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P614 A strategy to solve complexity of physician diagnosis using a mixture of Patient Reports and Provider Reports: A Case Study of Crohn’s Disease Phenotypes

Zhang, L.(1);Fan, Y.(2);Thompson, J.(3);Bohn, R.(4);Negar, O.(4);Brodovicz, K.(2);Parakkal, D.(5);

(1)Boehringer Ingelheim Pharmaceuticals Inc., Real World Evidence Analytics Center of Excellence, Ridgefield, United States;(2)Boehringer Ingelheim Pharmaceuticals Inc., Global Epidemiology, Ridgefield, United States;(3)Boehringer Ingelheim Pharmaceuticals Inc., TA Inflammation Medicine, Ridgefield, United States;(4)Bohn Epidemiology, Consulting Services, Boston, United States;(5)Washington University School of Medicine, Institute of Clinical and Translational Sciences, Saint Louis, United States

Background

The IBD Plexus® Registry, established by the US Crohn’s & Colitis Foundation, combines patient and provider reported survey data collected from doctors’ visits and historical data in electronic medical record (EMR) systems. This multi-resource dataset presents data discrepancies in assessing phenotypes of Crohn’s disease (CD). The aim of this analysis is to describe a strategic process to solve data challenges related to CD phenotype definitions based on the IBD Plexus data. 

Methods

This cross-sectional, multicenter, US based study used data from 11/2016 to 06/2020 from the IBD Plexus® Sparc program to assess demographics, symptoms and treatments among CD patients.  Data discrepancies between CD phenotype status reported and as described in historical EMRs were identified. Physicians may use the Montreal classification with/without the Paris modification for phenotype evaluation. To resolve this discrepancy, we explored and evaluated several study phenotype definitions: 1) using phenotypes at visits, the registry suggested method; 2) using phenotype and history of fistula/abscess or stricture in EMR; and 3) using definition 2 without anal stricture. The implementation included two steps: 1) severe conditions (penetrating, stricturing or both) were considered irreversible and defined using the data at any time before  30 days after the registry consent date; 2) the inflammatory condition was positive in the absence of any other reported severe condition during the entire study period.

Results

The frequency results by phenotypes show small differences across definitions (Figure 1). The discrepancy in frequency by definition1 demonstrated the phenotypes recorded at visits contradicted phenotypes in the EMR. For instance, 0.1%-3.2% or 0.1-0.7% of CD inflammatory patients had subtypes of stricture and subtypes of fistula/abscess, respectively. About 0.5% of CD stricturing patients had intra-abdominal abscess or other fistula (Figure 2). Among CD penetrating patients, 32.0% had history of ileal stricture (Figure 3). Including EMR phenotype variables in definition 2, all discrepancies were resolved. With verification, anal strictures are due to perianal disease which should not be used in the stricturing definition; therefore, the anal stricture was exempt from definition 3. All subtype phenotypes showed 0% discrepancy with study phenotype. A small percentage of positive anal stricture patients was allowed in definition 3. 

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Conclusion

When handling the mixture of patient reported and provider-reported data, data discrepancies have many causes. Clarifying the clinical rationale is a key process to resolve discrepancies and accurately define measures of interest.

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