Todd Cooperman PharmD MBA RPh SVP, Clinical Analytics and R&D at RJ Health

&Wendy Sullivan, MPH, Director of Data Informaticsby:

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been to apply headcount (ex. case workers and analysts), implement supporting procedures (ex. prior au-thorization), or outsource to a full-ser-vice vendor (ex. PBM, medical billing, or payment integrity partners). Any of these efforts, or com-bination of them, has resulted in suboptimal out-comes, limited visibility, and an unsustainable environment for controlling healthcare costs. In our medical drug claim analysis experience, we have found that plans are consistently pricing drugs sub-optimally and allowing claims with potentially inappropriate number of units to pass through to payment. Figure 1 shows pricing and unit outlier rates for four health plans that we have assisted in improving the medical drug claim process.

Figure 1: Percentage of paid amount variance associated with inappropriate pricing and units

Overview

This whitepaper provides structure and a case study to demonstrate the value of an automat-ed medical drug claim edits solution. RJ Health has implemented a rules-driven edit platform to reduce overall medical drug claims errors and improve operational efficiency.

Introduction

Appropriate reimbursement for drugs covered by the medical benefit requires more data and structure than most medical claims or billing systems were originally intended to process. This applies to a greater extent when the systems are proprietary. The tendency to solve this issue has

Medical Drug Claim Edits to Optimize Reimbursement

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quarterly, and annual variability in data updates. Unlike other services or equipment categories where there is more of a “1 to 1” match between products and coding, the medically covered drug category often has “1 to many” associations for which one drug could have many companion mappings. Moreover, those associations can repeatedly change over time. As an example, Figure 2 shows how within specific therapeutic classes there is significant variability in the number of NDCs and pricing, which both need to be accounted for when ensuring proper medical drug claim processing (Figure 3 shows the same data without the top 3 classes with the largest variability to assist in the visualization of the other therapeutic classes).

Compared with the infrastructure and data that has become standard procedure within pharmacy benefit systems, medical benefit systems were not originally developed to manage and process medically administered drugs. Over time the management and coverage of medically covered drugs have expanded and become more complex, from both payment and clinical management perspectives. To address these changes, health plans have modified systems and edits to adjust to the challenge. This requires an increased level of complexity accounting for the sophistication and variability of how medically covered drugs are grouped, coded and priced. In addition, the expansion of the specialty drug category has brought an added challenge in the form of monthly,

Figure 2: NDC and pricing variability within specific therapeutic classes

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The increased complexity associated with proper drug reimbursement imparts challenges with handling system limitations, ensuring payment accuracy, compliance with policies and a multitude of fee schedules, and ensuring utilized data is up to date.

System Limitations

Medical claim systems can have several limitations in properly identifying and addressing of potential medical drug claim issues:

Figure 3: NDC and pricing variability within specific therapeutic classes

Barriers to Appropriate Reimbursement Under the Medical Benefits

1. Claim Edits: The ability to properly create edits to identify distinct issues with the claims. Historically, most medical claim system edits have been broad based and focused on extreme outliers in pricing and/ or number of units. Due to the potential of significant variability across drugs, the management of these inconsistencies requires a source of edits that provides drug level identification of outliers and actionable points. In addition, many claim systems lack the functionality to develop the complex edits required to properly manage drugs.

2. Source Data: The lack of support to ensure that source data (i.e. pricing and mappings) are

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Payment Accuracy

Based on Client Claims data, the margin for error is greater than 10% when comparing allowed amounts to appropriate reimbursement. In the case of medically covered drugs, many systems have been, and still are, evaluating the claim based on HCPCS/CPT coding. While this method is effective when there is a 1:1 match between Code and Diagnosis (e.g., Remicade), it may be insufficient in cases when multiple drugs are as-sociated with a HCPCS Code or when the claim was submitted with a “Not Otherwise Classified” miscellaneous drug code. Multiple assignments or “unclassified code uses” are often reimbursed as a percentage of billed charges because pay-ors do not have a way to determine the clinical crosswalk. Frequently, these claims are returned partially paid or denied which drives the cycle of appeal and review between provider and payor.

Compliance with Health Plan Policies

Policy adherence requires people, process and

system support. With medically covered drugs, this is particularly true when the policy is fo-cused on a requirement for submission of NDCs on medical claims. NDC mandates have been in place for Medicaid covered lives for over a de-cade; but in recent years, this requirement has been expanded to account for additional lines of business. This shift creates a larger member population which, in turn, creates greater claim volume. The addition of the volume mixed with the requirement for electronic claim submissions puts pressure on both payors and providers if the people, processes and system infrastructure aren’t in place. The challenge is even more com-plex for providers who have multiple systems for managing patients, billing, and collections. Any inconsistency in data brings exposure to errors and can result in improperly coded claims and lack of policy adherence.

Pricing Methodologies

Medically covered drug pricing is variable with changes occurring frequently. The more variabil-ity in a system, the greater the chance for errors and inefficiencies. Regarding price methodolo-gies, most reimbursements are based on CMS’ Av-erage Sales Price (ASP) and/or Manufacturers’ Av-erage Wholesale Price (AWP). In addition, pricing based on HCPCS code versus NDC code units can vary significantly. Secondarily, disparate provider and facility contract rates create additive com-plexity in ensuring appropriate pricing. Incorrect

Based on Client Claims data, the

margin for error is greater than 10% when comparing allowed amounts to

appropriate reimbursement.

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updated on a frequent basis and are in alignment with currently marketed drugs. Properly updating information in a core medical claim system requires close oversight to ensure properly loading and quality checking the data to ensure that there are no adverse effects to core business operations.

3. Internal Cost: High internal cost associated with the development and implementation of drug management solutions, from both a system development and personnel perspective, can be a significant barrier that both delays implementations and adds significant costs that the organization may not be able to afford or justify.

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prices in conjunction with variable contract rates create additive errors in reimbursements which frequently vary significantly from current market rates. The application of an “in-process and re-al-time” edit of the calculated rate and/or pricing methodology can protect from under/overpay-ments.

New Therapies and Continual Updates

Each year there are many new drugs that are ap-proved by the FDA and CMS assigns new HCPCS codes (40 codes in January 2019) to a subset of these approvals, as well as hundreds of new drug indications approved. This is in addition to the ongoing updates in coding assignments,

pricing, generic entries and more. Considering that the average cost for a medically covered non-specialty drug is approximately $500 and specialty drugs are $5,900 (Client Claims data), errors associated with the processing of these claims have significant implications of the claim payment process. Data must be monitored and updated into processes and systems to ensure accurate and current data being utilized. This challenge is further compounded by frequent updates to the pricing methodology or coding assignments. Without rigorous governance over these innovative therapies and updates, the im-pact of these coding complexities can create sig-nificant expense implications in a short period.

Addressing Barriers to Medical Drug Claim Payment Issue

Optimal management of drug reimbursement requires an organization to implement an end-to-end solution of claim validation edits with actionable outcome that result in operational efficiency gains and cost reduction (Figure 3). Some organizations may elect to implement solutions in a step-wise fashion, starting with edits and then adding case & utilization review and/or provider facing tools.

Figure 4: Example of medical drug edit end to end solution

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Disparity is inevitable and there is a mutual

impact to operations and payment integrity.

These di�erences result in potential additive

costs to both parties as claims are worked

through the reconciliation process.

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“The implementation of medical drug edits

in conjunction with network designs and

contract administration results in signi�cant

operational improvements and fosters

payment accuracy

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Foundationally ensuring consistency and align-ment in the data utilized by both the payor and the provider is paramount to ensuring appropri-ate claim submission and payment. There are several reliable sources for the data needed by Payors and Providers to manage systems and the reimbursement process. These sources, which are a mix of commercial and public access, inher-ently introduce variability in breadth and depth when being compared and implemented. As an example, a payor chooses source “A”, but the pro-vider is using source “B”. Disparity is inevitable and there is a mutual impact to operations and payment integrity. These differences result in po-tential additive costs to both parties as claims are worked through the reconciliation process.

The need for data alignment is pervasive through-out the medical drug coverage process and can be thought of as being governed through a “two-gate” process. The first “gate” addresses the determination of medical necessity based on submission of prior authorizations and the second applies post administration of the drug, when claim data is processed through various forms of rules or edits in an adjudication process. To minimize barriers and ensure the consistent use of a normalized data sources, medical drug edits must align for the claim billing and utiliza-tion management processes, thereby ensuring an aligned process.

Implementation of Medical Drug Claims Validation Edits

To address medical drug claim payment barriers, a payor should implement an automated claim edit application to quickly identify and address issues. For payors, the implementation of med-ical drug edits in conjunction with network de-signs and contract administration results in sig-nificant operational improvements and fosters payment accuracy in the claims process. In addi-tion, the edits can be coupled with provider com-munications to address denials, partial payments or requests for supporting data. Finally, tools can be provided to the physician to assist them in addressing claim issues, thereby improving claim accuracy rates and reducing overall time and cost of claim processing. The provider would benefit from medical drug edits and supportive web tools, in combination with the Electronic Health Record (EHR) system, to obtain real-time guidance prior to drug administration and/or to claims being submitted. The Edits can be in-corporated into a pre-claim “scrub” process that flags fields needing correction or review before submission.

To optimally implement edits, the system must evaluate various aspects of the claim (Table 1).

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Table 1: Medical Drug Edits Required for Optimal Management

To Build or Not to Build

Approaching the implementation of medical drug claims validation edit system requires organization-al alignment in ascertaining whether the system should be built or if a third-party vendor should be leveraged. When deciding to build a system, various considerations must be addressed, which are inherently included in a third-party solution:

1. Control: By building a homegrown system an organization can maintain full control on system development. Although this is desired by many organizations, it comes with challenges. The primary challenge is assurance that the core data utilized in the edits is up to date and being applied appropriately. In addition, the acquisition and maintenance of such core data for edits requires significant expertise from a technical, payment and clinical perspective.

2. Efficiency: Many organizations believe that maintaining internal control results in greater efficiency in the implementation and customization of the system. We have found through various implementations that this belief is flawed and that deferring customization to a third party that specializes in medical drug edit systems results in faster implementation at a significant lower cost.

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Figure 5: Medical Dug Edit Application

From a process improvement perspective, third party solutions are inherently developed with robust reporting which provide insight into areas of opportunity and potential causes of medical drug billing issues. There are specifically three areas of potential insight:

Through the utilization of a mature third-party solution for medical drug edits a payor can em-ploy normalized, up-to-date coding and pricing data and logic in cooperation with the organiza-tion’s policy and claim data to drive timely, accu-rate and appropriate payments (Figure 3). In ad-dition, organizations can decide which edits best meet their needs and apply them in customized manner. With each medical drug edit being an enabler of change that can drive improvements for both Payors and Providers, savings and ef-ficiency can be spread throughout the claim

process. To ensure providers have the tools to properly submit correct claims, a third-party or-ganization should be selected that can provide an end to end solution which includes tools for providers. Finally, by utilizing a third-party solu-tion, an organization is inherently taking advan-tage of the experience of multiple payors and many provider organizations as the system is en-hanced to address potential gaps. This leads to an even greater accuracy in the medical drug edit platform.

3. Claim System Integration: Integration into the claim system is an ideal solution, but many claim systems are not readily compatible with medical drug edits and, therefore require significant enhancements. There is often little benefit in directly retrofitting legacy claim systems due to the high cost of such changes.

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The client implemented a standard configura-tion of the RJ Health Medical Drug Edit platform and achieved an 8.2 percent reduction in claims requiring manual review. The client elected to send medical drug claims through an application programming interface (API) at set times through out the day, seven days a week.

Nine months after implementation the client experienced a significant improvement in error

rates within medical drug claims (Figure 4). Over-all, the rates of invalid claims (claims which con-tain an error), was reduced by 2.1 percent. The rate of corrected claims (claims with an error that the platform was able to provide a correction) was reduced by 6.1 percent. The 8.2 percent re-duction in claims requiring manual review led to an equally significant improvement in valid claims over time.

Case Study: Midsized Health Plan

Figure 6: Results after 9 months of utilizing the RJ Health Medical Drug Edits Platform

1. Identification of areas for improvement in operations, contracting, and systems.

2. Identification and monitoring of drug classes, specific drugs, disease states or conditions, providers, and patients for potential medical drug claim issues and effectiveness of reconciliation actions.

3. Identification and monitoring of claims submitted in accordance with the payor’s policy and payments were challenged or adjusted.

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percent reduction in claim errors requiring man-ual review. Just as accounting data drives bud-geting and prioritization, medical benefit drug data needs equal attention to achieve accurate billing and reimbursement. The barrier to imple-mentation of a medical drug edit platform is sig-nificantly lower when utilizing a third party with a mature edits platform, compared with building a platform internally. In addition, maintenance and versatility of applications across various ar-eas is increased significantly through the usage of an external system. Incremental benefit can be achieved through the implementation of pro-vider support tools that work synergistically with edits.

As a result of these corrections, the client realized a significant reduction in operational costs asso-ciated due to a reduction in manual claim review efforts and to the automation of claim denials. In addition, the client-generated provider deni-al letters based on the edit results that included provider education notes. These provider educa-tion outreach will further improve the claim sub-mission process.

Conclusion

The medical benefit drug trend has become a prime target for cost controls across policy, fi-nance and operational disciplines. RJ Health’s edit platform and case study with a midsized health plan, clearly demonstrates the value in optimization of drug claim reimbursement using edits. In our case study, the client realized an 8.2

About the Authors

Wendy is responsible for the development and implementation of RJ Health’s Medical Drug Edits. She also manages the creation and/or productionalization of standard and custom datafiles.

Wendy Sullivan, MPH,Director of Data Informatics,RJ Health

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Todd Cooperman,PharmD MBA RPh,SVP, Clinical Insights and R&D, RJ Health

Todd Cooperman joined RJ Health in June 2016 as Vice President, Clinical Insights and Analytics. As Vice President, Todd has extensive input to the development and maintenance of RJ Health’s drug informa-tion databases. Additionally, Todd oversees the development of analytic methodology, implementa-tion, and reporting for our various clients.

Prior to joining RJ Health, Todd worked for CVS Health, overseeing the operationalization and strategic development of the medical benefit product offering and IT systems, which included claims and prior authorization platform solutions. Todd had responsibility for analytic, strategic, and business develop-ment of drug strategies and strategic reporting for specialty drugs. In addition, Todd oversaw the CVS Health Specialty residency program.

Todd has an extensive background in all aspects of managed care and specialty pharmacy including: utilization review, Pharmacy and Therapeutics Committee oversight, predictive and pharmacoeconom-ic modeling, rules engine development, formulary management, business operations, benefit design, drug Informational and claim databases, patient education, and clinical practice.

Todd earned a Bachelor’s in chemistry from Binghamton University, Doctorate in Pharmacy from North-eastern University, and a Masters of Business Administration from the University of Hartford. Todd com-pleted a pharmacy practice residency at Saint Francis Hospital and University of Connecticut. He is a Registered Pharmacist in the State of Connecticut and is a member of the Academy of Managed Care Pharmacy.

About the Authors (cont.)

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About

RJ Health is a drug data, application & analytics provider to the pharmacy reimbursement market, bringing scalability to specialty drug innovation. We focus on specialty drug innovation (new approvals and additional indications), as well as normalizing reimbursement for drug classifications that have market forces at-play (generics / biosimilars, rebates, and CMS policy).

The company provides industry standard pricing, coding, dosing, weight, age, and diagnosis data & analyses to pharmacy, market access, claims, billing, finance, and network management clientele.

RJ Health ensures transparency between manufacturer, payor, provider, pharmacies and their respective solution vendors (PBMs, Payment Integrity, Revenue Cycle, EHR, etc...) – all licensees of RJ Health data.

To learn more about RJ Health, visit:rjhealth.com

Or email:info@rjhealth.com