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Recruitment and feasibility tool

Characterisation

Tool, patient recruitment, clinical trial feasibility.

Tool description

The recruitment and feasibility tool (earlier named Yakobo) was developed in the EURECA project to assess protocol feasibility and to find eligible patients for clinical trials. Protocol feasibility functions analyze the feasibility of a trial protocol by assessing the expected patient enrollment rate of a selection of sites given the protocol’s eligibility criteria, based on “historical” data (existing patient data). It allows for answering questions such as whether inclusion and exclusion criteria are useful for defining the proper study population, whether it is likely that the necessary volume of patients can be recruited in time to collect data with sufficient statistical power and/or the expected duration of a trial.

Criteria are expressed in a domain specific language [1] A Trial metadata repository contains protocol definitions (Figure 1) and the SNAQL engine executes the DSL of the criteria to find patients belonging to the cohort. The SNAQL engine accesses the semantic integration services which provide a query interface [2] with reasoning abilities. Once a clinical protocol has been finalized, the tool is used to find patients eligible for enrollment.

Figure 1
figure1

Schema of the workflow for using the Recruitment and feasibility tool.

Status of development

Concept validation and validation by selected user groups.

Link

http://eurecaproject.eu/

References

  1. 1.

    Claerhout B, Schepper KD, Pérez-Rey D, Alonso-Calvo R, Leeuwen JV, Bucur A: Implementing patient recruitment on EURECA semantic integration platform through a Groovy query engine. Proc. BIBE. 2013, 1-5.

  2. 2.

    Paraiso-Medina S, Perez-Rey D, Alonso-Calvo R, Claerhout B, de Schepper K, Hennebert P, et al: Semantic Interoperability Solution for Multicentric Breast Cancer Trials at the Integrate EU Project. HEALTHINF. 2013, 34-41.

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Author information

Correspondence to Jasper van Leeuwen.

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Keywords

  • Specific Language
  • Enrollment Rate
  • Integration Service
  • Reasoning Ability
  • Sufficient Statistical Power