%0 Journal Article %A Vivek Ashok Rudrapatna %A Benjamin Scott Glicksberg %A Atul Janardhan Butte %T Utility of routinely collected electronic health records data to support effectiveness evaluations in inflammatory bowel disease: a pilot study of tofacitinib %D 2021 %R 10.1136/bmjhci-2021-100337 %J BMJ Health & Care Informatics %P e100337 %V 28 %N 1 %X Objectives Electronic health records (EHR) are receiving growing attention from regulators, biopharmaceuticals and payors as a potential source of real-world evidence. However, their suitability for the study of diseases with complex activity measures is unclear. We sought to evaluate the use of EHR data for estimating treatment effectiveness in inflammatory bowel disease (IBD), using tofacitinib as a use case.Methods Records from the University of California, San Francisco (6/2012 to 4/2019) were queried to identify tofacitinib-treated IBD patients. Disease activity variables at baseline and follow-up were manually abstracted according to a preregistered protocol. The proportion of patients meeting the endpoints of recent randomised trials in ulcerative colitis (UC) and Crohn’s disease (CD) was assessed.Results 86 patients initiated tofacitinib. Baseline characteristics of the real-world and trial cohorts were similar, except for universal failure of tumour necrosis factor inhibitors in the former. 54% (UC) and 62% (CD) of patients had complete capture of disease activity at baseline (month −6 to 0), while only 32% (UC) and 69% (CD) of patients had complete follow-up data (month 2 to 8). Using data imputation, we estimated the proportion achieving the trial primary endpoints as being similar to the published estimates for both UC (16%, p value=0.5) and CD (38%, p-value=0.8).Discussion/Conclusion This pilot study reproduced trial-based estimates of tofacitinib efficacy despite its use in a different cohort but revealed substantial missingness in routinely collected data. Future work is needed to strengthen EHR data and enable real-world evidence in complex diseases like IBD.Data are available in a public, open access repository. The analytic code in the form of a R markdown file as well as the accompanying data set needed to reproduce the analysis in this work are available in a Docker container to all investigators without restriction (https://doi.org/10.7272/Q6PZ5715). These individual participant data were de-identified to comply with the US Department of Health and Human Services ‘Safe Harbor’ guidance and applicable laws and regulations concerning privacy and/or security of personal information. The data dictionary is documented within the study protocol section of Supplemental Content. %U https://informatics.bmj.com/content/bmjhci/28/1/e100337.full.pdf