Automating Claims Classification & Data Extraction:
Leverage Pre-Trained AI to Double Claim Processing Capacity & Reduce Claim Resolution Time
The Roots: What spurred this on?
Fraudulent healthcare claims in the US cost $68B per year,
increasing vigilance across insurers and resulting in lengthy claim validation processes to ensure accurate payouts.
In 2021, 17% of healthcare claims were denied and only 0.2% appealed,
increasing administrative burden on the healthcare staff and decreasing customer satisfaction with insurers.
In 2018, 92% of prior-authorization issues contributed to care delays,
with only 25% of pre-authorization work being automated and 84% of insurers classifying this work as extremely high burden.
It takes healthcare providers 15 hours to complete one pre-authorization request,
34% of providers have dedicated staff working exclusively on these requests.
How do these challenges germinate and why are they so difficult to eradicate?
1. Incomprehensible Volumes
Service providers and insurance payers are burdened by the overwhelming volume of documentation involved in processing pre-authorization and claim requests.
2. Gaps In Claims Automation
In healthcare, according to McKinsey only 10% of medical record review is automated, leaving most of it to manual review. On the insurer side, each claim takes 40 minutes and costs an average of $15 to process.
3. Difficult to Transfer Knowledge
AI models are getting increasingly more intelligent these days but the insurance claims processing realm is incredibly nuanced and contextualized for AI models to completely take over. As it stands today, the final approval of claims permutations can successfully and accurately be achieved only by the human professionals.
4. Human-Centred Approach
The gap with existing Claims automation solutions is the lack of empathetic interactions with customers in dire life situations. It is still an on-going challenge for insurance organizations to implement an efficient AI automation with a human-centered approach.
What can Adlib do to help?
Adlib's AI is designed to assist and enable professionals to gain higher efficiency and accuracy in pre-processing claims for more accurate review while achieving higher job satisfaction, improving accuracy of settlements and supporting customers in their most difficult times.
Collaborate with us as we harness the power of pre-trained AI to overcome these challenges.
Stemming business challenges
Payout Delays & Customer Dissatisfaction
Manual claims pre-processing and validation is time-consuming, demanding on resources, and ultimately delays payouts and reduces customer satisfaction.
Increased Chance of Fraud
Varying approaches and training across business units may cause errors in claims classification and validation increasing rework, demand on resources and the chance of fraud.
Misfiling & Retrieval Issues
Human errors may cause misplaced or incomplete information, complicating future retrieval, audits, lititgation and customer churn risk.
Scalability & Cost Concerns
Staff shortages, increased turnover and expertise gaps hinder growth and elevate operational costs.
Benefits of automating with Adlib's Pre-trained AI
Happier, More Empathetic Staff
Automated assembly of archive-ready, machine-readable, metadata-rich claims documentation frees up time and helps minimize staff burnout, enabling your front-facing workers to focus on delivering compassionate customer service.
Faster Review & Reduced Fraud
More efficient claim data prep and reduced chance of incomplete, inaccurate information enable your organization to expedite claims reviews and minimize fraudulent payouts.
Proven Compliance & Accuracy
Pre-trained AI gets the work done accurately and in adherence with regulatory requirements every single time, eliminating audit, compliance and litigation risk.
Adlib AI Grows With Your Needs
The elasticity of Adlib's cloud-based solution can support spikes in demand during open enrollement period or flourishing growth without resource constraints.
reduction in claim settlement time & processing costs
forecasted chance of error in claim assessment
more claims processing capacity without growing the team
How It Works:
Leverage custom-built and pretrained AI model to drive evidence and claim documentation classification
How It Works:
Leverage custom-built and pretrained AI model to facilitate extraction of critical metadata from claim submissions.
How It Works:
Annotation module tracks low confidence classification and data extraction entries enabling the human in the loop to correct & modify the class assigned to each document or extracted metadata.
How it Works:
Automated retraining capability enables the underlying models to continually improve knowledge libraries for even better performance.
How It Works:
The systems seamlessly plugs into existing DMS, ICMS systems and other systems via API integration.
How It Works:
Advanced document assembly functionalities automatically standardize 300+ document types, including PDF, Word, TIFFs, Images and Excel, into conformant, review- and archive-ready formats reducing technical rejections from automated approval systems.
Here Is How You Can Plant Your Own Innovation Seeds!
An ideal grower would be:
A Passionate Innovator
You're the curious brains behind your wildest ideas, blending geeky enthusiasm with innovative thinking.
You excel in building bridges, connecting with diverse individuals, and turning conversations into creative collaborations.
You're a masters of mixing "constructive feedback" with a sprinkle of positive vibes and a dash of humor. You turn feedback into a fun growth recipe!