CHARACTERIZING THE JOHNS HOPKINS INFLAMMATORY BOWEL DISEASE COHORT USING OMOP CDM

Abstract BACKGROUND Inflammatory Bowel Disease (IBD) is an increasingly prevalent condition that results in weight loss, bloody diarrhea, and poor quality of life. Traditional population-based research on patients with IBD has involved use relatively shallow claims data deficient precise demographics. using richly detailed electronic health record (EHR) been difficult due to the need for laborious manual chart review extract information, but new methods technology allow rapid EHR extraction. We present here extraction patient from our into Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). METHODS This study observational cohort care extracted OMOP CDM. Transforming standard CDM format allows information different databases coding schema be compared aggregated. used a de-identified dataset all seen at Johns Hopkins Medicine since 2016. Our IBD, Crohn’s disease (CD), Ulcerative Colitis (UC) were stratified by age, sex, race, weight, pregnancy status. Within cohorts, we obtained demographics, comorbidities, symptoms, labs, medications, other data. validated comparison queries Slicer/Dicer (SD). RESULTS There 11,357 including 6,512 CD 4,224 UC patients. more female both (56.4% v 57.5%) white (55.4% 56.7%) black (23.5% 22.6%) Asian (5.6% 4.9%). treated systemic steroids (49.1% 51.5%), 5-ASA (24.9% 47.2%) anti-TNF inhibitors (24.0% 12%), IL12/23 (8.4% 2.7%), JAK (0.3% 1.8%). Using SD queries, percent differences determined between data, revealing 0.54% difference number 10.36% (Table 1). CONCLUSION analyze clinical characteristics outcomes valuable method obtaining reducing risk, facilitating creation on-demand cohorts multi-institutional studies. advantage balanced lack access row-level validate cohorts. Local validation through can big research. The most significant was calculation prevalence medications suggesting differing could result underestimate rates treatment proprietary local schema.