Encoding laboratory testing data: case studies of the national implementation of HHS requirements and related standards in five laboratories |
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Authors: | Raja A Cholan Gregory Pappas Greg Rehwoldt Andrew K Sills Elizabeth D Korte I Khalil Appleton Natalie M Scott Wendy S Rubinstein Sara A Brenner Riki Merrick Wilbur C Hadden Keith E Campbell Michael S Waters |
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Affiliation: | Deloitte Consulting LLP, Washington, District of Columbia, USA;Office of the National Coordinator for Health Information Technology, Washington, District of Columbia, USA;U.S. Food and Drug Administration, Silver Spring, Maryland, USA;U.S. Department of Health and Human Services, Silver Spring, Maryland, USA;Association for Public Health Laboratories, Silver Spring, Maryland, USA;University of Maryland, College Park, Maryland, USA;U.S. Department of Veterans Affairs, Bend, Oregon, USA |
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Abstract: | ObjectiveAssess the effectiveness of providing Logical Observation Identifiers Names and Codes (LOINC®)-to-In Vitro Diagnostic (LIVD) coding specification, required by the United States Department of Health and Human Services for SARS-CoV-2 reporting, in medical center laboratories and utilize findings to inform future United States Food and Drug Administration policy on the use of real-world evidence in regulatory decisions.Materials and MethodsWe compared gaps and similarities between diagnostic test manufacturers’ recommended LOINC® codes and the LOINC® codes used in medical center laboratories for the same tests.ResultsFive medical centers and three test manufacturers extracted data from laboratory information systems (LIS) for prioritized tests of interest. The data submission ranged from 74 to 532 LOINC® codes per site. Three test manufacturers submitted 15 LIVD catalogs representing 26 distinct devices, 6956 tests, and 686 LOINC® codes. We identified mismatches in how medical centers use LOINC® to encode laboratory tests compared to how test manufacturers encode the same laboratory tests. Of 331 tests available in the LIVD files, 136 (41%) were represented by a mismatched LOINC® code by the medical centers (chi-square 45.0, 4 df, P < .0001).DiscussionThe five medical centers and three test manufacturers vary in how they organize, categorize, and store LIS catalog information. This variation impacts data quality and interoperability.ConclusionThe results of the study indicate that providing the LIVD mappings was not sufficient to support laboratory data interoperability. National implementation of LIVD and further efforts to promote laboratory interoperability will require a more comprehensive effort and continuing evaluation and quality control. |
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Keywords: | health information interoperability clinical laboratory information systems public reporting of healthcare data Logical Observation Identifiers Names and Codes |
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