May 12, 2022

8 Focus Areas for Accuracy of Provider Data Management that Impact Payment Accuracy

Errors in provider data account for the top reasons’ claims are pended or processed incorrectly, leading to frequent reprocessing and even potential fines, often attracting unwanted attention from providers, members, and regulators.


By Erica Nelson


Maria Turner

Managing a network of healthcare providers presents many challenges. Given the wide variety of data collected, maintained, and distributed by network management teams, maintaining a network’s provider data can become a nightmare when not managed effectively. Even small gaps and inefficiencies in data management can cause major issues across the health plan, especially when not quickly addressed.

Errors in provider data account for the top reasons’ claims are pended or processed incorrectly, leading to frequent reprocessing and even potential fines, often attracting unwanted attention from providers, members, and regulators. This can be frustrating, given the widely accepted belief that quality provider data is difficult to collect, validate, and update within reasonable turnaround times. Many plans are forced to rely directly on providers to submit rosters of data, which are often not the group’s top priority to maintain or distribute. Even when relying on delegated groups and IPAs, it can be challenging to receive accurate data at the required frequency from providers. 

Below are identified areas of PDM pain points and the ongoing and evolving challenges they face:


As with all areas of payer operations, the primary objective is to ensure adequate care is being provided to members. Members need access to an accurate list of in-network specialists. They must feel confident that they are assigned to an appropriate primary care physician. They need to access and understand provider directories to locate urgent care facilities and clinics for rapid-response treatment. Any gap in provider data that leads to a member having even a slightly difficult experience locating or receiving healthcare must be treated as a critical risk to payers, even if it is as “simple” as incorrect provider demographic information such as suite or telephone number. If these gaps are not remediated, the impact on members can quickly snowball to become catastrophic.


Keeping providers happy is a critical goal of health plans. When providers join a payer’s network, they expect their information and data to be managed with the utmost care. Every physician, facility, pharmacy, and lab must be accounted for in a payer’s system. Any inaccuracy may lead to issues including incorrect claims payment, authorization issues, PCP assignment issues, publishing incorrect data in a provider directory, the list goes on. If a provider feels their data is not being collected, stored, and updated in an accurate and timely fashion, that provider becomes a risk. In their view, these errors are not just inconsiderate to them as providers but are also dangerous to members. Whether choosing to act on their own behalf or in defense of their patients, providers will not hesitate to raise concerns if they feel a health plan is not maintaining their data at a high standard. In these instances, they will not hesitate to amend or terminate their contracts, alert regulators, or take legal action.


Maintaining a good relationship with regulators is crucial to any payer looking to maintain or expand their current book of business. Generally, this relationship is managed by specific teams that are responsible for producing reports, sharing information, and providing updates to specific regulators. However, this department is not usually responsible for the maintenance of accurate data, as they rely on a PDM team. Due to the demanding nature of many regulators, other teams typically don’t have the time or resources to validate the accuracy of the data they use to respond to regulators’ demands. They run the risk of being caught off guard when regulators bring up issues that have been escalated to them from members and providers. It may not be immediately obvious from where these issues stem and performing root cause analysis is often time-consuming and expensive. In order to keep regulators happy, it is critical for all teams to have a high degree of confidence in the provider data that they use.


Everyone fears a CMS audit. Similar to state and local regulators, CMS and the federal government have a say in how provider data should be maintained. In fact, it is common for federal, state, and local requirements to be in conflict with each other, which creates challenges for the PDM team that is trying to manage a large network. In any case, PDM teams must have documented policies and procedures that comply with all levels of government oversight, while simultaneously meeting contractual obligations, provider requests, and internal corporate goals. Once these are established, payers need to face the challenging task to develop processes, metrics and quality checks that accurately measure the PDM team’s performance on meeting these requirements. 


Finding out that your network has gaps can be scary. Any issues in network can escalate from any of the previously mentioned groups, and any suspected issues in your underlying data must be promptly remediated. However, before those issues can be resolved, fingers will be pointed, and blame assigned. More often than not, the PDM team is an easy target because they manage the overall provider data, and as a result they are accountable for any and all gaps in accuracy, regardless of providers and other departments that share in the responsibility to exercise checks and balances leading up to the current issue at hand.


We read about new technology all the time. Apple, Google, 5G, Tesla, block chain, Bitcoin. It’s a lot to keep track of. Unsurprisingly, it can be difficult to tell where a healthcare payer fits into this new world of technology. Provider data management is not often the target of new and exciting innovation, with entrepreneurs preferring to focus on shiny, marketable areas that will be more visible to patients, providers, and regulators. It can be difficult to find support, funding, or even interest in upgrading the technology used for PDM, despite its critical role in the success of the health plan’s operations. 


Even if things are going well (which in PDM is often defined as “no major catastrophes yet today”), mismanaged data inhibits payers from realizing a number of opportunities. Truly accurate and complete provider data can tell a lot of stories to other departments. Where are our contracting opportunities? How can we foster better relationships between patients and providers? Are we utilizing our entire network to maximize its impact on our members? Even if a health plan has decent data, it’s critical to understand how to extract, cleanse, and interpret provider data that answers these questions. Sadly, these types of initiatives are often forgone to make time for dealing with day-to-day maintenance and issue remediation. When this happens, opportunities (and money) are left on the table.


Due to everything discussed so far, it is easy for payers to fall into a similar pattern when dealing with provider data. It is easy for the department to become reactive, focused on daily issues resolution and the prioritization of escalated items in order to narrowly avoid ruining a relationship with a member or provider. This leads to a high demand for skilled, manual data entry resources who can react quickly to the changing demands of the network. Not only can this lead to an inefficient use of time and resources, but it also puts payers at risk of becoming reliant on a group of employees performing reactive, manual tasks to avoid disaster. It’s an odd feeling to simultaneously worry about having too many resources devoted to manual data entry, but also worry about what would happen if even a few of the experts leave the company. 

These focus areas often require difficult conversations with providers, members, and regulators. These challenges range from quick fixes to complex overhauls of provider data management, including but not limited to: 

  • Roster and PDM accuracy audits 
  • Claims data mining and analytics 
  • Customer Relationship Management (CRM) optimization and turnaround time reduction 
  • Add/Term/Change process optimization and documentation 
  • Advanced Master Data Management (MDM) solutions to ensure consistency and accuracy across multiple systems 
  • Contract/Amendment implementation tracking, quality checks, and key performance indicators (KPIs) 
  • Incorporating third-party sources into the data validation process, including CAQH, NPPES, state files, and Google Maps API 
  • Reports, dashboards, and other tools that track discrepancies and changes to provider data over time 
  • In depth analytics on a number of challenging data elements, including phone numbers, address, ADA accessibility, BH expertise, taxonomies, provider specialties, new patient acceptance, etc. 

Provider Data Management is a multi-faceted focus area requiring intensive, cooperative tech stacks and intentional data design frameworks. With strong dependencies demanding intelligent digital and data solutions, the key to simplifying the complexity is by ensuring that the digital and technology framework supports the organization’s specific, targeted needs and is sustainable for profitable business growth.



By Erica Nelson


Maria Turner

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