STOPPING ICD-10 FRAUD BEFORE IT HAPPENS

Transcription

1 STOPPING ICD-10 FRAUD BEFORE IT HAPPENS How will the transition to ICD-10 coding affect healthcare payers? PRODUCT POSITIONING PAPER

2 2 INTRODUCTION Capturing accurate quality clinical documentation is a critical factor in providing quality care, and ultimately has the biggest connection to generating revenue. The change in the U.S. healthcare coding system, from ICD-9 to ICD-10, creates added complexity and a steep learning curve for any organization that is involved in healthcare billing. Although the deadline could shift, a federal mandate was issued requiring providers to move to ICD-10 by Oct This opens new avenues for fraud and abuse, especially during these times of transition, and the payer/insurance community needs to be on high alert. ARE INSURANCE PROVIDERS READY? The healthcare system and insurance providers are required to make the change to ICD-10 classification codes. This adjustment will directly affect all medical payers since paying claims in the health insurance world is administered by classification codes. The new coding system will provide more granularity, providing not only a patient s medical condition, as well as the treatment and services provided by the healthcare providers and payers (e.g. billing). And this includes Medicare, Medicaid and private health payers that service them. With the move to ICD-10, the entire healthcare eco-system will benefit. The new coding increases information accuracy that will be used to identify patterns of criminal fraud behavior. It will indirectly target insurance thieves and limit the damage they can do. Meanwhile, fraud will likely increase during the adjustment period while healthcare payers adjust to the ICD-10 coding system, and billions of dollars will be on the fraud crime experts radar. Anti-fraud analytical systems will be pressured to adapt and the re-calibration process is complex. The questions that should be raised are: are the healthcare payers ready for the greatest reform in the U.S. s healthcare system? How are they preparing against potential fraud threats? The Move to ICD-10 Means Increased Information and Granularity, but also Increased Complexity The reasons for the change to ICD-10 are clear and the process is long overdue. Moving to ICD-10 is intended to bring the benefits of greater coding accuracy, higher data quality, more efficiency, lower costs, better utilization of electronic health records, and better alignment internationally (other countries have been using WHO s ICD-10 revision). ICD-10 is also expected to enable greater payment integrity analysis, trend analysis and business and patient analytics. One of the most pressing reasons for the change, however, is that many chapters of ICD-9 are simply full and cannot accommodate new codes. The conversion expands the number of codes by approximately 800 percent from 17,000 to nearly 155,000. In addition to the jump in the number of codes, ICD-10 expands the length of diagnosis codes as well, by adding in two more digits, resulting in codes that are three to seven digits long. Moving to the new system creates a steep learning curve and huge amount of added complexity for anyone associated with healthcare billing. KEY DIFFERENCES PROCEDURE CODES ICD-9-CM v. ICD-10-PCS FEATURE ICD-9-CM ICD-10-CM CODE SET ICD-9-CM Volume III ICD-10-PCS (Procedural Classification System) STRUCTURE _ Minimum of 3 digits, maximum of 4 digits, decimal point after the second digit _ Numeric _ Limited multiaxial structure _ Minimum of 7 digits, no decimal point _ Alphanumeric _ Multiaxial structure - each code character has the same meaning within the specific procedure section and across procedure sections, where possible SAMPLE CODES _ 47.01, Laparoscopic appendectomy _ 0DTJ4ZZ, Laparoscopic appendectomy X X X X X FORMAT Category Biology or disease manifestations Section Root Approach Qualifier Operation Significant axis, such as anatomical site Sub classification (e.g., mode of diagnosis, anatomical site) Body System Body Part Device

3 3 Complexity and Uncertainty Paves the Way for Errors, Fraud and Abuse Unfortunately, much of today s healthcare fraud is committed by providers who feel that they are not getting paid what the insurance companies owe them. Fraud is often thought of as their way to recover what is due. With ICD-10, while its added granularity and complexity will be beneficial in the long run, it also makes it harder to recognize improperly coded diagnoses and treatments. For example, there will only be a small percentage of ICD-9 codes that will map directly to ICD-10, and all other codes will lose information or need someone to assume the specifics originally intended. This means that the quality and accuracy of code mapping is directly related to the quality of the person doing the translation. Some may find it tempting to use this period of transition to their benefit, and accidentally enter the incorrect codes then claim it was a mistake if it gets caught. Fraud and improper payments as an industry problem will get worse before they get better. Unfortunately, much of today s healthcare fraud is committed by providers who feel that they are not getting paid what the insurance companies owe them. Why Some Fraud Systems Can't Fix the Problem Most fraud is detected by transactions that don t conform to norms, but with ICD-10, just about everything will be non-conforming. Even automated rules-based fraud prevention systems that have been effective in managing ICD-9 codes in the past, will be lost when it comes to ICD-10. After all, the rules have changed. You can t write a rule about behavior you haven t seen or don t fully understand. Because ICD-10 codes are so different from ICD-9 codes, there will be completely new vulnerabilities for potential fraud. Mappings and rules-based systems aren t going to know what the problems are for a while. False positives will be generated because rules need to be all reconfigured or designed from scratch. Cases will be sent to resolution, but they will be out of context in the new standard. All this will lead to an explosion of alarms and supposed errors that will quickly become a coding nightmare. With the introduction of ICD-10, there are some critical questions every Payer will want to ask: _How reliable is the data? _ Are there holes in the system you need to be aware of while the mapping exercise is underway? _ Are there intentional errors or misrepresentations made by fraudulent billers? _ Will billers use both ICD-9 and ICD-10 codes- based on whichever is more advantageous? _ Who is at fault for coding errors - the payer, the provider, the clearinghouse? _Which fraud alerts are false positives due to poor data quality? _ How do you perform trending and peer group analysis to determine which claims are valid vs. outliers worthy of scrutiny? Advanced Fraud Management Requires a Combination of Approaches Neglecting the complete cycle of Fraud Management and relying on a single approach to detect fraud, no matter how robust, is ineffective because it also creates a single point of failure that, once breached, can potentially allow complete access to systems and sensitive data. Instead, healthcare payers must create a multilayered approach to fraud detection and management that identifies, contains, and responds to new types of fraud to protect an organization s critical assets and data. Below are five steps providers and insurance companies should take to improve fraud detection and response: > ADVANCED FRAUD MANAGEMENT > Prevent Detect Analyze Resolve Learn Investigate

4 4 Prevent and Detect When it comes to fraud prevention, assume now that the unscrupulous will find any hole in your system and take full advantage of it. It is in every organizations best interest to prepare better documentation to support diagnoses or claims that are questioned, and have an automated system in place to analyze records and find any issues you can correct. No one can respond to fraud attacks they don t know about. Historically, payers have relied on manual or automated rulesbased systems to detect fraud. The advantage of using a rulesbased system is that businesses can encode knowledge and use automated tools to undertake the complex tasks of detecting fraud. It adopts a common sense approach, in which you don t need to process a million variables to find a fraud type, and can instead use pre-determined rules to examine specific complex variables to quickly identify fraud with a high rate of accuracy. But as mentioned earlier, this approach will only be partially successful; as it depends entirely on the strength of the rules being employed, and with ICD-10 the old rules will not apply. Data-driven analytics, in contrast, catch emerging behavior patterns and problems that aren t obvious enough yet to capture in a policy rule. Rules based systems can only detect specific types of fraud for which rules have been established. In other words, rules-based systems can protect your business against yesterday s threats, but are ineffective against emerging ones. More effective modern fraud management techniques combine rules-based systems and unsupervised models, which take a set of information and use big data technologies to process analytical models to look for unknown types of fraud. This approach collects information from external sources that go well beyond normal inputs used to create profiles. Using cases that are 100 percent matches for fraudulent activity as a baseline, predictive fraud systems that rely on analytics look for providers with profiles with lower percent matches and creates correlations between users fitting that profile. These providers are not automatically identified as fraudsters, but since parts of their profile match typical fraudster behavior, they can be highlighted for fraud management teams to investigate further, in order to determine if it is a new type of fraud for which new rules must be created. WeDo Technologies RAID Fraud Management System uses a hybrid approach that combines the best rules-based and unsupervised approaches to achieve better results. The output of statistical methods is used to create, correct and improve new rules. The accuracy of the rule-based feature is augmented by applying advanced fraud detection procedures based on statistical techniques and machine learning methods to generate alarms for resolution, or even enrich the detection rules knowledge base. In addition, RAID:FMS offers an assisted, easy-to-use interface to simplify the task of rule management for both static business rules or dynamic ones. Businesses don t need experienced rule developers to manage the system to provide a usable and accurate solution. RAID FMS ADVANCED FRAUD DETECTION Advanced Fraud Detection (AFD) takes RAID:FMS to the next level of intelligent fraud detection. AFD empowers fraud managers with an analytical tool that allows them to build their own data mining models, customized to the insurance industry and their requirements, by using a simple step-by-step wizard. The visibility and automation that AFD provides make service providers networks more secure and reduces operational costs. More effective modern fraud management techniques combine rules-based systems and unsupervised models, which take a set of information and use big data technologies to process analytical models to look for unknown types of fraud.

5 5 Analyze and Investigate With ICD-10, unknown fraud patterns are more of a concern and the ability to make well-informed decisions requires a solution with the necessary visualization capabilities to enable the data to be actionable and usable. Simple yet powerful visualization tools can lay the foundation for making important decisions during the fraud detection process. Ease of use is also critical to the success or failure of a fraud management system s information dashboard. Having tools that integrate with existing information for fraud investigation is mandatory to help managers make informed decisions by creating a centralized, aggregate view of information from disparate sources. This tool can also accelerate situational awareness and support faster, more informed decision-making across departments. WeDo Technologies RAID Fraud Management System presents an easy-to-use interface for an hybrid approach that combines the best rules-based and unsupervised approaches to achieve better results. LINK ANALYSIS Being able to easily interpret large amounts of events to quickly identify potential fraud risks can be a challenge. To help fraud managers identify changes or patterns not visible in rows and columns of data. RAID:FMS includes an advanced set of visualization tools capable of highlight and providing context during detection, investigation and case resolution of fraud scenarios.

6 6 Resolve and Learn (Pattern-based Knowledge Base Enrichment) As discussed, in the current fraud landscape, rules-based systems alone are not enough to stop emerging fraud types. At the same time, always relying on big data analytics to detect fraud may be tempting, but it s expensive and time consuming. Fraud management systems that combine the two approaches provide the best of both solutions, using previously analyzed suspicious patterns to enrich the rules knowledgebase. This eliminates repetitive and time-consuming decisions for analysts when a new suspicious pattern is found. But knowledge can do more than improve the rules. Case Management tools, when integrated with investigation and visualization tools, also provide knowledge management capabilities that speed up the fraud management process, increase productivity and reduce operating costs. In addition to supporting decision making, this knowledge base goes beyond providing faster answers: it is a valuable tool for seamlessly creating known errors and helping to identify root causes, important aspects of fraud incidents and incident prevention. Case management tools are also important because they provide a centralized access to known fraud information from all technologies and create a benchmark for future cases. As it is important to share processed information with other people and departments, the tool should allow all parties to use the same language and make decisions using the same tools, and enables skills for fraud prevention to be built within an organization. Think of case management as a collaborative process that assesses, plans, implements, coordinates, monitors, and evaluates the options and steps required to address fraud investigation and stoppage. COMPREHENSIVE PROTECTION FOR INSURANCE FRAUD SCENARIOS The power, precision and flexibility of RAID s robust rules engine provides insurance companies with a comprehensive fraud rule library. RAID:FMS enhances this coverage by combining the accuracy of a knowledge base of tested rules with the ability to easily fine tune and develop new ones. RAID FMS CASE MANAGEMENT RAID FMS Advanced Case Management is a comprehensive platform for social collaboration, faster resolution and contextual analytics. It provides the most innovative social collaboration technologies into your business environment for full integration across fraud investigation processes. From collaborating alongside fraud scenarios case escalation to following people and case resolution, you ll eliminate errors and get work done in ways you never thought possible.

7 7 In Conclusion The move to ICD-10 provides countless avenues for fraud and abuse. The benefits of an automated fraud prevention system that combines business rules with predictive analytics and machine learning cannot be overstated. Why not rely on big data alone? Because business rules help to operationalize the benefits of big data. They act as a decision tree, taking the data and parsing it in a way that reduces the complexity, and delivering alarms and alerts that have already been verified to meet specific decision criteria. Predictive analytics, on the other hand, helps businesses turn uncertainty about the future into manageable probabilities. Combining the two provides actionable intelligence that can deliver the one-two punch needed to help to mitigate the risk associated with the transition to ICD-10. With an automated solution that leverages business rules combined with big data, payers can flag outliers and stop fraud before it happens, enabling businesses to analyze data to discover priorities, identify solutions and take action before it s too late. Potential Benefits of an Hybrid Fraud Management Solution for ICD-10: _ Gain valuable information about areas for further investigation _ Determine which service lines will be most affected _ Identify areas that require clinical documentation review _ Review managed care contracts and negotiate terms that will be more protective _ Leverage analytics and financial impact data to educate and support staff SCAN THIS QR CODE TO LEARN MORE ABOUT WEDO TECHNOLOGIES INSURANCE SOLUTIONS. Download a QR code reader to your mobile phone at the Apple Store or in the Android Market for free. OFFICES PORTUGAL _ Lisbon PORTUGAL _ Braga AUSTRALIA _ Sydney BRAZIL _ São Paulo BRAZIL _ Rio de Janeiro BRAZIL _ Florianopolis EGYPT _ Cairo FRANCE _ Paris IRELAND _ Dublin MALAYSIA _ Kuala Lumpur MEXICO _ Mexico City POLAND _ Warsaw SPAIN _ Madrid UK _ Reading USA _ Chicago USA _ Washington ON THE WEB GENERAL INFORMATION customerservices@wedotechnologies.com WHY WEDO TECHNOLOGIES? WeDo Technologies is a worldwide leader in Enterprise Business Assurance, providing software and expert consultancy, to intelligently analyze large quantities of data from across an organization helping to negate or minimize operational or business inefficiencies and allowing businesses to achieve significant return on investment via revenue protection and cost savings. Revenue Assurance, sometimes also called Profit Protection or Loss Prevention and Fraud Management, are the domains where WeDo Technologies - through its Software and Services - has become recognized as a constant innovator and true worldwide market leader. WeDo Technologies works with some of the world s leading blue chip companies from the retail, energy and finance industries, as well as more than 180 telecommunications operators from more than 90 countries, through almost 500 highly-skilled professionals. WeDo Technologies shareholder, Sonae Group, is the biggest private non-financial employer in Portugal, with around 40,000 employees and presence in more than 60 countries. WeDo Technologies, AN INNOVATOR IN REVENUE AND BUSINESS ASSURANCE SOFTWARE. Assuring your Business for the Future. FOR MORE INFORMATION ON WEDO'S FRAUD PREVENTION SOLUTIONS download our healthcare brochure, or request a meeting to speak with someone on our team or to schedule a demo.