Quick Answer: AI in healthcare automates document processing, with Valere partnering with Notable Systems to tackle “fax wrangling” – automatically extracting information from flooded inboxes of orders and documents. This eliminates manual sorting and data entry, saving significant staff time and reducing errors.
Key Takeaways:
- AI automates document processing in healthcare, eliminating manual sorting of faxes and orders through systems like Notable’s platform.
- AI-powered claims processing catches errors before submission, reducing denial rates from 24% to 8% for some providers.
- Smart inventory systems predict equipment needs based on usage patterns, preventing critical supply shortages while optimizing stock levels.
AI Applications in Healthcare Revenue Cycle Management
The financial side of healthcare often involves mountains of paperwork and complex processes that drain resources and slow down patient care. For Home and Durable Medical Equipment (HME/DME) providers, these challenges are especially tough. AI technology is changing this landscape by turning tedious manual tasks into streamlined, automated workflows.
Healthcare providers now use AI to handle the financial tasks that once required hours of staff time. These smart systems can process documents, check for errors, and even predict potential problems before they happen. For DME suppliers struggling with overflowing inboxes of faxes and orders, AI offers a way out of the document chaos.
Valere’s partnership with Notable Systems addresses this exact problem. Their combined solution tackles the “document wrangling” challenge by automatically processing incoming documents, extracting key information, and entering it into the right systems—all without human intervention.
Automating Claims Processing and Reducing Denials
Claims denials cost healthcare providers billions each year and create frustrating rework. AI-powered claims processing systems now scan claims before submission, catching errors that human eyes might miss. These systems check for missing information, incorrect codes, and compliance issues that could trigger denials.
The real power comes from how these systems learn over time. When a DME provider processes thousands of claims, the AI identifies patterns in what gets approved versus denied. This learning helps prevent future rejections by flagging potential issues before submission.
One DME supplier using Valere’s Workflow Automation saw their denial rate drop from 24% to just 8% within three months. The system automatically extracts relevant details from clinical notes using natural language processing to support medical necessity requirements—a common reason for DME claim denials.
Streamlining Prior Authorization Workflows
Prior authorizations represent one of the biggest headaches for DME providers. Traditional methods involve staff members manually gathering documentation, completing forms, and making follow-up calls—a process that can take days or even weeks.
AI-powered prior authorization tools transform this process. These systems automatically collect required documentation from electronic health records, complete authorization forms, and track approval status in real-time. The technology can even predict which equipment orders will likely need extra documentation based on payer history and patient diagnosis.
A respiratory equipment provider using Valere’s Business Interoperability platform reduced their prior authorization processing time from an average of 72 hours to just 35 minutes. The system continuously monitors payer portals for updates and automatically alerts staff when action is needed, eliminating the need for constant manual checking.
Optimizing Patient Eligibility Verification
Verifying insurance coverage traditionally requires phone calls, portal logins, and manual data entry. AI eligibility verification tools now perform these checks automatically in seconds rather than hours.
These systems connect directly to payer databases to verify coverage in real-time, checking not just whether a patient has insurance but specifically what DME benefits are available. The AI can determine if a particular piece of equipment is covered, what documentation is required, and what the patient’s financial responsibility will be.
The technology also monitors for changes in coverage. If a patient’s insurance status changes, the system alerts staff proactively, preventing denied claims and billing surprises. One home medical equipment company using Valere’s Order Management solution reduced eligibility-related claim rejections by 67% while cutting verification staff time in half.
Enhancing Medical Coding Accuracy and Efficiency
Accurate coding is essential for DME reimbursement, but keeping up with changing codes and payer requirements is challenging. AI coding assistants now analyze clinical documentation and suggest appropriate HCPCS codes for equipment and supplies with remarkable accuracy.
These systems use natural language processing to identify clinical indicators in documentation that support medical necessity. For example, the AI can recognize language in a physician’s notes that justifies a specific type of wheelchair or oxygen equipment.
The technology continuously improves its recommendations based on successful claims and regulatory updates. One DME provider using AI-assisted coding increased their first-pass claim approval rate by 28% while reducing the time coders spent on each claim by more than half.
By implementing Valere’s Point-of-Care Platform, providers can ensure accurate coding from the moment an order is placed, reducing downstream billing problems and speeding up the revenue cycle.
AI-Powered Order Management for HME/DME Providers
The daily operations of Home and Durable Medical Equipment providers often get bogged down by paperwork and manual processes. AI technology is now transforming how these providers handle orders from start to finish. By automating the most time-consuming tasks, staff can focus on what really matters – patient care.
Intelligent Document Processing for Referrals and Orders
Every day, HME/DME providers face a flood of faxes and emails containing vital patient information. Traditionally, staff members manually review each document, extract key details, and enter them into electronic systems. This process is slow, error-prone, and keeps skilled workers tied to desks instead of helping patients.
AI-powered document processing changes everything. Systems like those offered through Valere’s partnership with Notable Systems can automatically scan incoming referrals, pull out patient demographics, diagnosis codes, and equipment specifications without human help. When a physician faxes an order for a wheelchair, the AI reads the document just like a human would, but in seconds rather than minutes.
These smart systems don’t just extract information – they check it for completeness. When a referral arrives missing the required face-to-face documentation, the AI automatically generates a request to the physician’s office. One DME provider reported cutting their order processing time from 24 hours to just 30 minutes after implementing Valere’s Document Intake and Triage solution.
Predictive Inventory Management and Supply Chain Optimization
Running out of critical medical supplies can delay patient care, while overstocking ties up valuable resources. AI inventory systems analyze past order patterns to predict future needs with remarkable accuracy. These tools consider seasonal trends (like increased oxygen concentrator needs during flu season) and local patient demographics to optimize stock levels.
For equipment rental programs, AI predicts when devices will need maintenance based on usage patterns and manufacturer data. This proactive approach extends equipment life and prevents the frustration of unexpected breakdowns when patients need equipment most.
The technology also monitors the broader supply chain for potential disruptions. When manufacturing delays might affect CPAP machine availability, the system alerts managers early and suggests alternative models or suppliers. This foresight helps providers maintain service levels even during supply chain challenges like those experienced during recent global disruptions.
Automated Coverage Criteria Verification
Insurance coverage rules for medical equipment are complex and constantly changing. AI verification tools match patient diagnostic information with payer-specific coverage criteria in real-time. When a patient needs a hospital bed, the system instantly checks if their diagnosis and documentation meet Medicare requirements for coverage.
These tools go beyond simple verification. They can suggest alternative equipment options that might have better coverage based on the patient’s specific insurance plan. If a particular walker model isn’t covered, the AI might recommend a similar model that is approved by the patient’s insurance.
The most valuable aspect is how these systems stay current. As Medicare and private payers update their policies, the AI automatically incorporates these changes. Providers using Valere’s Automated Eligibility Checks report significant reductions in denied claims and faster reimbursement cycles.
Smart Patient Communication and Delivery Coordination
Getting equipment to patients involves multiple touchpoints that traditionally require phone calls and manual scheduling. AI communication systems now automate this entire process. They schedule deliveries based on equipment availability and optimal routing, then send text or voice reminders to patients about upcoming appointments.
Modern AI chatbots answer common patient questions about their equipment and insurance coverage at any hour. When a patient wonders how to adjust their CPAP pressure at 2 AM, they can get immediate help without waiting for office hours.
The technology also identifies patients who might need extra support. If usage data shows a patient isn’t using their equipment as prescribed, the system flags this for follow-up. This proactive approach improves patient outcomes and satisfaction while reducing the likelihood of equipment abandonment.
AI Integration with Existing Healthcare Systems
The promise of AI in healthcare often hits a roadblock when providers face the reality of their current technology setup. Many HME/DME companies run on a patchwork of systems built over decades. The good news? You don’t need to rip and replace everything to benefit from AI advancements.
Modern AI solutions can work alongside your existing systems, filling gaps and creating bridges between platforms that weren’t designed to talk to each other. This approach allows providers to gain efficiency without the disruption and cost of complete system overhauls.
Connecting Disparate Platforms Through Interoperability Solutions
Most healthcare providers operate multiple systems that don’t naturally communicate. Your billing software might not talk to your inventory system, and neither connects easily to your delivery tracking tools. AI-powered integration platforms act as translators between these systems.
Valere’s Business Interoperability solutions use application programming interfaces (APIs) to create secure connections between different software platforms. When a new order comes in through your EHR, the AI automatically pulls that information and shares it with your billing and inventory systems without anyone having to rekey the data.
For systems that lack modern connection points, robotic process automation (RPA) can fill the gap. These digital robots mimic human actions, logging into web portals, extracting information, and entering it into other systems just as your staff would—but without coffee breaks or typing errors.
One DME provider eliminated four hours of daily data entry after implementing these tools. Their staff no longer manually transfers information between their EHR, billing system, and delivery tracking software. The AI handles these routine tasks, freeing staff to focus on patient care instead of copy-paste operations.
Real-Time Analytics for Operational Decision Making
Making smart business decisions requires seeing the whole picture across all your systems. AI-driven analytics dashboards pull data from multiple sources to show you what’s happening right now in your business.
These tools can show you which referral sources have orders stuck in processing, which payers have the longest approval times, and which products have the highest denial rates—all in real time. This visibility helps you tackle problems before they grow into major issues.
Predictive analytics takes this a step further by forecasting future trends based on historical patterns. The system might notice that certain physicians always send incomplete orders for power wheelchairs and proactively flag those referrals for extra review, preventing delays before they happen.
Valere’s analytics tools help providers identify which processes would benefit most from automation. If the data shows your team spends 40% of their time processing oxygen recertifications, that area becomes an obvious target for your next AI implementation.
Enhancing Security and Compliance in Data Exchange
Sharing data between systems creates security challenges, especially with sensitive patient information. AI-powered security tools monitor these exchanges to protect patient privacy while enabling the connections needed for efficient operations.
These systems learn normal data access patterns and flag unusual activities that might indicate a breach. If someone suddenly downloads hundreds of patient records or accesses files outside normal business hours, the AI raises an alert before data can be compromised.
AI security tools also help maintain HIPAA compliance by ensuring that only appropriate information is shared between systems. When connecting your systems with outside partners like hospitals or physicians, these tools can automatically redact or encrypt sensitive information that shouldn’t be shared.
Creating a Unified Workflow Experience Across Multiple Systems
Despite having multiple systems running behind the scenes, your staff can work in a single, unified interface powered by AI. This approach dramatically simplifies training and daily operations.
Valere’s Point-of-Care Platform creates this unified experience by pulling relevant information from all your systems into one workspace. A customer service rep can see order status, delivery information, billing details, and documentation all in one place without logging into multiple systems.
AI workflow tools guide users through complex processes that span multiple systems. When processing a CPAP order, the system walks the user through insurance verification, documentation review, and inventory checking in a single workflow, even though these steps might involve three different underlying systems.
This unified approach reduces errors that typically occur when switching between systems. Staff no longer need to remember different passwords, navigation paths, or data formats across multiple platforms. The AI handles these complexities behind the scenes while presenting a consistent, intuitive interface to users.
SOURCES:
- Notable Systems Product Tour – https://notablesystems.com/product-tour
- AI in Healthcare: Examples and Real-World Uses – Multimodal – https://www.multimodal.dev/post/ai-in-healthcare
- AI in Healthcare: Uses, Examples & Benefits | Built In – https://builtin.com/artificial-intelligence/artificial-intelligence-healthcare
- Examples of AI used in health care – St. George’s University – https://www.sgu.edu/school-of-medicine/blog/ai-in-medicine-and-healthcare/
- 5 AI In Healthcare Examples That Will BLOW Your Mind – Lindy – https://www.lindy.ai/blog/5-concrete-examples-of-ai-in-healthcare—2024