Know where provider information stands

Healthcare and payer organizations typically ignore or at best, take a reactive approach to assessing their provider data quality and its impacts. It is not until problems with provider receivables, financial accuracy errors or service issues begin to impact customer retention that action occurs. When provider data issues get to that point, organizations tend to throw resources at the problem, calling providers, fixing claims retroactively and attempting to perform damage control.

In many cases, the state of provider data is much worse than these averages. The impact to member/provider/account satisfaction, financial accuracy, additional manual work for claims, calls and returned mail as well as risks to late payment interest and performance guarantees, coupled with client retention and company perception issues, should give organizations ample reasons to make the accuracy of their provider data a corporate priority. For those organizations that do consider provider file accuracy and currency mission-critical, the question is how to best assess and monitor the overall accuracy of the data and its downstream impacts.

There are two main methods to determine where your organization stands in terms of provider information quality.

The second option is to have a third party review and analyze a random, statistically significant sample of the entire provider file. The pros to this method are internal: resource strain is minimized, results are unbiased and independent, and the tools and technology utilized will take into account the best matching and analytic methods available. The cons to this approach include the initial financial investment required to perform the audit, and staff time needed to review and internalize the results.

Typically, this method requires an investment of internal staff's time. There likely will be a consulting fee for the audit as well. When an audit is performed by a vendor, most organizations will ask many questions and request specific examples of the results before becoming comfortable with them. The primary advantage of this method is that the results are compiled by an unbiased source with focused expertise in the area of provider information.

Regardless of whether an internal or external review of provider file accuracy is selected, there are several critical decisions that must occur, as outlined in the bullets below.

Understand the business requirements for each data attribute. Specifically, what attributes are mission-critical? And what accuracy rate is acceptable for each attribute across various provider types? While 100% accuracy of all attributes for all providers on file would be ideal, achieving that goal is costly and impractical.

This is especially true given that there always will be claims and changes from new and out-of-network providers. Even for established, in-network providers, achieving perfection is effectively impossible, given the frequency at which demographic information changes (between two and two and one-half percent of which changes each month). In addition, achieving perfection is a challenge because you do not know which providers have changed. Further, the frequency of measuring accuracy and monitoring it over time should be established, thereby creating a baseline to measure improvement. A monthly assessment is the most effective.

When establishing business requirements, one typically considers the cost of acquiring the information and the cost of fixing problems caused by errors, both in the functional area where the error occurs and in downstream areas, such as accounting. "Soft" considerations also are relevant for issues such as the implications of bad or missing data for member, provider and customer satisfaction, and potential penalties and compliance issues.

Determining whether the information in the provider file is correct via an internal audit requires identifying the current authority source for each data attribute. In addition, you must check the information in the provider file against the authority source. Just because a source is an authority for one attribute doesn't mean that it is the best source for other attributes.