Cited by 156Electronic Health Records SystemsArtificial Intelligence in Healthcare and EducationTechnology and Human Factors in Education and Health

Clinical decision support capabilities of commercially-available clinical information systems

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Wright, A., Sittig, D. F., Ash, J. S., Sharma, S., Pang, J. E., Middleton, B.·2009·Journal of the American Medical Informatics Association

Abstract

Background The most effective decision support systems are integrated with clinical information systems, such as inpatient and outpatient electronic health records (EHRs) and computerized provider order entry (CPOE) systems. Purpose The goal of this project was to describe and quantify the results of a study of decision support capabilities in Certification Commission for Health Information Technology (CCHIT) certified electronic health record systems. Methods The authors conducted a series of interviews with representatives of nine commercially available clinical information systems, evaluating their capabilities against 42 different clinical decision support features. Results Six of the nine reviewed systems offered all the applicable event-driven, action-oriented, real-time clinical decision support triggers required for initiating clinical decision support interventions. Five of the nine systems could access all the patient-specific data items identified as necessary. Six of the nine systems supported all the intervention types identified as necessary to allow clinical information systems to tailor their interventions based on the severity of the clinical situation and the user's workflow. Only one system supported all the offered choices identified as key to allowing physicians to take action directly from within the alert. Discussion The principal finding relates to system-by-system variability. The best system in our analysis had only a single missing feature (from 42…

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Crossref · 10.1197/jamia.m3111

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  • A large 2015 survey found that 95% of respondents had implemented drug-allergy, drug-drug, or drug-laboratory interaction alerts.

    “CDS alerts are included in all major commercial electronic health records (EHRs); a large 2015 survey found that 95% of respondents had implemented drug–allergy, drug–drug, or drug–laboratory interaction alerts.8”
  • CDS alerts are included in all major commercial electronic health records (EHRs).

    “CDS alerts are included in all major commercial electronic health records (EHRs); a large 2015 survey found that 95% of respondents had implemented drug–allergy, drug–drug, or drug–laboratory interaction alerts.8”

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Authors
Wright, A., Sittig, D. F., Ash, J. S., Sharma, S., Pang, J. E., & Middleton, B.
Affiliations
  • Brigham and Women's Hospital (US)
  • Memorial Hermann (US)
  • Oregon Health & Science University (US)
Corresponding author
Wright, A.
Venue
Journal of the American Medical Informatics Association
Published
2009-09-01
Volume
16
Issue
5
Pages
637-644
ISSN
  • 1067-5027 (ISSN-L)
  • 1527-974X
OpenAlex
W2138993334
Cited by
156
References
1
Citations by year
2026: 6 · 2025: 7 · 2024: 3 · 2023: 7 · 2022: 6 · 2021: 5 · 2020: 7 · 2019: 12 · 2018: 11 · 2017: 3 · 2016: 9 · 2015: 13 · 2014: 8 · 2013: 22 · 2012: 6
FWCI
26.06
Type
journal article
Language
en
Open access
Locations
  • Journal of the American Medical Informatics Association (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • Digital Commons-TMC (Texas Medical Center) (submittedVersion)
Funders
  • U.S. Public Health Service (HHHSA 29020080010)
  • U.S. National Library of Medicine (R56LM006942, R56-LM006942-07A1)
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 › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
Keywords
clinical decision support, electronic health records, computerized physician order entry, clinical information systems, alert response, system variability
MeSH terms
Humans, Software Design, Technology Assessment, Biomedical, United States, Decision Support Systems, Clinical

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