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Cited by 193Electronic Health Records SystemsPharmaceutical Practices and Patient OutcomesArtificial Intelligence in Healthcare and Education

The DOI matches its Crossref record; 80 of the 80 references it cites were found in a registry or an index.

Do computerised clinical decision support systems for prescribing change practice? A systematic review of the literature (1990-2007)

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Pearson, Sallie-Anne, Moxey, Annette, Robertson, Jane, Hains, Isla, Williamson, Margaret, Reeve, James, Newby, David·2009·BMC Health Services Research
DOI 10.1186/1472-6963-9-154PMC PMC2744674
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Abstract

BACKGROUND: Computerised clinical decision support systems (CDSSs) are used widely to improve quality of care and patient outcomes. This systematic review evaluated the impact of CDSSs in targeting specific aspects of prescribing, namely initiating, monitoring and stopping therapy. We also examined the influence of clinical setting (institutional vs ambulatory care), system- or user-initiation of CDSS, multi-faceted vs stand alone CDSS interventions and clinical target on practice changes in line with the intent of the CDSS. METHODS: We searched Medline, Embase and PsychINFO for publications from 1990-2007 detailing CDSS prescribing interventions. Pairs of independent reviewers extracted the key features and prescribing outcomes of methodologically adequate studies (experiments and strong quasi-experiments). RESULTS: 56 studies met our inclusion criteria, 38 addressing initiating, 23 monitoring and three stopping therapy. At the time of initiating therapy, CDSSs appear to be somewhat more effective after, rather than before, drug selection has occurred (7/12 versus 12/26 studies reporting statistically significant improvements in favour of CDSSs on = 50% of prescribing outcomes reported). CDSSs also appeared to be effective for monitoring therapy, particularly using laboratory test reminders (4/7 studies reporting significant improvements in favour of CDSSs on the majority of prescribing outcomes). None of the studies addressing stopping therapy demonstrated impacts in favour of CDSSs over comparators. The most consistently effective approaches used system-initiated advice to fine-tune existing therapy by making recommendations to improve patient safety, adjust the dose, duration or form of prescribed drugs or increase the laboratory testing rates for patients on long-term therapy. CDSSs appeared to perform better in institutional compared to ambulatory settings and when decision support was initiated automatically by the system as opposed to user initiation. CDSSs implemented with other strategies such as education were no more successful in improving prescribing than stand alone interventions. Cardiovascular disease was the most studied clinical target but few studies demonstrated significant improvements on the majority of prescribing outcomes. CONCLUSION: Our understanding of CDSS impacts on specific aspects of the prescribing process remains relatively limited. Future implementation should build on effective approaches including the use of system-initiated advice to address safety issues and improve the monitoring of therapy.

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Figure 1 Process of study inclusion for the systematic review. * 8 Studies provided data relevant to more than one prescribing domain.
Figure 1 Process of study inclusion for the systematic review. * 8 Studies provided data relevant to more than one prescribing domain.CC BY · PubMed Central

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Research works printed but not linked: 1

  1. Bero L, Deane K, Eccles M, Grimshaw J, Gruen R, Mayhew A, Oxman AD, Pantoja T, Paulsen E, Shepperd S, et al: Cochrane Effective Practice and Organisation of Care Group. About The Cochrane Collaboration (Cochrane Review Groups (CRGs)). 2009

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Metadata

Authors
Pearson, S.-A., Moxey, A., Robertson, J., Hains, I., Williamson, M., Reeve, J., & Newby, D.
Affiliations
  • UNSW Sydney (AU)
  • University of Newcastle Australia (AU)
Corresponding author
Pearson, Sallie-Anne
ORCID
Venue
BMC Health Services Research
Publisher
Springer Science and Business Media LLC
Published
2009-08-28
Volume
9
Issue
1
Pages
154-154
ISSN
1472-6963 (ISSN-L)
DOI
10.1186/1472-6963-9-154
PMC
PMC2744674
OpenAlex
W2080746135
Cited by
193
References
80
Citations by year
2026: 3 · 2025: 3 · 2024: 2 · 2023: 4 · 2022: 10 · 2021: 3 · 2020: 12 · 2019: 14 · 2018: 10 · 2017: 20 · 2016: 16 · 2015: 17 · 2014: 17 · 2013: 18 · 2012: 16
FWCI
2.19
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Health Services Research (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
  • NOVA (University of Newcastle Australia) (submittedVersion)
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Medicine › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
drug prescribing, drug initiation, treatment monitoring, patient safety, multicomponent intervention, cardiovascular disease
MeSH terms
Humans, Practice Patterns, Physicians', Drug Prescriptions, User-Computer Interface, Decision Support Systems, Clinical

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