Provider Data Accuracy – Why it Matters

Julie SkeenJune 10, 2020

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What is Provider Data and Why Must it be Accurate?

Provider data is essential when connecting healthcare professionals, exchanging information and managing payments. When providers stop accepting new patients, change their contract with a health plan or start working for a different entity, these data changes create issues for patients, health plans, systems and other healthcare entities. These difficulties arise because data originates from a variety of sources and maintained by third parties on behalf of the actual source of truth, the providers themselves. Adding to these complexities are different technologies and systems, as well as no singular structure to pass the data. The result is data that needs to be provided in multiple ways to a variety of constituents, muddying the waters. Despite the constantly changing data, and the difficulties keeping it up-to-date, provider data accuracy is critical to us all.

Learning from Others

With no single vendor able to tackle provider data accuracy, the healthcare industry has tried many ways to get around these data issues which have resulted in a patchwork of solutions. Various organizations and vendors have tried to establish a single source of truth, but each result was the creation of more versions of the truth. Centers for Medicare & Medicaid Services (CMS) indicated that they may try to standardize provider data, but no one knows if, when or how this will happen. We do know that anything they do will, at least initially, be limited to only Medicare Advantage plans.

Achieving provider data accuracy is not something that happens overnight. That is why health plans and other healthcare organization need to learn from other highly regulated industries, like financial services, how to create long-term strategies to ensure the integrity of their critical business data.

Health plan members may be the first to see the benefit of any significant improvements in provider data integrity due to reduced costs in fines, but the benefits go beyond this segment. Achieving success means government regulatory agencies will benefit from spending less time on this issue and relationships between health plans and providers will improve since data will be in sync with increased transparency in value-based payment models.

Actions To Develop Provider Data Accuracy

Taking a long-term approach to provider data integrity requires a structured methodology to ensure data accountability. This approach should, at a minimum, include the following elements:

  • Define key elements that are part of the provider information.
  • Assign ownership of the provider data elements and processes.
  • Document the process and data lineage to understand where data resides, where it moves and to what other data assets it is related.
  • Provide a mechanism for users to report issues or ask questions to subject matter experts.
  • Apply quality checks on provider data being received from external sources.
  • Perform frequent reconciliations between internal systems to identify any areas where the data is out of synch and include prioritization rules to determine the most current data.
  • Apply validation checks to ensure data integrity as it moves between systems and processes.
  • Implement routing capabilities to categorize any exceptions, allow them to be quickly resolved and ensure there is a mechanism to group any exceptions for the same provider together.
  • Deploy automation to ensure issues do not re-occur once resolved.
  • Provide visibility to business stakeholders to ensure a current view of any issues via an interactive dashboard.

Once these introductory steps are complete, implement more sophisticated features such as:

  • Scorecard each external entity sending provider data. Consider financial incentives or penalties based on level of data quality and accuracy.
  • Integrate with external sources to validate information such as addresses and NPI.
  • Move data using real-time Kafka streams, verifying the quality as it moves.
  • Apply anomaly checking using Artificial Intelligence (AI) as soon as any new data is received.

Accurate provider data is not a want, it’s a need. Many organizations have looked for quick fixes to resolve the issues. Unfortunately, many of the point solutions available today only address a single issue or for a short period of time, similar to a fad diet. To be healthier, eating habits and exercise have to be prioritized. It cannot be achieved quickly, instead the change has to occur at the core. In a similar way, following the basic approaches above will create long-lasting results for the health of your provider data. The up-front effort is worth it, and all parties will benefit.

For more information about provider data accuracy and how Infogix might support a data quality program, please check out this data sheet, above and below.

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