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Perspectives

Solving the Provider Data Management Challenge

2020-02-05


It’s time for an end-to-end approach to create and sustain accurate provider information.

Warnings from the Centers for Medicare & Medicaid (CMS) citing inaccurate provider directories, high claim-reprocessing volumes and substantial encounter-data rejection rates all are telling symptoms of expensive and expansive problems with provider data.

We estimate that errors in provider data cost payers over $3 billion yearly. However, that estimate is likely conservative, because it excludes eventual CMS fines or state sanctions, such as losing auto-enrollment status. That figure also doesn’t accurately capture the downstream snags caused by poor provider information. These include incorrect claims payments; high volumes of grievances and appeals; lower volumes of referrals due to inaccurate or missing specialty codes in directories; negative evaluations from members; and providers leaving networks. Moreover, CAQH estimates physician practices spend a total of $2.76 billion yearly on provider directory maintenance. This would indicate that provider data issues cost the industry about $6 billion annually.

Many payers try to address symptoms of problematic provider data by cleaning up a database here and there. Those efforts are ineffective because they are not broad enough and do not identify the root causes of bad data. All too soon, provider data is once again inaccurate, with its negative effects traceable throughout preauthorization, claims processing, member and provider satisfaction, compliance and so on.

Optimizing provider data and addressing the value chain problems it causes requires a holistic approach we call provider information management (PIM). PIM is a comprehensive and process-oriented view that broadly defines “provider data” as any provider-related data that is part of the payer value-chain. PIM reveals how provider data has an impact on or is affected by virtually every payer process (see Figure 1). Adopting the scope of PIM helps payers create and sustain clean provider data that they can use in more proactive, digitally mature ways. That helps payers streamline processes and workflows and greatly reduce the systemic costs of out-of-date, inaccurate provider data.

PIM: Establishing a single source of truth

PIM redefines the scope of reference for provider data. It shows why managing provider data goes beyond the IT department and any single database. PIM captures how provider data is created, gathered, transformed, validated and consumed, and published by each workflow, application or system within the payer value chain. This expansive view of provider data reveals how inaccurate provider data, such as a missing provider name, not only causes claims rejections and grievance issues downstream but may ultimately result in upstream issues such as lower Stars ratings, impacts to sales and marketing efforts, and overall enrollment levels.

PIM also is adaptable to industry shifts, such as the category of “provider” enlarging to include nonmedical service providers such as Lyft and Uber Health, community organizations and more.

Figure 1

With a complete understanding of which processes affect and rely on provider data, payers can create comprehensive PIM strategies. While the solutions may vary depending on the size of payer operations, differences among lines of business and specific business goals, to build an effective PIM payers will need to address these four components:

  • A single source of truth.
    Establishing central truth is the heart of PIM. This source of truth must serve as a protected golden record and be independent of any single system, whether a core claims system or provider application. Payer and provider applications and systems must then tap into this record. Built on a standardized data model, the system must align with industry-accepted data definitions.

    Creating this single source of truth will likely require redesigning business processes to eliminate practices and gaps that contribute to provider data inaccuracies. The root causes of inaccurate data are many, and often spread across multiple systems and related workflows. Providers operate many legacy commercial systems from a variety of vendors, and these systems lack common data definitions and formats. These stand-alone point solutions each have their own proprietary provider master files and workflows. This lack of standardization and systems interoperability makes it extremely difficult to sustain data hygiene, even after a concerted clean-up effort. 

    Approaching provider data from a PIM perspective identifies these relationships among data producers and consumers so that they can be standardized and governed.

  • Strong data governance.
    Creating a business function to validate creation of new records and changes to existing records in the source of truth will help ensure and sustain its integrity. Most payers have poor governance controls, yet even the most obscure-seeming data can have an immense impact on operations and costs. An erroneous provider change-of-address that causes a primary care physician assignment issue can create a multitude of issues for members and processes, and can easily proliferate to other systems.

    Data governance processes also monitor and uphold the standardized data model. This model will adapt to changing industry-accepted data definitions and regulations, and maintain an audit trail.

  • Bidirectional integration.
    The PIM source of truth must take in data from sources such as provider rosters and network management applications and accept change requests from systems such as member and provider portals. It must validate provider data additions and edits, then propagate those to other systems. These bidirectional data flows will require an approach to integration that is extensible and configurable, supporting multiple integration technologies.

  • End-to-end platform.
    A common technology platform that automates daily transactions that generate or consume provider data across provider business functions will help enforce governance policies and streamline data management. When built on a modern, scalable and secure technology infrastructure, the platform must be flexible enough to encompass modular applications and third-party data and apps while still enabling payers to enforce provider data governance.

    The platform must incorporate several technical architecture layers that orchestrate the use, management, integrity and security of provider data. Creating those layers requires payers to redesign and rationalize current data architectures and flows. Modular applications for traditional provider operations and provider network management can sit on top of the platform. Similarly, third-party applications and/or external provider data sources may feed or draw on the platform via application programming interfaces.

Even with these four components in place, it’s important to approach PIM as a journey, not a one-and-done initiative. PIM represents a new view of how to manage and sustain accurate provider data across a healthcare ecosystem. As such, PIM is adaptable to different healthcare organizations and their business models and objectives.

This article was authored by Greg Anderson, vice president of Cognizant Healthcare Consulting, and Kekai Beyer, director of Cognizant Healthcare Consulting.

To learn more, visit the Healthcare section of our website, or contact us.

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Solving the Provider Data Management Challenge