Care, Billing Companies, Agencies. --- ## Amy — AI Medical Coder **URL:** https://www.combinehealth.ai/ai-medical-coding-software ### What Amy Does Amy is CombineHealth's AI medical coder. She automates ICD-10-CM and CPT coding with 99.2%+ accuracy, ensuring payer-specific compliance and identifying undercoded and missing services that cause revenue leakage. ### Key Features - AI-driven ICD-10-CM and CPT code assignment - Payer-specific coding compliance rules - Identification of undercoded and missing services - Coding accuracy enhancement to reduce claim denials - Integration with existing EHR and billing workflows ### Key Stat Amy achieves 99.2%+ coding accuracy across ICD-10-CM and CPT codes, reducing claim denials caused by coding errors. ### Use Cases - Hospital outpatient coding - Physician group coding - FQHC multi-specialty coding - ASC procedure coding - Anesthesia coding (150+ claims generated in minutes) ### Frequently Asked Questions **How accurate is Amy's AI medical coding?** Amy achieves 99.2%+ coding accuracy across ICD-10-CM and CPT codes, reducing claim denials caused by coding errors. **What coding standards does Amy support?** Amy supports ICD-10-CM diagnosis coding and CPT procedure coding, with payer-specific rule sets for major commercial payers and CMS. **How does Amy identify undercoded services?** Amy cross-references clinical documentation against coding guidelines and payer LCD/NCD policies to flag services that were provided but not captured in the submitted code set. **Does Amy integrate with EHR systems?** Yes. Amy integrates with existing EHR and practice management systems, working within current workflows rather than replacing them. --- ## Mark — AI Medical Biller **URL:** https://www.combinehealth.ai/mark-ai-medical-biller ### What Mark Does Mark is CombineHealth's AI medical biller. He automates claim generation, validation, and submission to payers with built-in error checks. Mark tracks claim statuses, identifies billing discrepancies, and reduces rejections and A/R days. ### Key Features - Automated claim generation from coded encounters - Payer-specific validation rules before submission - Electronic claim submission with error checks - Claim status tracking and follow-up - Billing discrepancy identification - A/R days reduction ### Key Stat Mark helped an anesthesia group generate 150+ claims in minutes, reducing manual billing time dramatically. ### Use Cases - High-volume claim generation for anesthesia groups - Eligibility verification (80% reduction in verification time for one anesthesia group) - Multi-payer submission for physician groups - Denial prevention through pre-submission validation ### Frequently Asked Questions **What types of claims does Mark support?** Mark supports professional claims (CMS-1500), institutional claims (UB-04), and electronic 837P/837I transactions for all major payer types. **How does Mark reduce claim rejections?** Mark validates claims against payer-specific edits before submission, catching errors that would cause rejections — such as missing modifiers, invalid code combinations, or eligibility mismatches. **How fast does Mark generate claims?** An anesthesia group using Mark generated 150+ claims in under one hour — a process that previously took a full billing team a full day. --- ## Jessica — AI Medical Scribe **URL:** https://www.combinehealth.ai/jessica-ai-medical-scribe-solution ### What Jessica Does Jessica is CombineHealth's AI medical scribe. She generates real-time clinical notes by listening to the doctor during the patient encounter. Jessica flags missing clinical details, auto-structures notes for coding and billing accuracy, and feeds documentation directly into the billing workflow. ### Key Features - Real-time clinical note generation during patient encounters - Smart prompts that flag missing clinical details - Auto-structured SOAP and specialty-specific note formats - Notes structured for ICD-10 coding accuracy - Direct integration with billing workflow - HIPAA-compliant audio processing ### Use Cases - Outpatient physician documentation - Specialist visit notes - FQHC encounter documentation - Post-encounter note review and correction ### Frequently Asked Questions **What is an AI medical scribe?** An AI medical scribe listens to the doctor-patient conversation and automatically generates a structured clinical note, eliminating the need for manual documentation or human scribes. **How does Jessica differ from traditional medical scribes?** Jessica works in real time, never tires, produces consistent structured output, and costs a fraction of a human scribe. She also flags missing clinical details that human scribes might miss, improving coding accuracy downstream. **Is Jessica HIPAA compliant?** Yes. Jessica processes audio and clinical data in a HIPAA-compliant environment with SOC 2 Type II certified infrastructure. **Does Jessica work with all specialties?** Jessica supports a wide range of outpatient specialties including primary care, surgery, anesthesia, internal medicine, and more. --- ## Adam — AI Denial Manager **URL:** https://www.combinehealth.ai/adam-ai-denial-management-software ### What Adam Does Adam is CombineHealth's AI denial manager. He navigates payer portals autonomously, makes AI-driven calls to retrieve claim status and resolve denials, and intelligently prioritizes denial cases using customizable call scripts and branching logic. ### Key Features - Autonomous payer portal navigation - AI-driven phone calls to payer IVR systems and representatives - Intelligent denial case prioritization based on dollar value and denial type - Customizable call scripts and branching decision logic - Claim status retrieval without manual staff effort - 75% reduction in claim denial rates ### Key Stat Adam reduces claim denial rates by up to 75%, recovering revenue that would otherwise be written off. ### Use Cases - High-volume denial follow-up for hospitals - Payer portal status checks for physician groups - Prior authorization follow-up - Claim underpayment identification and appeal initiation ### Frequently Asked Questions **What is AI denial management software?** AI denial management software automates the process of identifying, following up on, and resolving denied insurance claims — tasks that traditionally require a large billing staff calling payers manually. **How does Adam automate denial follow-up?** Adam logs into payer portals and uses AI-driven calls to IVR systems and live representatives to retrieve denial reasons, submit reconsiderations, and track outcomes — without human involvement. **What is a good claim denial rate in healthcare?** Industry average claim denial rates range from 5–15%. Best-in-class organizations target below 5%. Adam helps reduce denial rates by up to 75% from their current baseline. **Which payers does Adam work with?** Adam works across major commercial payers, Medicare, Medicaid, and regional plans. Custom payer portal configurations are available. --- ## Taylor — AI Revenue Cycle Analyst **URL:** https://www.combinehealth.ai/taylor-ai-revenue-cycle-optimization ### What Taylor Does Taylor is CombineHealth's AI Revenue Cycle Analyst. She analyses each step of the RCM process, identifies bottlenecks causing revenue leakage, builds real-time analytics dashboards, and generates monthly summary reports customized to each team's KPIs. ### Key Features - End-to-end RCM process analysis - Revenue leakage detection across the revenue cycle - Real-time analytics dashboards - Customizable monthly KPI reports - Benchmarking against industry standards - Bottleneck identification and prioritization ### Use Cases - CFO and revenue cycle director reporting - A/R aging analysis - Denial trend analysis - Payer performance benchmarking - Coding accuracy trend monitoring ### Frequently Asked Questions **What is revenue cycle analytics?** Revenue cycle analytics is the systematic analysis of financial and operational data across the healthcare billing process — from charge capture through collections — to identify inefficiencies and improve net revenue. **What KPIs does Taylor track?** Taylor tracks key RCM metrics including clean claim rate, first-pass acceptance rate, denial rate by payer and code, days in A/R, cost to collect, and net collection rate. **How does Taylor identify revenue leakage?** Taylor cross-references coding data, billing submissions, payer adjudications, and payment postings to identify patterns where revenue is being lost — such as systematic undercoding, payer underpayments, or unbilled encounters. --- ## Penny — AI Policy Reviewer **URL:** https://www.combinehealth.ai/penny-ai-policy-review-rcm ### What Penny Does Penny is CombineHealth's AI payer policy reviewer. She searches across CMS manuals, public payer policies, and policy PDFs to answer policy questions instantly. Penny provides precise answers with page-level citations and collaborates with other CombineHealth AI agents (Mark, Amy) to prevent denials before they happen. ### Key Features - CMS manual and LCD/NCD policy search - Commercial payer policy search with page-level citations - Policy PDF ingestion and search - Collaboration with Amy (coding) and Mark (billing) to flag policy conflicts - Denial prevention through pre-submission policy compliance - 35% reduction in denials attributed to policy non-compliance ### Key Stat Penny reduces denials by 35% by ensuring coding and billing decisions comply with current payer policies before claims are submitted. ### Use Cases - Pre-authorization policy lookups - ICD-10 and CPT coverage verification - LCD/NCD compliance checks - Payer-specific billing rule clarification ### Frequently Asked Questions **How do I check payer policies for CPT codes?** Penny searches CMS manuals, LCD/NCD databases, and commercial payer policy portals to answer coverage questions for specific CPT codes — and provides the exact page and document as a citation. **What is a payer policy reviewer in healthcare?** A payer policy reviewer checks whether a proposed coding or billing decision complies with the applicable payer's coverage and payment policies before a claim is submitted, preventing denials. **How does AI help with payer policy compliance?** AI can instantly search thousands of pages of policy documentation and compare planned coding decisions against current rules — a process that would take a human coder hours to do manually. --- ## Rachel — AI Appeals Manager **URL:** https://www.combinehealth.ai/rachel-ai-medical-appeal-rcm-solution ### What Rachel Does Rachel is CombineHealth's AI medical appeals manager. She drafts clear, payer-specific appeal letters in minutes. Rachel adapts to your organization's writing style, extracts medical necessity reasoning from provider notes, and tracks appeal outcomes. ### Key Features - Payer-specific appeal letter generation in minutes - Organizational writing style adaptation - Medical necessity reasoning extraction from provider notes - Clinical evidence synthesis for strong appeal arguments - Appeal tracking and outcome management - Support for first-level and second-level appeals ### Use Cases - High-volume denial appeal programs - Complex medical necessity appeals - Prior authorization denial appeals - Clinical documentation improvement for appeals ### Frequently Asked Questions **How do you write a medical appeal letter?** A strong medical appeal letter includes: (1) the specific denial reason being contested, (2) the applicable coverage policy or clinical guideline, (3) medical necessity evidence from the patient's clinical notes, and (4) a clear request for reconsideration. Rachel automates all four elements. **What is the success rate for medical billing appeals?** First-level appeal overturn rates average 40–60% across payers. Well-crafted appeals that include clinical evidence and cite the specific policy being contested achieve higher overturn rates. Rachel's structured approach maximizes appeal quality. **How does AI automate insurance appeal letters?** Rachel reads the denial explanation, retrieves the relevant payer policy, extracts supporting evidence from the clinical notes, and drafts a structured appeal letter — a process that takes minutes instead of hours. **What information is needed for a medical necessity appeal?** Medical necessity appeals require: the denied service and its CPT/ICD-10 codes, the payer's denial reason and policy reference, the patient's clinical documentation supporting the medical necessity of the service, and any applicable clinical guidelines or peer-reviewed evidence. --- ## Company — About CombineHealth **URL:** https://www.combinehealth.ai/about-us CombineHealth was founded by Sourabh Agrawal and Shikha, combining 40+ years of experience in revenue cycle management and artificial intelligence. The company is headquartered in San Francisco, California. CombineHealth is SOC 2 Type II certified and fully HIPAA compliant. The platform integrates with existing EHR and practice management systems. **Founding year:** 2022 **Headquarters:** 2261 Market Street, #22878, San Francisco, CA 94114 **Contact:** info@combinehealth.ai **LinkedIn:** https://www.linkedin.com/company/combinehealth --- ## Customer Success Stories **Clients include:** Kodiak KANA, Homeward, InnoviHealth, Derma Clinic. **Anesthesia Group Generates 150+ Claims in Minutes** URL: https://www.combinehealth.ai/resources/customer-success-stories/case-study/anesthesia-group-claims An anesthesia group using CombineHealth's Mark (AI Medical Biller) generated over 150 claims in under one hour — a task that previously required a full billing team working a full day. **80% Reduction in Eligibility Verification Time** URL: https://www.combinehealth.ai/resources/customer-success-stories/case-study/anesthesia-group-eligibility The same anesthesia group reduced eligibility verification time by 80% using CombineHealth's automated verification workflow. **Community Health Center Achieves 20% Reduction in Denials** URL: https://www.combinehealth.ai/resources/customer-success-stories/case-study/community-health-center A community health center (FQHC) reduced their claim denial rate by 20% after deploying CombineHealth's AI coding and policy compliance agents. **AI Matched Expert Coders Across 1,000 ED Charts** URL: https://www.combinehealth.ai/resources/customer-success-stories/case-study/ai-matched-expert-coders In a controlled parallel study, CombineHealth's AI delivered expert-level accuracy, reduced turnaround time by 50%, and surfaced critical documentation gaps missed in Emergency Department traditional coding workflows. --- ## Trust & Security **URL:** https://www.combinehealth.ai/trust-and-security - SOC 2 Type II certified - HIPAA compliant - Data encrypted in transit and at rest - Role-based access controls - Audit logging for all data access --- ## FAQs — https://www.combinehealth.ai/faqs **What is Revenue Cycle Management (RCM)?** Revenue Cycle Management is the financial process healthcare organizations use to track patient care episodes from registration and appointment scheduling through the final payment of a balance. It includes coding, billing, claims submission, payment posting, denial management, and collections. **How does CombineHealth's AI differ from traditional RCM software?** Traditional RCM software automates workflows but still requires human staff to make decisions. CombineHealth's AI agents make autonomous decisions — coding claims, navigating payer portals, drafting appeal letters, and generating reports — without requiring human review of every transaction. **Is CombineHealth HIPAA compliant?** Yes. CombineHealth is fully HIPAA compliant and SOC 2 Type II certified. All patient data is encrypted in transit and at rest with strict access controls. **Which EHR systems does CombineHealth integrate with?** CombineHealth integrates with major EHR and practice management systems. Contact the sales team for a specific integration inquiry. **How long does implementation take?** Implementation timelines vary by organization size and integration complexity. Contact CombineHealth at info@combinehealth.ai or schedule a demo at https://www.combinehealth.ai/demo. **What types of healthcare organizations use CombineHealth?** CombineHealth serves hospitals and health systems, clinics and physician groups, FQHCs, ASCs and specialty care centers, billing companies, and healthcare agencies.