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www.hexaware.com

Claims Data Capture

Overview ..............................................................................................................................3

Challenges ............................................................................................................................4

Proposed Solution ..............................................................................................................4

OCR + iProTrack as claims data entry system application ..................................4

RPA potential to reduce manual operations............................................................4

Experienced delivery team ..........................................................................................4

Credible case study to showcase claim capture to claim adjudication ..............4

Business Benefits ...............................................................................................................5

Table of Contents

Claims operations:Today, insurers around the world face a common challenge – to grow the business while remaining profitable. Uncertain economic conditions, regulatory pressures, operational inefficiencies, and the need for improved transparency and risk management only add to the complexity of this task. For health insurers to remain viable in this era of complex regulatory mandates and healthcare exchanges, they must review all areas of their plan to seek efficiency improvements and optimize processes to drive down costs. It is no longer an option to sit on the sidelines. Health insurers must automate and streamline to succeed.

Claims operations overview

Overview

Claims processing

Claims capture is not just a process - its impacting everything in the value chain. You’ve heard the phrase “garbage in, garbage out.” Nowhere is that more evident in an insurance plan than in the front-end of claims processing. Whether paper-based or electronic, if your input is not clean and accurate, then your downstream processes will be negatively impacted. Errors cause rework, auto-adjudication rates plummet, efficiency declines.

• What if you could improve the accuracy of front-end data capture?• What if you could streamline processes on the front end to further increase efficiency and auto-adjudication rates?• How might your bottom line be impacted by efficiency gains across claims operations?• Whether taking in claims, enrollment forms or other correspondence via paper or electronic format, it is critical that you capture the most accurate information at the onset.

Claims must be adjudicated in a timely and cost effective manner. The quality and accuracy of claim data going into the adjudication process remains a key factor in downstream efficiencies that drive internal administrative cost, as well as member and provider satisfaction. The number of ways to submit and code a claim is multiplying, further driving the need for consistently capturing high quality claim data from the onset.

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Challenges Some challenges that we face in claims processing are while 22% of the claims submitted were rejected, 1 out of every 5 claims are processed inaccurately, 4$ is spent on every manually claimed process, 0.86$ is the average cost per transaction, $400 bn is spent on non-core medical activities,$210 bn is spent every year on claims processing. This leads healthcare payers to lose an average of $3.2 billion every year from inefficient and highly manual processes. All of this leads to a dissatisfied provider group.

• High cost of Claim processing - cost more than $2.5 and manual claims more than $4 • Legacy systems in use that lead to lower productivity. With the modern new gen systems coming in, we migrate to newer systems for claims processing• Low OCR conversion rates leads to excessive manual intervention. Black form is not read by OCR • Manual keying errors and rework • Customer dissatisfaction due to delay in reimbursements • High rejection rates

Proposed SolutionThe target group here includes Health Insurers and large and medium mail room services providers.

1. OCR + iProTrack as claims data entry system application : We believe that as the need to control costs becomes more pressing and the expectation to meet regulatory compliance becomes more challenging, there is a quiet revolution taking place across organizations to make changes to a long standing paper queue.

Our solution for this is spread across 5 phases of the capture continuum:

Phase 1: Scan & Store - In today’s era, companies that continue to do business on paper based operations will surely find themselves at a disadvantage. This is the process of eliminating paper from paper intensive operations.

As straightforward as this sounds, one may have to justify the additional labor need to presort and separate and index the documents in various digital repositories. ,

Phase 2: Basic Recognition - Digitizing the documents is not enough, because even scanned documents are difficult to find and a lot of time needs to be spent on indexing the existing documents. This is why we deploy Optical Character Recognition (OCR) that will read and capture key information and automatically populate a variety of index fields. We can also use barcodes that can be interpreted quickly and reveal an extensive set of data.

Significant improvements in error rate, cycle time and staffing requirements are hard dollar benefits. But even in this process, we have manual labor who can insert separator sheets, then physically scan the documents and verify the integrity of data collected.

Phase 3: Intelligent Data extraction - Rather than simply gathering data for indexing, intelligent data extraction strategies pull more data from documents where data location may not be

known ahead of time. This enables both machine and handprint recognition to reduce manual keying. Your OCR should include Intelligent Character Recognition (ICR) engines and Natural Handwriting Recognition (NHR) engines to further reducemanual keying.

Phase 4: Distributed Capture : For organizations with a multitude of paper documents being generated in multiple locations, moving scanning and their functions to the point of origin saves on mail and courier expense, speeds data input and expedites the process of critical data inputs. This shorten the transaction processing time, cuts costs in shipping and, mailing, and opens up new opportunity for increased productivity.

Phase 5: Enterprise capture: is a universal capture portal where all documents that arrive in an organization are digitized and stored with the least amount of manual labor. In this phase, documents are intelligently identified using advanced text analytics. All relevant data from these documents id captured, validated and automatically sent to data repositories. As a result, only a handful of people ae required to manage data exceptions.

2. RPA potential to reduce manual operations: Our approach to implement RPA in any operations is again spread across 4 phases:

• Prioritize: Here we categorize the processes basis stability, complexity, scale, risk and estimated automation potential.

• Assess: We meet the Insurance SMEs who run us through how the processes are implemented at the client’s premises. We then do a time and motion study, we do an RPA analysis and create value stream maps and a business case is developed.

• Standardize: We then understand the process variations and standardize wherever possible. We improve the level of task repeatability and streamline hand offs.

• Optimize: in order to optimize, we eliminate the non value adds and implement a control framework to enable continuous improvement.

• From a digital asset point of view for claims data capture, we have 2 BOTS - Document classification BOT and Indexing BOT. These are Hexaware Intellectual property that have been developed for our existing clients. These are currently a part of our Robobank - our bot repository and can be readily used with customizations for our new clients. This reduces the turnaround time for BOT implementation and the monetary as well as time benefits, in turn, are passed to the client.

3. Experienced delivery team: our exceptional delivery team and insurance SMEs have a rich experience of working with these all these years. In the satisfaction survey with our insurance clients, we were ranked a 4/5.

4. Credible case study to showcase claim capture to claim adjudication: We are proud to state that our insurance industry retention rate is 100%, which essentially means that we have successfully retained all our insurance clients ever since the association. We have proactively implement Coordination of benefit bot for one of our old insurance and benefits administrator, so much so that our current cost per transaction is lower than that in their captives.

2. RPA potential to reduce manual operations:

3. Experienced delivery team: and insurance SMEs have a rich experience of working with these all these years. In the satisfaction survey with our insurance clients, we were ranked a 4/5.

adjudication: industry retention rate is 100%, which essentially means that we have successfully retained all our insurance clients

4. Credible case study to showcase claim capture to claim adjudication: industry retention rate is 100%, which essentially means that we have successfully retained all our insurance clients

adjudication: industry retention rate is 100%, which essentially means that we have successfully retained all our insurance clients

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Business Benefits

Providers are the worst affected lot in the

lengthy claims adjudication process.

Reducing the turnaround time of the process will

reduce the delay in reimbursements.

If your input is not clean and accurate, then your

downstream processes will be negatively impacted.

Errors cause rework, auto-adjudication rates

plummet, efficiency declines. Thus, it is

important in the claims operations process that we

get the first step of capturing the data

accurate for improved auto adjudication rates

Automated processing will make this a straight through process with

reduced average handling time along with higher accuracy levels. It will

also reduce the duplication of efforts. If

front end electronic data capture can be managed electronically, the team size required to manage this will be very small.

Improved Productivity:By minimizing front-end data capture submission

errors, health insurers can increase auto-adjudication

rates, reduce costs and increase provider and member satisfaction

dramatically.

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