In healthcare, phone calls are still a main way to handle many tasks. These include asking payers questions, setting appointments, and following up with patients. Old Interactive Voice Response (IVR) systems use fixed menus that can be hard to use and often need a person to help. New AI phone call platforms do more by using conversational AI based on large language models.
These AI systems can understand and respond like a human would. They can talk with patients, payers, and healthcare workers in a natural way. They help with key tasks such as:
For example, companies like Bland AI, Infinitus Systems, Nanonets Health, and Vogent offer AI solutions that follow HIPAA and SOC 2 rules. Their platforms connect with Electronic Health Records (EHR) systems to automate these time-consuming tasks. Using these platforms cuts down on repetitive calls, helping patients get care faster and reducing delays with payers.
Electronic Health Records (EHR) systems, like Epic, Cerner, and Meditech, handle patient information, clinical notes, and operations data. Enterprise Resource Planning (ERP) systems manage back-office work such as finance, supply chain, billing, and human resources.
Linking AI phone platforms with both EHR and ERP systems lets healthcare providers automate work that crosses clinical, admin, and financial areas. The AI agents can access patient and provider info, update records instantly, and share data between departments smoothly.
Main features of these integrations include:
These links help departments work better together. They speed up tasks like verifying eligibility and keep accounting and billing teams updated on time.
AI phone platforms tied to EHR and ERP systems bring several benefits:
Combining AI phone call platforms with workflow automation works well for handling complex healthcare administrative jobs. AI improves workflows by:
Linking AI tools to ERP systems helps align billing, inventory, and staffing with clinical work. For example, when AI schedules an appointment, the ERP can adjust provider availability and room readiness to improve efficiency.
Big companies like Epic Systems show the value of AI integration with EHRs. Epic uses AI such as GPT-4 to automate clinical documentation and help patient communication. Their tool Comet studies billions of patient events to predict clinical outcomes. This shows AI helps both clinical and admin work.
Healthcare AI phone platforms also use large language models for natural talks and quick replies. They follow HIPAA rules needed in U.S. healthcare.
Additionally, open-source tools help check AI models’ accuracy and safety. This promotes trust and proper use in automated tasks.
The Royal Adelaide Hospital in Australia has a complex system linking 13 engineering and ICT systems. It coordinates staff and equipment in real time. Wireless tracking helps manage assets and patients, improving resource use.
Similarly, U.S. hospitals and large clinics using AI phone platforms linked with EHR and ERP systems can see similar gains. Coordinating schedules, staff, billing, and patient contact reduces wasted efforts, improves patient satisfaction, and uses resources well.
Healthcare leaders thinking about AI integration should consider:
Using integrated AI phone call platforms in U.S. healthcare can reduce admin work, improve patient and payer interactions, and meet regulations. These tools help provide coordinated, timely, and efficient care.
New AI phone call platforms in healthcare have made it easier to improve administrative tasks. When linked with Electronic Health Records and Enterprise Resource Planning systems, they automate jobs like talking to payers, scheduling appointments, and managing revenue cycles. This makes admin work more accurate and efficient. For medical practice managers, owners, and IT staff in the U.S., adopting these tools is a useful step to improve operations and patient care in a challenging healthcare system.
Payer-Facing AI Phone Calls use AI to manage phone interactions with health insurers, automating tasks like verifying eligibility, prior authorizations, claim status checks, denied claims appeals, credentialing, and provider management, mostly via outbound calls with some inbound capabilities.
Healthcare AI agents offer dynamic, natural conversations with lower latency and higher reliability, integrating securely with EHRs and allowing seamless fallback to human agents, unlike rigid, menu-driven traditional IVR systems which have limited adaptability and user experience.
Most platforms hold HIPAA and SOC 2 Type 2 certifications, with some also possessing ISO 27001 and GDPR compliance, ensuring strong data privacy and security in managing sensitive healthcare information.
Processes commonly automated include eligibility and benefits verification, prior authorization requests, appointment scheduling, claim status updates, medication management, referral intake, billing inquiries, and managing denied claim appeals.
AI agents reduce administrative burden by automating repetitive tasks, improving data accuracy, expediting patient access to care, integrating with existing healthcare and ERP systems, and providing real-time analytic dashboards for performance monitoring.
They use proprietary or fine-tuned large language models and in-house language models to enable human-like, low-latency voice interactions, with capabilities to break conversations into sub-prompts and support advanced IVR navigation and human handoffs.
AI platforms integrate with EHRs, ERP, order management, prescription platforms, and insurance databases via APIs or low-code/no-code dashboards, allowing seamless data exchange and automation of complex workflows within healthcare operations.
Features include scheduling and tracking calls, custom call flow configuration through low-code UIs, real-time call result viewing, post-call automation, human agent fallback, and dashboards for monitoring and optimizing call performance.
Notable providers include Bland AI, Infinitus Systems, Nanonets Health, SuperDial, Synthpop, Vogent, Avaamo, Deepgram, Delfino AI, and Prosper AI, each offering specialized AI-driven automation for payer and patient communications.
AI agents automate key RCM processes like claim status updates, eligibility checks, prior authorizations, and denials management by communicating with payers, generating summaries, alerting humans when necessary, and integrating with multiple EHR platforms for accuracy and speed.
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