Literature DB >> 24734138

Design and multicentric implementation of a generic software architecture for patient recruitment systems re-using existing HIS tools and routine patient data.

B Trinczek1, F Köpcke2, T Leusch3, R W Majeed4, B Schreiweis5, J Wenk6, B Bergh5, C Ohmann6, R Röhrig4, H U Prokosch2, M Dugas1.   

Abstract

OBJECTIVE: (1) To define features and data items of a Patient Recruitment System (PRS); (2) to design a generic software architecture of such a system covering the requirements; (3) to identify implementation options available within different Hospital Information System (HIS) environments; (4) to implement five PRS following the architecture and utilizing the implementation options as proof of concept.
METHODS: Existing PRS were reviewed and interviews with users and developers conducted. All reported PRS features were collected and prioritized according to their published success and user's request. Common feature sets were combined into software modules of a generic software architecture. Data items to process and transfer were identified for each of the modules. Each site collected implementation options available within their respective HIS environment for each module, provided a prototypical implementation based on available implementation possibilities and supported the patient recruitment of a clinical trial as a proof of concept.
RESULTS: 24 commonly reported and requested features of a PRS were identified, 13 of them prioritized as being mandatory. A UML version 2 based software architecture containing 5 software modules covering these features was developed. 13 data item groups processed by the modules, thus required to be available electronically, have been identified. Several implementation options could be identified for each module, most of them being available at multiple sites. Utilizing available tools, a PRS could be implemented in each of the five participating German university hospitals.
CONCLUSION: A set of required features and data items of a PRS has been described for the first time. The software architecture covers all features in a clear, well-defined way. The variety of implementation options and the prototypes show that it is possible to implement the given architecture in different HIS environments, thus enabling more sites to successfully support patient recruitment in clinical trials.

Entities:  

Keywords:  Clinical trials as topic; hospital information systems; patient identification systems; patient selection; software architecture

Mesh:

Year:  2014        PMID: 24734138      PMCID: PMC3974260          DOI: 10.4338/ACI-2013-07-RA-0047

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.342


  28 in total

1.  Routine data from hospital information systems can support patient recruitment for clinical studies.

Authors:  Martin Dugas; Matthias Lange; Carsten Müller-Tidow; Paulus Kirchhof; Hans-Ulrich Prokosch
Journal:  Clin Trials       Date:  2010-03-25       Impact factor: 2.486

2.  Using an information warehouse to screen patients for clinical trials: a prototype.

Authors:  Jyoti Kamal; Kabardhi Pasuparthi; Patrick Rogers; Jason Buskirk; Hagop Mekhjian
Journal:  AMIA Annu Symp Proc       Date:  2005

3.  Unlocking Data for Clinical Research - The German i2b2 Experience.

Authors:  T Ganslandt; S Mate; K Helbing; U Sax; H U Prokosch
Journal:  Appl Clin Inform       Date:  2011-03-30       Impact factor: 2.342

4.  Finding appropriate clinical trials: evaluating encoded eligibility criteria with incomplete data.

Authors:  N Ash; O Ogunyemi; Q Zeng; L Ohno-Machado
Journal:  Proc AMIA Symp       Date:  2001

Review 5.  Comparing semi-automatic systems for recruitment of patients to clinical trials.

Authors:  Marc Cuggia; Paolo Besana; David Glasspool
Journal:  Int J Med Inform       Date:  2011-04-02       Impact factor: 4.046

6.  Preserving consent-for-consent with feasibility-assessment and recruitment in clinical studies: FARSITE architecture.

Authors:  John Ainsworth; Iain Buchan
Journal:  Stud Health Technol Inform       Date:  2009

7.  Web-based decision support for clinical trial eligibility determination in an international clinical trials network.

Authors:  Philip P Breitfeld; Fred Ullrich; James Anderson; William M Crist
Journal:  Control Clin Trials       Date:  2003-12

8.  Selection of patients for clinical trials: an interactive web-based system.

Authors:  Eugene Fink; Princeton K Kokku; Savvas Nikiforou; Lawrence O Hall; Dmitry B Goldgof; Jeffrey P Krischer
Journal:  Artif Intell Med       Date:  2004-07       Impact factor: 5.326

9.  Analysis of eligibility criteria complexity in clinical trials.

Authors:  Jessica Ross; Samson Tu; Simona Carini; Ida Sim
Journal:  Summit Transl Bioinform       Date:  2010-03-01

10.  What influences recruitment to randomised controlled trials? A review of trials funded by two UK funding agencies.

Authors:  Alison M McDonald; Rosemary C Knight; Marion K Campbell; Vikki A Entwistle; Adrian M Grant; Jonathan A Cook; Diana R Elbourne; David Francis; Jo Garcia; Ian Roberts; Claire Snowdon
Journal:  Trials       Date:  2006-04-07       Impact factor: 2.279

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  8 in total

1.  Clinical Research Informatics: Recent Advances and Future Directions.

Authors:  M Dugas
Journal:  Yearb Med Inform       Date:  2015-08-13

Review 2.  Key components and IT assistance of participant management in clinical research: a scoping review.

Authors:  Johannes Pung; Otto Rienhoff
Journal:  JAMIA Open       Date:  2020-10-14

3.  Leveraging Real-World Data for the Selection of Relevant Eligibility Criteria for the Implementation of Electronic Recruitment Support in Clinical Trials.

Authors:  Georg Melzer; Tim Maiwald; Hans-Ulrich Prokosch; Thomas Ganslandt
Journal:  Appl Clin Inform       Date:  2021-01-13       Impact factor: 2.342

Review 4.  Employing computers for the recruitment into clinical trials: a comprehensive systematic review.

Authors:  Felix Köpcke; Hans-Ulrich Prokosch
Journal:  J Med Internet Res       Date:  2014-07-01       Impact factor: 5.428

5.  Applied Practice and Possible Leverage Points for Information Technology Support for Patient Screening in Clinical Trials: Qualitative Study.

Authors:  Linda Becker; Thomas Ganslandt; Hans-Ulrich Prokosch; Axel Newe
Journal:  JMIR Med Inform       Date:  2020-06-16

6.  MAGIC: once upon a time in consent management-a FHIR® tale.

Authors:  Martin Bialke; Thomas Bahls; Lars Geidel; Henriette Rau; Arne Blumentritt; Sandra Pasewald; Robert Wolff; Jonas Steinmann; Tobias Bronsch; Björn Bergh; Galina Tremper; Martin Lablans; Frank Ückert; Stefan Lang; Tarik Idris; Wolfgang Hoffmann
Journal:  J Transl Med       Date:  2018-09-14       Impact factor: 5.531

7.  Patient Recruitment System for Clinical Trials: Mixed Methods Study About Requirements at Ten University Hospitals.

Authors:  Kai Fitzer; Renate Haeuslschmid; Romina Blasini; Fatma Betül Altun; Christopher Hampf; Sherry Freiesleben; Philipp Macho; Hans-Ulrich Prokosch; Christian Gulden
Journal:  JMIR Med Inform       Date:  2022-04-20

8.  MIRACUM: Medical Informatics in Research and Care in University Medicine.

Authors:  Hans-Ulrich Prokosch; Till Acker; Johannes Bernarding; Harald Binder; Martin Boeker; Melanie Boerries; Philipp Daumke; Thomas Ganslandt; Jürgen Hesser; Gunther Höning; Michael Neumaier; Kurt Marquardt; Harald Renz; Hermann-Josef Rothkötter; Carmen Schade-Brittinger; Paul Schmücker; Jürgen Schüttler; Martin Sedlmayr; Hubert Serve; Keywan Sohrabi; Holger Storf
Journal:  Methods Inf Med       Date:  2018-07-17       Impact factor: 2.176

  8 in total

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