Literature DB >> 9787630

Transforming a hospital through growing, not building, an electronic patient record system.

C J Atkinson1, V J Peel.   

Abstract

The benefits for any health care provider of successfully introducing an Electronic Patient Record System (EPRS) into their organisation can be considerable. It has the potential to enhance both clinical care and managerial processes, as well as producing more cost-effective care and care programmes across clinical disciplines and health care sectors. However, realising an EPRS's full potential can be a long and difficult process and should not be entered into lightly. Introducing an EPR System involves major personnel, organisational and technological changes. These changes must be interwoven and symbiotic and must be managed so that they grow together in stages towards a vision created and shared by all clinical professional staff, other staff, and managers in that process. The use of traditional "building" or "journey" metaphors inadequately reflects the complexity, uncertainty and, therefore, the unpredictability of the process. We propose that a more useful metaphor may be of "growing" a progressively more united, unified information system and health care organisation. We suggest this metaphor better recognises that the evolutionary process appears to be more organic than predictable and more systemic than mechanistic. An illustration is given of how these organisational clinical and technical issues might evolve and interweave in a hospital setting through a number of stages.

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Year:  1998        PMID: 9787630

Source DB:  PubMed          Journal:  Methods Inf Med        ISSN: 0026-1270            Impact factor:   2.176


  3 in total

1.  Information technology in ophthalmology-experience with an electronic patient record.

Authors:  G W Aylward; D N Parmar
Journal:  Br J Ophthalmol       Date:  1999-11       Impact factor: 4.638

2.  A user-centered, object-oriented methodology for developing Health Information Systems: a Clinical Information System (CIS) example.

Authors:  Georgios Konstantinidis; George C Anastassopoulos; Alexandros S Karakos; Emmanouil Anagnostou; Vasileios Danielides
Journal:  J Med Syst       Date:  2010-04-23       Impact factor: 4.460

3.  Predicting Therapy Success and Costs for Personalized Treatment Recommendations Using Baseline Characteristics: Data-Driven Analysis.

Authors:  Vincent Bremer; Dennis Becker; Spyros Kolovos; Burkhardt Funk; Ward van Breda; Mark Hoogendoorn; Heleen Riper
Journal:  J Med Internet Res       Date:  2018-08-21       Impact factor: 5.428

  3 in total

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