Electronic clinical quality measure (eCQM) concordance and quality care disparities among patients with breast cancer (BC).
Authors: Nehanda Jones, Elizabeth Lipschultz, Adam Blair, Brooke Smither, Jacob Koskimaki, Robert S. Miller
Journal: Journal of Clinical Oncology (2024)

e23237 Background: BC mortality is decreasing steadily, yet disparities in treatment and outcomes persist. eCQMs are metrics specified in a standard electronic format using data from electronic health records (EHR) and other systems to measure care quality. CancerLinQ is a health technology platform aggregating EHR data from ~7M patients (pts) seen in US oncology practices and cancer centers. This analysis assesses odds of non-concordance with 4 BC-specific eCQMs in CancerLinQ. Methods: Pts actively treated for BC in 2021 in CancerLinQ data were included in this study. The following four practice-level eCQMs were assessed as proportions of BC pts who: eCQM1 – Undergo HER2 testing eCQM2 – Are &lt; age 70 with early-stage, hormone receptor (HR) negative BC who receive combination chemotherapy &lt; 4 months of dx eCQM3 – Have early-stage, HER2+ BC and receive trastuzumab eCQM4 – Have early-stage, HR+ BC and receive tamoxifen or an aromatase inhibitor (AI) &lt; 1-year of dx Ethnicity, race, age at dx, pt/practice rural status, and practice type were assessed as covariates. Adjusted odds ratios (aOR) and 95% confidence intervals (95% CI) were calculated for associations among study variables and receipt of guideline non-concordant care. Results: aORs (95% CI) of pt characteristics were compared to reference groups - non-Hispanic, white, age at dx 60-69, married, urban: eCQM1 (N = 21296): For unknown ethnicity, aOR (95% CI) = 1.5 (1.3 1.6); unknown race = 1.3 (1.2, 1.5); age 70-79 = 1.1 (1.0, 1.2), age 80-89 = 1.4 (1.2, 1.5), age &gt; 90 = 1.5 (1.1, 2.2); formerly married/partnered = 1.2 (1.1, 1.3), thus having greater odds of non-concordance. Age 40-49, aOR (95% CI) = 0.9 (0.8, 0.986), had lower odds of non-concordance. eCQM2 (N = 1259): For unknown ethnicity, aOR (95% CI) = 1.9 (1.2, 3.1); Asian = 2.9 (1.7, 4.9) or other race = 2.3 (1.2, 4.1); and formerly married/partnered = 1.7 (1.2, 2.6), thus having greater odds of non-concordance. Pts age &lt; 40 = 0.6 (0.3, 0.9) had lower odds of non-concordance. eCQM3 (N = 1341): Age &gt; 80, aOR (95% CI) = 3.8 (1.5, 9.1), had greater odds of non-concordance. eCQM4 (N = 5063): For age &lt; 40, aOR (95% CI) = 2.9 (2.1, 4.1), age 40-49 = 1.6 (1.2, 2.0), and age 50-59 = 1.5 (1.2, 1.9); and formerly married/partnered = 1.3 (1.1, 1.7), thus having greater odds of non-concordance. Conclusions: As expected, pts &lt; 40 had greater odds of receiving chemotherapy and pts &gt; 80 had lower odds of receiving trastuzumab, possibly due to cardiotoxicity concerns. Although all women with early-stage HR+ BC are potential tamoxifen/AI candidates, pts &lt; 60 with early-stage HR+ BC had greater odds of not receiving tamoxifen/AI compared to those age 60-69. Additionally, divorced, separated, or widowed pts had greater odds of non-concordant care in 3 of 4 of eCQMs assessed. Our findings demonstrate the ability of eCQMs to identify clinical subgroups more likely to receive non-concordant care who may be eligible for targeted interventions.