Intelligent Process Automation for RCM New Technologies Pave the Way. Authors: John Fundingsland Dan Hillman.

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1 Intelligent Process Automation for RCM New Technologies Pave the Way Authors: John Fundingsland Dan Hillman

2 Introduction Revenue cycle professionals have long recognized that many of the tools and processes that they rely on to manage operations across the revenue cycle are the result of years of ad-hoc workarounds. These reflect the nearly unmanageable growth of regulatory and financial systems they must work in. Further, the current healthcare system is changing almost daily, as new technologies and new approaches to health care delivery are challenging established ways of doing business. The constant state of change in health care financial operations and the dizzying pace of change in information system technology has created numerous opportunities for disruption and step change improvements in the ways and means that revenue cycle practitioners do business. The economics of this opportunity is enormous. In 2016, billed professional and facility fees in the United States accounted for more than $2.7 trillion in healthcare spending, and produced over $55 billion in bad debt1. This is clearly an unsustainable situation and a major drain on the health care economy, resulting in untold hours of productivity loss. Re-capturing just 1% of that lost revenue could yield over $500 million in recovered cash. How much of that is on your organization s balance sheet? What if there were a means to accomplish this in a way that also reduced the overall cost to collect? What if it were possible to accomplish this with the same or fewer resources and with higher quality and consistency? Intelligent process automation is a leading approach to making this a reality today. Current Sources of Inefficiency in Revenue Cycle There are many ways to understand health care providers position relative to best in class performance when it comes to revenue capture. In a business process as complex as revenue cycle, there are many points along the way to take stock of performance. One key indicator is adherence to HFMA s MAP keys model, which provide an overall best practice guideline, and more specifically, the cost to collect for any given account. Our proprietary research shows that 41% of the cost to collect comes from back-end functions and also show that staff spend an average of 1-2 hours per day on hold while communicating with payers. A further source of inefficiency in the current process employed by most revenue cycle departments is that up to 35% of claims after primary payments are incorrectly transferred to patient pay without detecting the appropriate secondary payer. These dismal statistics should not suggest that there have not been efficiency gains in other parts of the revenue cycle, but despite all of these improvements and movement toward standards and common measures, despite better practice management technology, clearinghouse edits and relationships, tools integration and improved analytics, most revenue cycle departments still have vast amounts of processing done manually. Staff often either ignore new directives and revert to working within their comfort zone or change management systems are not robust enough to ensure long term sustainable adherence to the new operating models. Without a fundamental change to our approach to change management, business process improvement, and technology adoption, the industry will continue to lag behind other sectors of the economy that have embraced new approaches such as intelligent process automation, also commonly referred to as robotic process automation (RPA). For the purposes of this article, intelligent process automation includes machine learning and artificial intelligence technology, while RPA is concerned with the application of business rules in an automated fashion that eliminates or reduces the need for manual processing. The need for greater application of RPA, machine learning, and artificial intelligence to the revenue cycle has been recognized by many leading healthcare providers, including Catholic Health Initiatives (CHI) and others. Examples of RPA application to a wide variety of revenue cycle and financial processes at large and small health care providers are becoming more widely known and RPA adoption is accelerating.2 Among the several processes within revenue cycle that are ripe for application of RPA are: Payer Contact Electronic Data Exchange Information (EDI) processing Low Balance Collections (under $30000) ¹ HFM, Bad Debt Expense Benchmarks, February 2017 ² Robotic Disruption and the New Revenue Cycle, Hfm, HFMA, September 2017

3 When considering how to apply RPA to revenue cycle, a helpful model is shown below. By evaluating the relative extent of unstructured information and the complexity of decision making in a process, it is possible to prioritize and position a process in terms of the impact that RPA can have on driving efficiency and improving quality. Figure 1 below shows various revenue cycle processes mapped against these dimensions. Figure 1: Robotic Disruption and the New Revenue Cycle, Hfm, HFMA, September 2017 Looking at those processes where automation can have a high impact (lower left of the graphic), it is clear that back end processes such as insurance discovery, appeals and denial management have very high potential for improvement using RPA. So what can RPA offer to improve productivity in this regard? RPA offers three key benefits for revenue cycle management: Processing Information via Intelligent Machine-driven Process: RPA supports enhanced security. Human points of failure with regard to PHI security are eliminated when the information is processed via intelligent machine-driven processes Uniform Application of Performance via RPA: RPA is a precise means for monitoring quality and consistency. Uniform application of performance standards is automatic with RPA-led approaches Centralizing Approval mechanism: Technology evolution is moving much faster than process evolution and can be adjusted much more quickly to meet changing reimbursement guidelines. The typical issues surrounding deploying a new process or business rule (training, quality control) are eliminated as one central point of update and approval is required to affect change across an organizational process Automation, considered either as RPA or the more comprehensive approach, intelligent process automation, is the beginning of a technological journey that must be mapped to and supports the overall strategic goals of the enterprise. Decoupled from this context, it is not likely to be successful, but if supported and amplified by the overall strategic framework of an organization s growth plan, it will dramatically impact results for the better. Applying RPA to the Revenue Cycle The following several examples provide a framework for applying RPA to revenue cycle business process, in particular, back end processes such as insurance A/R follow up and payer contact. Payer Contact and Claim Data Collection: Data retrieval for patient and billing information is a varied process and its implementation creates logistical and processing hurdles that are often solved by manual means. For example, IVR systems and web portals used to collect data are inherently inefficient. One of the more burdensome inefficiencies is the management of login credentials. Credentials often expire monthly and are required for each individual accessing a system. It is difficult to manage and expired login credentials can force the user to spend time resetting or in some cases, bypassing and picking up the phone. Outsourcing some of these may reduce the cost or burden on the provider s revenue cycle staff, but it just transfers the inefficiencies to another party.

4 Payers have invested heavily in web portals, but have not realized the sought after benefits of call avoidance. Maintaining log in credentials is a thorn in the side of many system administrators, particularly when third party partners are involved or if high turnover is a concern. The constant issuing, deactivating, and resetting of passwords is time consuming and a drain on productivity. This is an example of a business process that can be dramatically improved using RPA. Payer contact is one of the more vexing challenges in improving productivity of revenue cycle operations. The amount of time spent on hold with payers can take up to several hours of productivity out of an associate s day. RPA has been deployed to allow providers to schedule when and how they want their associates to be contacted by a payer even to the point of specifying which accounts the associate wants to discuss with the payer. By eliminating the need for an associate to place a call and navigate the payer s IVR system, thousands of hours of productive time can be recovered each month thereby lowering the cost to collect. Claim Status Processing: Actionable or enhanced claim data processing represents another area where RPA can have a significant impact on revenue collection. For example, it is not uncommon for account information to be lumped together by payers, often simply because of incorrectly documented subscriber identifiers. Obtaining remit information though a RPA-driven system from payers to supplement claim status responses, for a super 835 provides a much more comprehensive view of the claim. Adding remit data such as patient responsibility to claim status responses will then drive higher call avoidance rates. If a process such as this is enhanced with RPA, and for instance, an additional 25 data elements are added to an 835 response, the impact on productivity and ability to collect even low balance accounts increases dramatically. Eligibility and Insurance Discovery: Eligibility and insurance discovery are important steps in the creation of clean claims that hold the highest potential for payment. These components are also important in managing the Accounts Receivable (A/R) process. Using RPA-driven advance search and discover technology with a typical process, hundreds of payers can be searched for coverage and benefit details with limited information on input and most importantly, a single sign-on to a platform that provides these data elements in an automated framework. This is particularly important when coverage information is not readily available as may be the case with EMS billing, for example. The ability to see real time eligibility within any workflow system is another key advantage to speeding up the claims resolution process. While many systems and clearing houses offer this benefit, when used in conjunction with RPA-led coverage discovery, the results and data can be far more comprehensive and supportive of a robust and efficient claims management process. Finally, the delay in collecting on claims and patient responsibility in particular are made worse by outdated address or contact information. RPA-led processing provides better data without manual intervention, reducing return mail and time spent sending new statements or searching for addresses using manual methods. Case Study Low balance collections are a segment of A/R that are difficult to collect because of the labor intensive nature of the process and the generally low level of effort placed on these accounts. RPA-led solutions can be used to automate the process to the point where meaningful recoveries can be achieved at a cost-to-collect that makes sense from an expense perspective as well. The following case study, shown in Figure 2 below illustrates how significant recoveries are achievable from an inventory of aged small balance accounts. In this case, the average claim age was 222 days, the average claim value was under $700, and the total recovery was 16% (based on placed value). These results could not have been achieved using traditional manual-based methods and are illustrative of the power of robotic process automation to enhance productivity to the point where a significant additional component of revenue can be captured that was previously written off as uncollectable revenue/bad debt.

5 Financial Class Volume $ Value Avg/Claim Avg Age Collections Active Value Blue Plan 64,518 $57,433,707 $ $13,684,142 $5,660,331 Commercials 285,289 $158,275,552 $ $20,732,775 $22,620,728 Medicare 45,624 $37,813,019 $ $3,892,382 $4,529,415 Medicaid 25,387 $22,785,892 $ $1,937,682 $5,364,368 MVA 8,823 $12,397,182 $1, $2,226,156 $- WC 24,155 $19,623,149 $ $5,788,992 $42,798 Self-Pay 3 $5,050 $1, $- $- G. Total 453,799 $308,333,551 $ $48,262,129 $38,217,640 G. Total (Collected from placed value) 16% Commercials 13% Medicare 10% Medicaid 9% MVA 18% Work Comp 30% Figure 2 Summary The promise of RPA to enhance productivity, reduce costs, and allow an organization to grow without adding resources, has been well documented in many other industries. Its impact is only beginning to be felt in healthcare. Leading health care delivery organizations and best in class revenue cycle departments have seen significant improvements in bottom line results by applying these new technologies and approaches, in solving what have been some of the most intractable and labor intensive processes in Accounts Receivables. Application to upstream revenue cycle processes such as patient registration, coding and manually driven billing processes are also amenable to RPA applications. About the Authors John Fundingsland is the Vice President of Healthcare Financial Services at Hexaware Technologies. He is tenured and experienced executive who has led diverse operational teams in fast-paced environments to achieve extraordinary financial and operational results. He brings strong technical and business qualifications with a track record of hands-on success running revenue cycle management organizations and is a leading advocate of technology driven solutions in healthcare financial operations. Dan Hillman is the Vice President of revenue cycle at Hexaware Technologies and is responsible for client requirement analysis and solution development in the revenue cycle function. He brings over 30 years of diverse experience in healthcare financial operations, business operations planning and global service delivery operations.

6 About Hexaware Hexaware is the fastest growing next-generation provider of IT, BPO and consulting services. Our focus lies on taking a leadership position in helping our clients attain customer intimacy as their competitive advantage. Our digital offerings have helped our clients achieve operational excellence and customer delight by Powering Man Machine Collaboration. We are now on a journey of metamorphosing the experiences of our customer s customers by leveraging our industry-leading delivery and execution model, built around the strategy Automate Everything, Cloudify Everything, Transform Customer Experiences. We serve customers in Banking, Financial Services, Capital Markets, Healthcare, Insurance, Manufacturing, Retail, Education, Telecom, Professional Services (Tax, Audit, Accounting and Legal), Travel, Transportation and Logistics. We deliver highly evolved services in Rapid Application prototyping, development and deployment; Build, Migrate and Run cloud solutions; Automation-based Application support; Enterprise Solutions for digitizing the back-office; Customer Experience Transformation; Business Intelligence & Analytics; Digital Assurance (Testing); Infrastructure Management Services; and Business Process Services. Hexaware services customers in over two dozen languages, from every major time zone and every major regulatory zone. Our goal is to be the first IT services company in the world to have a 50% digital workforce. NA Headquarters Metro 101, Suite 600,101 Wood Avenue South, Iselin, New Jersey Tel: Fax: India Headquarters 152, Sector 3 Millennium Business Park A Block, TTC Industrial Area Mahape, Navi Mumbai Tel : Fax : EU Headquarters Level 19, 40 Bank Street, Canary Wharf, London - E14 5NR Tel: Fax: APAC Headquarters 180 Cecil Street, #11-02, Bangkok Bank Building, Singapore Tel : Fax : Safe Harbor Statement Certain statements in this press release concerning our future growth prospects are forward-looking statements, which involve a number of risks, and uncertainties that could cause actual results to differ materially from those in such forward-looking statements. The risks and uncertainties relating to these statements include, but are not limited to, risks and uncertainties regarding fluctuations in earnings, our ability to manage growth, intense competition in IT services including those factors which may affect our cost advantage, wage increases in India, our ability to attract and retain highly skilled professionals, time and cost overruns on fixed-price, fixed-time frame contracts, client concentration, restrictions on immigration, our ability to manage our international operations, reduced demand for technology in our key focus areas, disruptions in telecommunication networks, our ability to successfully complete and integrate potential acquisitions, liability for damages on our service contracts, the success of the companies in which Hexaware has made strategic investments, withdrawal of governmental fiscal incentives, political instability, legal restrictions on raising capital or acquiring companies outside India, and unauthorized use of our intellectual property and general economic conditions affecting our industry. marketing@hexaware.com