Literature DB >> 11186051

Information technology adoption in health care: when organisations and technology collide.

I England1, D Stewart, S Walker.   

Abstract

The implementation of advanced information systems is enabling great social and organisational changes. However, health care has been one of the slowest sectors to adopt and implement information technology (IT). This paper investigates why this is so, reviewing innovation diffusion theory and its application to both health organisations and information technology. Innovation diffusion theory identifies variables that influence the 'innovativeness' of organisations and the rate at which a technology diffuses. When analysed, these variables show why IT implementation has progressed at a slower rate in health compared with other industry sectors. The complexity of health organisations and their fragmented internal structure constrain their ability to adopt organisation wide IT. This is further impacted upon by the relative immaturity of strategic health IT which is complicated and unable to show quantifiable benefits. Both organisational and technological factors lead to the slow adoption of strategic IT. On the other hand, localised IT solutions and those providing measurable cost reductions have diffused well.

Mesh:

Year:  2000        PMID: 11186051     DOI: 10.1071/ah000176

Source DB:  PubMed          Journal:  Aust Health Rev        ISSN: 0156-5788            Impact factor:   1.990


  13 in total

1.  Understanding implementation: the case of a computerized physician order entry system in a large Dutch university medical center.

Authors:  Jos Aarts; Hans Doorewaard; Marc Berg
Journal:  J Am Med Inform Assoc       Date:  2004-02-05       Impact factor: 4.497

Review 2.  Innovation in hospitals: a survey of the literature.

Authors:  Faridah Djellal; Faïz Gallouj
Journal:  Eur J Health Econ       Date:  2006-12-21

3.  Systems failure in hospitals--using Reason's model to predict problems in a prescribing information system.

Authors:  R M Lederman; C Parkes
Journal:  J Med Syst       Date:  2005-02       Impact factor: 4.460

4.  Implementation of electronic medical records: theory-informed qualitative study.

Authors:  Michelle Greiver; Jan Barnsley; Richard H Glazier; Rahim Moineddin; Bart J Harvey
Journal:  Can Fam Physician       Date:  2011-10       Impact factor: 3.275

5.  A systematic review on natural language processing systems for eligibility prescreening in clinical research.

Authors:  Betina Idnay; Caitlin Dreisbach; Chunhua Weng; Rebecca Schnall
Journal:  J Am Med Inform Assoc       Date:  2021-12-28       Impact factor: 4.497

Review 6.  Who's using PDAs? Estimates of PDA use by health care providers: a systematic review of surveys.

Authors:  Chantelle Garritty; Khaled El Emam
Journal:  J Med Internet Res       Date:  2006-05-12       Impact factor: 5.428

7.  The challenge of big data in public health: an opportunity for visual analytics.

Authors:  Oluwakemi Ola; Kamran Sedig
Journal:  Online J Public Health Inform       Date:  2014-02-05

8.  Evidence in the learning organization.

Authors:  Gerald E Crites; Megan C McNamara; Elie A Akl; W Scott Richardson; Craig A Umscheid; James Nishikawa
Journal:  Health Res Policy Syst       Date:  2009-03-26

9.  The use of electronic data capture tools in clinical trials: Web-survey of 259 Canadian trials.

Authors:  Khaled El Emam; Elizabeth Jonker; Margaret Sampson; Karmela Krleza-Jerić; Angelica Neisa
Journal:  J Med Internet Res       Date:  2009-03-09       Impact factor: 5.428

Review 10.  Staff experiences within the implementation of computer-based nursing records in residential aged care facilities: a systematic review and synthesis of qualitative research.

Authors:  Anne Meißner; Wilfried Schnepp
Journal:  BMC Med Inform Decis Mak       Date:  2014-06-20       Impact factor: 2.796

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