(091) Characterization of select laboratory test in administrative healthcare data and data from commercial laboratories among patients with COVID-19 diagnosed in outpatient settings

Background: Laboratory tests and results are essential to medical care and may inform up to 70% of clinical decisions, but differences in capturing and defining laboratory information can cause unwanted variation in evidence and may affect decision making.

Objectives: To characterize select laboratory tests ordered and reported in administrative healthcare and commercial laboratory data for patients diagnosed with COVID-19.

Methods: Among patients with an outpatient COVID-19 diagnosis claim in HealthVerity data (01/01/2021-12/31/2022), this observational study describes baseline characteristics and descriptively compares SARS-CoV-2 diagnostic tests and liver function tests from administrative healthcare (insurance claims and hospital billing data) and commercial laboratories, overall and according to code type (e.g., CPT, LOINC). Select liver function tests were also described by method-specific and methodless LOINC.

Results: Among 214,998 patients with COVID-19, 46.1% had a SARS-CoV-2 molecular diagnostic test recorded within 7 days of diagnosis (in either administrative or laboratory data); 44.5% had a corresponding CPT in medical claims, whereas only 10.0% had a corresponding LOINC in laboratory data. In contrast, the six most common liver function tests (albumin, aspartate aminotransferase, total protein, alkaline phosphatase, alanine aminotransferase, total bilirubin) were identified in 55.7%-56.6% of patients via LOINC, but only in 3.2%-4.2% via CPT claims. Of the total count of select liver function tests performed in the laboratory data, 99.7% of aspartate aminotransferase, 96.1% of direct bilirubin, and 82.9% of lactate dehydrogenase were reported by methodless LOINC rather than method-specific LOINC.

Conclusions: Important differences were identified between orders for SARS-CoV-2 diagnostic tests and liver function tests, as well as for missingness of LOINC method, highlighting challenges related to completeness of secondary laboratory data in real-world data sources. These challenges underscore a need to improve data quality when considering the utility of laboratory data for research.