BETHESDA, Md., July 18, 2024 /PRNewswire/ -- Incorrect data in health plan physician directories is a pervasive problem, according to new research conducted by researchers at University of Colorado and HiLabs. The study, published in BMC Health Services Research, leverages HiLabs AI algorithms to compare data for >40% of US physicians across five large health plan directories.

HiLabs was founded at Yale with the mission of refining dirty healthcare data. A team of healthcare professionals worked alongside data scientists and AI experts to perfect a platform capable of accurately discovering data patterns and errors in provider, claims, clinical, and value-based care data. HiLabs' AI platform, MCheck, has analyzed over 34 billion health data records covering 24% of the US healthcare population and serves 4 out of the 10 largest health plans and multiple regional plans. (PRNewsfoto/HiLabs)

Researchers found little variation across insurers in quality of information on physician addresses (72%-83% inaccurate), phone numbers (73%-84% inaccurate), or specialty (32-36% inaccurate). The level of inaccuracy was also noticeably high when comparing against the Medicare Provider Enrollment, Chain, and Ownership System (PECOS) database, which is widely regarded as the gold standard for provider data. States with more laws targeting this issue did not have better data quality.

Incorrect provider directory data can lead to delays in care, surprise billing, and challenges for consumers selecting health plans. The 2021 No Surprises Act contains requirements for insurers to keep their directories up to date. The REAL Health Providers Act, currently pending in the US Senate, proposes additional regulations for insurers to improve directory information, particularly for mental health providers. Notably, this new study found that physicians specializing in psychiatry or neurology had correct addresses only 28% of the time and correct phone numbers only 16% of the time, and no physician specialty had correct addresses or phone numbers >50% of the time.

"These results demonstrate that no insurer has solved the provider data problem," said Dr. Neel Butala, Assistant Professor at University of Colorado and lead author of the study. "They also suggest that legislation targeting insurers to improve directory accuracy has not been successful and that creation of a singular national provider directory, as recently proposed by CMS, may prove challenging."

"We are proud to collaborate with University of Colorado researchers to use our AI for this important study," said Amit Garg, CEO of HiLabs. "At HiLabs, we have seen tremendous interest from health plans in using AI algorithms to uncover provider directory inaccuracies in recent years and have seen substantial improvements in directory accuracy as a result."

For further information and to access the full study, please visit https://doi.org/10.1186/s12913-024-11269-5

About HiLabs

HiLabs is a leading provider of AI-powered solutions that clean dirty healthcare data. HiLabs is committed to transforming the healthcare industry through innovation, collaboration, and a relentless focus on improving patient outcomes. For more information, please visit hilabs.com or contact info@hilabs.com.

Cision View original content to download multimedia:https://www.prnewswire.com/news-releases/hilabs-ai-discovers-incorrect-physician-data-as-an-industry-wide-pervasive-problem-302200749.html

SOURCE HiLabs

Copyright 2024 PR Newswire