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Improving Provider Directory Accuracy: Can Machine-Readable Directories Help?
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Improving Provider Directory Accuracy: Can Machine-Readable Directories Help?

Michael Adelberg, MA, MPP; Austin Frakt, PhD; Daniel Polsky, PhD; and Michelle Kitchman Strollo, DrPH, MHS
The authors examined the accuracy of provider directories and found widespread errors. Machine-readable directories are not more accurate than conventional directories, despite their advantages. A survey of promising initiatives to improve directory accuracy was also completed.
Data sources. We downloaded and aggregated 4 separate sources of provider data—CMS’ National Plan and Provider Enumeration System (NPPES) file, conventional MA directories found on health plan websites and other online sources, exchange MR directory files, and Google Places—into a single analysis database (Table 1).

MA file compilation required 5 manual processes to download into the analysis database. Data quality issues such as misspellings and small inconsistencies in addresses were solved manually. The exchange data were in a uniform and standard format, but we still experienced some data challenges, which were solved via code and automation with little manual intervention.

We compiled the data into an analysis database, removing inconsistencies (eg, spacing and capitalization) and assigning each reported element to a category (ie, address or phone number) for validation and analysis across data sources. The analysis database contained all known information.

Summary of analysis methods. Throughout the data aggregation process, we tracked time and effort in order to assess the differences among the data sources by recording the time it took staff to complete each step to move the data into the analysis database (see eAppendix B).

After all of the data were compiled into a single database, data were analyzed via queries and text matching. For the text matching, human coders examined text similarity and assigned them into categories of like and unlike data. Because providers can practice in multiple locations, our analysis focused on whether 2 data sources reported at least 1 similar value.

Finally, we validated the accuracy of the electronically reported elements based on phone interviews with provider offices. We drew a random sample of more than 50 unique providers per specialty based on the primary specialty reported in NPPES. We contacted the provider’s practice address to validate each reported element in the analysis database.

Qualitative Analysis

We conducted phone interviews with representatives of CMS, state regulators, health plans and trade associations, and other experts to determine whether these stakeholders believe that MR directories facilitate more accessible and reliable information than conventional directories. Interviews were conducted with 4 CMS officials from 2 different program components, 5 senior state regulators from 4 states in different regions of the United States, 6 staff from 3 health plans that offer plans in the health insurance exchanges and MA, 3 health plan trade association staff from 2 associations, and 3 vendors of provider data accuracy solutions. These numbers do not include 2 individuals who declined to be interviewed.

Participants were provided with discussion topics in advance of the interview. Interviewees were offered confidentiality in exchange for their candor but no other compensation for their time.


We found widespread inaccuracy in provider information across directory types. We also found that provider directories from insurers with MA and exchange plans did not report the same phone number 50% of the time and did not list the same address 31% of the time. As displayed in Figure 1, provider directory addresses have a 30% inconsistency rate when a common provider is in the same company’s health plan networks across markets.

We also analyzed provider information accuracy through phone validation by calling provider offices. During these calls, we successfully validated 80% (2850 of 3562 calls) of information attributes attempted. As summarized in Figure 2, although all data sources contained inaccuracies and differences were sometimes slight, 2 findings can be implied: (1) Google is more accurate than provider directories or the federal NPPES file for name, address, and phone number (statistically significant [P <.01]); and (2) despite the advantages of MR directories, exchange provider directories are less accurate than conventional MA directories.

The higher inaccuracy rate of exchange provider directories was unexpected given the advantages of MR technology to improve accuracy. This is not necessarily an indictment of MR. The high inaccuracy rate of exchange provider directories is likely because MA plan sponsors (facing oversight from CMS) are investing resources in raising the accuracy of MA directories, whereas there is no equivalent pressure to improve directory accuracy in the exchanges.

Interviewees—whether they were from health plans, government agencies, or provider data vendors—all understood that provider directories are frequently inaccurate, but they differed in their perceptions of the problem and potential solutions. Interviewees who were familiar with MR directories understood their advantages over conventional directories, but only some acknowledged their potential value in improving accuracy. Contrasting responses are offered in Table 2.

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