Literature DB >> 11067416

The diffusion of decision support systems in healthcare: are we there yet?

H J Wong1, M W Legnini, H H Whitmore.   

Abstract

Clinical decision support (CDS) systems, with the potential to minimize practice variation and improve patient care, have begun to surface throughout the healthcare industry. This study reviews historic patterns of information technology (IT) in healthcare, analyzes barriers and enabling factors, and draws three lessons. First, the widespread adoption of clinical IT, including CDS systems, depends on having the right organizational and individual financial incentives in place. Second, although CDS systems and clinical IT in general are powerful tools that can be used to support the practice of medicine, they alone cannot redefine the workflow or processes within the profession. Healthcare managers counting on technology to restructure or monitor clinicians' work patterns are likely to encounter substantial resistance to CDS systems, even those that generate valuable information. Third, while the pace of implementing IT systems in healthcare has lagged behind that of other industries, many of the obstacles are gradually diminishing. However, several factors continue to inhibit their widespread diffusion, including the organizational turmoil created by large numbers of mergers and acquisitions, and the lack of uniform data standards.

Entities:  

Mesh:

Year:  2000        PMID: 11067416

Source DB:  PubMed          Journal:  J Healthc Manag        ISSN: 1096-9012


  5 in total

1.  Virtual healthcare delivery: defined, modeled, and predictive barriers to implementation identified.

Authors:  V M Harrop
Journal:  Proc AMIA Symp       Date:  2001

2.  Transaction-neutral implanted data collection interface as EMR driver: a model for emerging distributed medical technologies.

Authors:  Daniel Lorence; Anusha Sivaramakrishnan; Michael Richards
Journal:  J Med Syst       Date:  2009-03-20       Impact factor: 4.460

3.  Data-Driven Diffusion Of Innovations: Successes And Challenges In 3 Large-Scale Innovative Delivery Models.

Authors:  David A Dorr; Deborah J Cohen; Julia Adler-Milstein
Journal:  Health Aff (Millwood)       Date:  2018-02       Impact factor: 6.301

4.  Patient safety-related information technology utilization in urban and rural hospitals.

Authors:  Robert G Brooks; Nir Menachemi; Darrell Burke; Art Clawson
Journal:  J Med Syst       Date:  2005-04       Impact factor: 4.460

5.  A survey of extant organizational and computational setups for deploying predictive models in health systems.

Authors:  Sehj Kashyap; Keith E Morse; Birju Patel; Nigam H Shah
Journal:  J Am Med Inform Assoc       Date:  2021-10-12       Impact factor: 4.497

  5 in total

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