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Predictive models of disease burden at diagnosis in persons with adult-onset ulcerative colitis using health administrative data.


ABSTRACT:

Background

Health administrative data is increasingly used to conduct population-based health services research. A major limitation of these data for the study of inflammatory bowel diseases is the absence of detailed clinical information relating to disease burden. We used Ontario health administrative data to develop predictive models of disease burden at diagnosis in ulcerative colitis (UC) patients for future use in population-based studies of incident UC cohorts.

Methods

Through chart review, we characterized macroscopic colitis activity and extent at diagnosis in consecutive adult-onset UC patients diagnosed at The Ottawa Hospital between 2001 and 2012. We linked this cohort to Ontario health administrative data to test the capacity of administrative variables to discriminate different levels of disease activity, disease extent and the disease burden (a composite of disease extent and activity). We modelled outcomes as binary (using logistic regression) and ordinal (using proportional odds regression) variables and performed bootstrap validation of our final models.

Results

We tested 20 administrative variables in 587 eligible patients. The logistic model of total disease burden (severe and extensive colitis vs. all other phenotypes) showed moderate discriminatory capacity (optimism-corrected c-statistic value 0.729). Individual models of disease extent and disease activity showed poorer discriminatory capacity (c-statistic value ConclusionsOntario health administrative data may reasonably discriminate levels of total disease burden at diagnosis in adult-onset UC patients. Our models should be externally validated before their widespread application in future population-based studies of incident UC cohorts to adjust for the confounding effects of differences in disease burden.

SUBMITTER: Murthy SK 

PROVIDER: S-EPMC6341567 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Predictive models of disease burden at diagnosis in persons with adult-onset ulcerative colitis using health administrative data.

Murthy Sanjay K SK   Shukla Tushar T   Antonova Lilia L   Belair Marc-Andre MA   Ramsay Tim T   Gallinger Zane Z   Nguyen Geoffrey C GC   Benchimol Eric I EI  

BMC gastroenterology 20190121 1


<h4>Background</h4>Health administrative data is increasingly used to conduct population-based health services research. A major limitation of these data for the study of inflammatory bowel diseases is the absence of detailed clinical information relating to disease burden. We used Ontario health administrative data to develop predictive models of disease burden at diagnosis in ulcerative colitis (UC) patients for future use in population-based studies of incident UC cohorts.<h4>Methods</h4>Thro  ...[more]

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