Mr. Smith is a 68-year-old retired teacher on a tight, fixed income. After visiting his Primary Care Physician (PCP) for a regular check-up, his PCP requested that he schedule an appointment with an Ear, Nose, Throat (ENT) specialist for a consultation. Mr. Smith immediately calls the number on the back of his insurance card for assistance from member services. After receiving the name and office phone number for an ENT in his area, Mr. Smith calls and makes his appointment. 

The following day, Mr. Smith takes the 35-mile taxi ride to his appointment with the ENT, where his consultation is completed and is told that his PCP will be briefed. Thirty days later, Mr. Smith receives a bill from the ENT saying that his payment in the amount of $370 must be paid within 30 days. When Mr. Smith calls the ENT’s office to inquire, he learns that the ENT provider doesn’t accept his insurance.* 

Unfortunately, scenarios like this aren’t uncommon. According to a Centers for Medicare and Medicaid Services report released in 2018, despite a focus on directory accuracy, more than 45% of all provider directory locations had at least one inaccuracy.1

These inaccuracies are responsible for countless patient phone calls to obtain appointments, visiting a doctor mistakenly believed to be in-network, or even worse, enrolling in a plan with the belief that their current provider participates in the network only to discover they don’t. In addition, these situations directly impact patient satisfaction and breed distrust.

Sources of Inaccurate Health Plan Data

Health plans must strive to maintain and improve provider data quality to avoid unhappy members or even losing plan members. Moreover, poorly maintained data also causes delays, increased costs, and frustration for providers, payers, and health plans.

Data errors and deficiencies are noted in many areas including:

  • Providers listed at the wrong location
  • Providers who should not be listed at any location
  • Wrong phone numbers
  • Wrong addresses
  • Wrong suites
  • Providers listed as accepting new patients when they actually are not
  • Providers listed as not accepting new patients when they actually are

Fast-paced business environments combined with human error are a perfect recipe for inaccurate and incomplete provider data. Because of these things, health insurance companies must be vigilant about updating all provider data points frequently and consistently for best practice.

Provider Data Quality Is the Core of Every System

Health plans currently get pieces of provider data from a number of different sources including claims, provider group rosters, and contracting and credentialing processes. Each source is valuable, but only if you understand context. No one source contains the whole truth.

It’s vital to find to understand where sources are corroborating data elements, where there is conflict between sources, and which sources are most reliable for which data elements. 

This is why a multifaceted approach to provider data management, including referential data, claims analytics, machine learning, and cross-industry touchpoints is critical. I believe that organizations who optimize data management and view data as an asset will be more insightful. Putting a focus on a dependable data feed will make them better, faster and stronger.

The truth is, data is the core of every system within health plans. When you cannot rely on your provider data being accurate, you’re leaving huge gaps in your organization’s ability to provide quality care as well as reducing productivity. Data is central to all processes, therefore it needs to be kept top of mind at all times to ensure a strong foundation with which to work.

Validate Data for a Smoother Workflow

Health plans must put quality checks in place to avoid the congested workflows that result from inaccurate data points for their providers. This is especially pertinent since basic provider information changes at a rate of 2.4% per month.2

Keep on top of data changes by:

  • Validating data immediately before it becomes an issue
  • Conducting monthly or weekly data quality checks
  • Working with doctors to ensure data points are accurate

Adopting best practices when it comes to managing provider data quality drives the entire system along the correct path – boosting efficiency, patient experience, and compliance.

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References:

1 Online Provider Directory Review Report, Centers for Medicare and Medicaid Services, https:///www.cms.gov/Medicare/Health-Plans/ManagedCareMarketing/Downloads?Provider_Directory_Review_Industry_Report_Round_3_11-28-2018.pdf

2“A Business Case for Fixing Provider Data Issues.” LexisNexis Risk Solutions. http://techhubly.com/lexisnexis-resources/files/A%20Business%20Case%20for%20Fixing%20Provider%20Data%20Issues_WPNXR5062-0.pdf

* The story in the opening paragraph is an example for illustrative purposes only and not based on an actual person’s experience. Any correlation with an actual individual’s information or experience is incidental.