Literature DB >> 17084664

A qualitative study of the implementation of a bioinformatics tool in a biological research laboratory.

Nicholas R Anderson1, Joan S Ash, Peter Tarczy-Hornoch.   

Abstract

OBJECTIVE: To explore how the implementation of a comprehensive new bioinformatics analysis system would affect workflow, collaboration and information management in a small genetic research lab.
DESIGN: This was a longitudinal qualitative study of seven individuals involved in genomic and proteomic research. The study data were gathered using the illuminative/responsive approach of immersion in the environment. Additional qualitative data were gathered using informal semi-structured interviews, participant observation in lab meetings, and direct observation of lab researchers engaged in specific tasks. MEASUREMENTS: Interview, observation and field note data were coded and analyzed based on three analysis perspectives. A subset of the data was independently evaluated by an external researcher to enhance the trustworthiness of results.
RESULTS: Three reoccurring themes were observed in the study. (1) Satisfaction and acceptance of software tools tended to be role and goal specific. (2) The system was seen primarily as a measurement system rather than a "total laboratory analysis system". (3) Lab meetings deemphasized the system, preferring more traditional data analysis techniques. These themes support the observations that the system was not used to its full potential in the lab.
CONCLUSION: Themes identified in this study suggest that sophisticated genetic researchers face similar problems of technology implementation as do professionals in other fields. We recommend that leadership support and on-going training and evolution of academic curricula can improve chances of bioinformatics analysis systems becoming used more effectively.

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Mesh:

Year:  2006        PMID: 17084664     DOI: 10.1016/j.ijmedinf.2006.09.022

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  7 in total

1.  Issues in biomedical research data management and analysis: needs and barriers.

Authors:  Nicholas R Anderson; E Sally Lee; J Scott Brockenbrough; Mark E Minie; Sherrilynne Fuller; James Brinkley; Peter Tarczy-Hornoch
Journal:  J Am Med Inform Assoc       Date:  2007-04-25       Impact factor: 4.497

2.  Commentaries on "Informatics and medicine: from molecules to populations".

Authors:  R B Altman; R Balling; J F Brinkley; E Coiera; F Consorti; M A Dhansay; A Geissbuhler; W Hersh; S Y Kwankam; N M Lorenzi; F Martin-Sanchez; G I Mihalas; Y Shahar; K Takabayashi; G Wiederhold
Journal:  Methods Inf Med       Date:  2008       Impact factor: 2.176

3.  Resolving complex research data management issues in biomedical laboratories: Qualitative study of an industry-academia collaboration.

Authors:  Sahiti Myneni; Vimla L Patel; G Steven Bova; Jian Wang; Christopher F Ackerman; Cynthia A Berlinicke; Steve H Chen; Mikael Lindvall; Donald J Zack
Journal:  Comput Methods Programs Biomed       Date:  2015-11-12       Impact factor: 5.428

4.  Organization of Biomedical Data for Collaborative Scientific Research: A Research Information Management System.

Authors:  Sahiti Myneni; Vimla L Patel
Journal:  Int J Inf Manage       Date:  2010-06-01

5.  Supporting cognition in systems biology analysis: findings on users' processes and design implications.

Authors:  Barbara Mirel
Journal:  J Biomed Discov Collab       Date:  2009-02-13

6.  People and organizational issues in research systems implementation.

Authors:  Joan S Ash; Nicholas R Anderson; Peter Tarczy-Hornoch
Journal:  J Am Med Inform Assoc       Date:  2008-02-28       Impact factor: 4.497

7.  Collaboration gets the most out of software.

Authors:  Andrew Morin; Ben Eisenbraun; Jason Key; Paul C Sanschagrin; Michael A Timony; Michelle Ottaviano; Piotr Sliz
Journal:  Elife       Date:  2013-09-10       Impact factor: 8.140

  7 in total

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