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Methodology on Creating the U.S. Linked Retail Health Clinic (LiRHC) Database

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March 2023

Written by: Alice Zawacki, Joey Marshall, Donald Cherry, Xianghua Yin, Brian W. Ward

Working Paper Number:

CES-23-10

Abstract

Retail health clinics (RHCs) are a relatively new type of health care setting and understanding the role they play as a source of ambulatory care in the United States is important. To better understand these settings, a joint project by the Census Bureau and National Center for Health Statistics used data science techniques to link together data on RHCs from Convenient Care Association, County Business Patterns Business Register, and National Plan and Provider Enumeration System to create the Linked RHC (LiRHC, pronounced 'lyric') database of locations throughout the United States during the years 2018 to 2020. The matching methodology used to perform this linkage is described, as well as the benchmarking, match statistics, and manual review and quality checks used to assess the resulting matched data. The large majority (81%) of matches received quality scores at or above 75/100, and most matches were linked in the first two (of eight) matching passes, indicating high confidence in the final linked dataset. The LiRHC database contained 2,000 RHCs and found that 97% of these clinics were in metropolitan statistical areas and 950 were in the South region of the United States. Through this collaborative effort, the Census Bureau and National Center for Health Statistics strive to understand how RHCs can potentially impact population health as well as the access and provision of health care services across the nation.

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Internal Revenue Service, Bureau of Labor Statistics, Social Security Administration, Service Annual Survey, Center for Economic Studies, County Business Patterns, Longitudinal Business Database, Employer Identification Numbers, Economic Census, North American Industry Classification System, National Center for Health Statistics, Disclosure Review Board, Centers for Disease Control and Prevention, Data Management System

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