Implications of Race Adjustment in Lung-Function Equations.

BACKGROUND: Adjustment for race is discouraged in lung-function testing, but the implications of adopting race-neutral equations have not been comprehensively quantified. METHODS: We obtained longitudinal data from 369,077 participants in the National Health and Nutrition Examination Survey, U.K. Biobank, the Multi-Ethnic Study of Atherosclerosis, and the Organ Procurement and Transplantation Network. Using these data, we compared the race-based 2012 Global Lung Function Initiative (GLI-2012) equations with race-neutral equations introduced in 2022 (GLI-Global). Evaluated outcomes included national projections of clinical, occupational, and financial reclassifications; individual lung-allocation scores for transplantation priority; and concordance statistics (C statistics) for clinical prediction tasks. RESULTS: Among the 249 million persons in the United States between 6 and 79 years of age who are able to produce high-quality spirometric results, the use of GLI-Global equations may reclassify ventilatory impairment for 12.5 million persons, medical impairment ratings for 8.16 million, occupational eligibility for 2.28 million, grading of chronic obstructive pulmonary disease for 2.05 million, and military disability compensation for 413,000. These potential changes differed according to race; for example, classifications of nonobstructive ventilatory impairment may change dramatically, increasing 141% (95% confidence interval [CI], 113 to 169) among Black persons and decreasing 69% (95% CI, 63 to 74) among White persons. Annual disability payments may increase by more than $1 billion among Black veterans and decrease by $0.5 billion among White veterans. GLI-2012 and GLI-Global equations had similar discriminative accuracy with regard to respiratory symptoms, health care utilization, new-onset disease, death from any cause, death related to respiratory disease, and death among persons on a transplant waiting list, with differences in C statistics ranging from -0.008 to 0.011. CONCLUSIONS: The use of race-based and race-neutral equations generated similarly accurate predictions of respiratory outcomes but assigned different disease classifications, occupational eligibility, and disability compensation for millions of persons, with effects diverging according to race. (Funded by the National Heart Lung and Blood Institute and the National Institute of Environmental Health Sciences.).

Using SNOMED CT as a reference terminology to cross map two highly pre-coordinated classification systems.

We hypothesized that SNOMED CT, a granular formal reference terminology, could be used to assist in the creation of a valid crosswalk between two administrative classifications: the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and the U.S. Veterans Benefits Administration (VBA) disability code set. To establish a baseline, we created an ICD-9-CM terminology server and directly mapped textual descriptions of the VBA disability codes to ICD-9-CM. We next mapped ICD-9-CM and the VBA Disability codes to SNOMED CT. The SNOMED CT mappings were matched across classification systems and terms from related concepts were displayed for an expert coder's review. We report the rate of direct ICD-9-CM to VBA Disability Code mapping (26%), the eventual success of the SNOMED CT based crosswalk (95%) and the rate at which the reviewer had to add codes to complete the mapping (99%). The method using the SNOMED CT crosswalk provided significantly better coverage than the ICD-9-CM direct mapping alone (Pearson Chi Square test; p<0.001). We conclude that SNOMED CT can be a useful adjunct to direct mapping between administrative classifications.