CoChat
Sign Up
Cited by 47Electronic Health Records SystemsTechnology and Human Factors in Education and HealthArtificial Intelligence in Healthcare and Education

Are we measuring the right end-points? Variables that affect the impact of computerised decision support on patient outcomes: a systematic review

Sintchenko, Vitali, Magrabi, Farah, Tipper, Steven·2007·Medical Informatics and the Internet in Medicine
DOI 10.1080/14639230701447701
Open this paper in CoChat — free account

Abstract

Previous reviews of electronic decision-support systems (EDSS) have often treated them as a single category, and factors that may modify their effectiveness of EDSS have not been examined. The objective was to summarise the evidence associating the use of computerised decision support and improved patient outcomes. PubMed/Medline and the Database of Abstracts were searched for randomised controlled trials (RCT) of EDSS from 1 January 1994 to 31 January 2006. Twenty-four RCT studies from 97 reviewed were selected, eight of them examined systems supporting decisions for patients who presented with an acute illness, and 16 studies enrolled patients with chronic conditions. Overall, 13 (54%) of the studies showed a positive result, and 11 (46%) were with no impact. Critiquing and consultative systems showed the impact in 71% and 47% of studies, respectively. All systems targeting decisions related to acute disease improved patient outcomes compared with 38% of systems focused on the management of chronic conditions (P = 0.005). Provision of EDSS improves prescribing practices and treatment outcomes of patients with acute illnesses; however, EDSS were less effective in primary care. Complex interventions as clinical EDSS may require new metrics of assessment to describe the impact on patient outcomes.

Integrity signals

Registry

Crossref · 10.1080/14639230701447701

Cites

74 of 74 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Reviews covering electronic and paper-based CDSS in multiple clinical areas found they can alter clinician behavior, including screening, test ordering, and adherence to guidelines.

    “Systematic reviews of electronic and paper-based clinical decision support across a range of clinical domains have demonstrated its effectiveness in changing clinicians' practices such as screening, test ordering and guideline adherence, 5 7-9 11-13 but there is no consistent translation into patient outcomes.11”

    From Computerized clinical decision support for prescribing: provision does not guarantee uptake (2010) · cites this paper as [13]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Sintchenko, V., Magrabi, F., & Tipper, S.
Affiliations
  • The University of Sydney (AU)
  • UNSW Sydney (AU)
ORCID
Venue
Medical Informatics and the Internet in Medicine
Publisher
Informa UK Limited
Published
2007-01
Volume
32
Issue
3
Pages
225-240
ISSN
1463-9238 (ISSN-L)
DOI
10.1080/14639230701447701
OpenAlex
W2010776693
Cited by
47
References
74
Citations by year
2023: 1 · 2022: 1 · 2021: 1 · 2020: 3 · 2019: 1 · 2018: 3 · 2017: 3 · 2016: 2 · 2015: 2 · 2013: 7 · 2012: 6
FWCI
0.67
Type
journal article
Language
en
Open access
closed
Locations
  • Medical Informatics and the Internet in Medicine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
computerised decision support, decision support system, patient outcomes, acute illness, chronic disease, prescribing patterns, primary care, clinical decision support, outcome measurement, complex interventions
MeSH terms
Acute Disease, Chronic Disease, Diagnosis, Computer-Assisted, Humans, Randomized Controlled Trials as Topic, Outcome Assessment, Health Care, Decision Support Systems, Clinical, Endpoint Determination

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review