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Cited by 76Electronic Health Records SystemsArtificial Intelligence in Healthcare and EducationClinical Reasoning and Diagnostic Skills

Clinical decision support systems in the pediatric intensive care unit*

Mack, Elizabeth H., Wheeler, Derek S., Embi, Peter J.·2009·Pediatric Critical Care Medicine
DOI 10.1097/pcc.0b013e3181936b23
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Abstract

OBJECTIVE: To review the use of clinical decision support systems (CDSS) available in the pediatric intensive care unit (PICU). DATA SOURCES: Relevant English language publications indexed in Medline, as well as CDSS-related white papers and texts. STUDY SELECTION AND DATA EXTRACTION: Studies related to CDSS were considered. DATA SYNTHESIS: CDSS are operationally defined as computer software programs that aid healthcare providers in their clinical decision making. Once used solely for diagnostic support, many CDSS now have the ability to transform clinical practice through interactive assistance with therapeutic best practices. The recent emphasis on improving quality and patient safety through the incorporation of electronic health records as supported by Leapfrog and other agencies has encouraged advancements in the use of CDSS tools that leverage the capabilities of stand-alone electronic health records. CDSS are of particular interest in the PICU where rapid decision-making benefits from tools that can improve patient safety. CDSS have been described in the PICU with varying effects on healthcare outcomes. A growing consensus indicates that the success of such interventions depends as much or more on how they are implemented and used in such complex environments as on their programming. In the current review, the types and features of various CDSS tools and the supporting evidence are discussed. Factors such as liability, human factors engineering, alert fatigue, and audit trails are also covered. CONCLUSION: CDSS have the potential to improve clinical practice in PICU settings. Care should be taken when selecting and implementing such systems to achieve the goal of improved clinical practice while avoiding potential adverse impacts sometimes associated with the implementation of new technologies in complex healthcare settings.

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Crossref · 10.1097/pcc.0b013e3181936b23

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  • A good fit, or perceived fit, between e-health systems and workflows, and systems positively influencing workplace efficiency, facilitates use.

    “When there is a good fit, or perceived fit, between e-health systems and workflows, and when systems positively influence workplace efficiency, this facilitates use [15, 40, 41].”

    From Factors that influence the implementation of e-health: a systematic review of systematic reviews (an update) (2016) · cites this paper as [40]

  • The work of planning includes delineation of roles and responsibilities, securing time for system selection and procurement, evaluating concomitant policy and process changes, needs assessment and analysis, development of a business plan, early identification and engagement of champions, involving end users, establishing a guiding philosophy, testing organisational readiness, development of incent

    “The work of planning includes the delineation of roles and responsibilities [43], securing time to invest system selection and procurement [18], evaluating other concomitant policy and process changes [40], needs assessment and analysis, development of a business plan [44], early identification and engagement of champions [31], involving end users [16, 27, 41, 51], establishing a guiding”

    From Factors that influence the implementation of e-health: a systematic review of systematic reviews (an update) (2016) · cites this paper as [40]

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Authors
Mack, E. H., Wheeler, D. S., & Embi, P. J.
Affiliations
Cincinnati Children's Hospital Medical Center (US)
ORCID
Venue
Pediatric Critical Care Medicine
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2009-01
Volume
10
Issue
1
Pages
23-28
ISSN
1529-7535 (ISSN-L)
DOI
10.1097/pcc.0b013e3181936b23
OpenAlex
W2053394721
Cited by
76
References
50
Citations by year
2026: 1 · 2025: 1 · 2024: 1 · 2023: 5 · 2022: 5 · 2021: 5 · 2020: 3 · 2019: 3 · 2018: 4 · 2017: 5 · 2016: 3 · 2015: 2 · 2014: 8 · 2013: 9 · 2012: 4
FWCI
1.02
Type
journal article
Language
en
Open access
closed
Locations
  • Pediatric Critical Care Medicine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
Keywords
clinical decision support systems, pediatric intensive care unit, electronic health records, patient safety, alarm fatigue, human factors engineering, audit trail, clinical practice improvement, liability
MeSH terms
Child, Child, Preschool, Female, Humans, Infant, Male, Quality Control, Sensitivity and Specificity, Intensive Care Units, Pediatric, Medical Records Systems, Computerized, Critical Illness, Outcome Assessment, Health Care, Disease Management, Decision Support Systems, Clinical

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