AIMTo examine the incidence and trends in pediatric inflammatory bowel diseases (IBDs) over 2000-2015 and project the incidence to 2018.METHODSA 16-year prospective study of IBD patients < 19 years of age was conducted in the Czech Republic (the Pilsen region). All incident IBD cases within a well-defined geographical area were retrieved from a prospectively collected computerized clinical database. Historical Czech data were used for comparison (1990-2001). Our catchment population was determined from the census data. We calculated the incidence by relating the number of newly diagnosed cases to the size of the pediatric population-at-risk in each calendar year. Age/sex, disease type, place of residence, and race/ethnicity were identified.RESULTSIn total, 170 new IBD cases [105 Crohn’s disease (CD), 48 ulcerative colitis (UC), and 17 IBD-unclassified (IBD-U)] were identified. The median age at IBD diagnosis was 14.2 years, 59.4% were males, and 97.1% were Caucasians. A male preponderance of IBD (P = 0.026) and CD (P = 0.016) was observed. With 109209 person-years in the catchment area, the average incidence of IBD per 100000 person-years was 10.0 (6.2 for CD, 2.8 for UC, and 1.0 for IBD-U) for children aged 0 to 19 years; for those aged 0 to 15 years, the incidence rate was 7.3 (4.6 for CD, 2.0 for UC, and 0.7 for IBD-U). An increase in incidence with age was observed (P = 0.0003). Over the 16-year period, the incidence increased for IBD patients (P = 0.01) and CD in particular (P < 0.0001), whereas the incidence for UC (P = 0.09) and IBD-U (P = 0.339) remained unchanged. IBD-projected data from 2016 to 2018 were 12.1, 12.3 and 12.6 per 100000 person-years, respectively.CONCLUSIONPediatric-onset IBD incidence is around its highest point. The increase, which is particularly pronounced for CD, may be challenging to relate to causes of pediatric disease.

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Generally, the interoperability is the key feature to any widely used application or an information system. A system build on the basis of semantic data interpretation can also lead to an easy extensible and adaptable system, in the future. Otherwise, you have to deal with a lack of agreed terminologies or codes between standards e.g. DASTA vs. HL7, different coding structures and even variety of file formats or inconsistent database table schema. The most of these difficulties can be solved by the semantically interoperable system. We present our implementation strategy and meta data extraction methods for a research information system with an heterogeneous medical data. The medical data can have different origin, type, file format and even its version. We discuss the research information system that we primarily use for cerebrovascular brain diseases research.

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