# Improving treatment of lactation mastitis: leveraging claims data to fill evidence gaps > **NIH NIH R03** · TRUSTEES OF INDIANA UNIVERSITY · 2024 · $158,500 ## Abstract SUMMARY Lactation mastitis is an extremely painful and debilitating condition that affects 10-25% of breastfeeding people and can progress to breast abscess or septic fever. This significant disease burden occurs mostly during the first six months when birthing people are still in recovery from pregnancy and childbirth. The objective of the proposed study is to compare classes of antibiotics on first-line treatment failure and document disparities in severity at presentation and antibiotic prescription rates by race/ethnicity. Our central hypotheses are that some treatments are more effective than others for avoiding treatment failure and that there are measurable disparities in severity at presentation and treatments prescribed by race/ethnicity. We will construct a cohort of >5,000 diagnosed mastitis cases utilizing a nationwide healthcare claims dataset and conduct rigorous analyses to explore these hypotheses. Our team is uniquely poised to answer these critical research questions and includes an infectious disease epidemiologist, a lactation clinician who co-authored the current mastitis treatment guidelines, and an expert in using claims data to asses downstream impacts of medication use. Specifically, we aim to: (1) Compare the effectiveness of classes of antibiotics (e.g., first and second generation penicillins, cephalosporins, lincosamides, sulfonamides) prescribed for lactation mastitis on first-line treatment failure, abscess, and hospital admission. We hypothesize that given community and hospital transmission of MRSA, short-course penicillins will have the highest rate of first-line treatment failure. (2) Describe disparities by race/ethnicity in the severity of mastitis at presentation and the antibiotic prescription patterns after mastitis diagnosis. We hypothesize that given barriers to antenatal care and implicit provider bias, Black and Latina/e/x breastfeeding people will present with more severe cases of mastitis and are prescribed antibiotics less frequently after diagnosis in comparison with white breastfeeding people. The proposed study will make significant and novel contributions toward understanding current patterns in antibiotic prescriptions for mastitis treatment and the relative effectiveness of current antibiotic treatments. The formation of a mastitis diagnosis cohort using the Optum dataset will provide a platform to assess a number of other important factors such as local antibiotic resistance patterns and to assess the impact of changing policies (both mastitis treatment and antibiotic stewardship policies) on successful treatment. These results will also provide information on the most effective treatments to assess in future randomized trials. Innovative aspects of our proposal include: (1) high-quality observational studies that advance our understanding and can guide the design of future randomized trials, (2) assessment of treatment disparities by race/ethnicity which is critical for responding to clinical... ## Key facts - **NIH application ID:** 10952650 - **Project number:** 1R03HD116000-01 - **Recipient organization:** TRUSTEES OF INDIANA UNIVERSITY - **Principal Investigator:** Christina Marie Ludema - **Activity code:** R03 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $158,500 - **Award type:** 1 - **Project period:** 2024-09-01 → 2026-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10952650 ## Citation > US National Institutes of Health, RePORTER application 10952650, Improving treatment of lactation mastitis: leveraging claims data to fill evidence gaps (1R03HD116000-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10952650. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*