Literature DB >> 23958964

Features of computerized clinical decision support systems supportive of nursing practice: a literature review.

Seonah Lee1.   

Abstract

This study aimed to organize the system features of decision support technologies targeted at nursing practice into assessment, problem identification, care plans, implementation, and outcome evaluation. It also aimed to identify the range of the five stage-related sequential decision supports that computerized clinical decision support systems provided. MEDLINE, CINAHL, and EMBASE were searched. A total of 27 studies were reviewed. The system features collected represented the characteristics of each category from patient assessment to outcome evaluation. Several features were common across the reviewed systems. For the sequential decision support, all of the reviewed systems provided decision support in sequence for patient assessment and care plans. Fewer than half of the systems included problem identification. There were only three systems operating in an implementation stage and four systems in outcome evaluation. Consequently, the key steps for sequential decision support functions were initial patient assessment, problem identification, care plan, and outcome evaluation. Providing decision support in such a full scope will effectively help nurses' clinical decision making. By organizing the system features, a comprehensive picture of nursing practice-oriented computerized decision support systems was obtained; however, the development of a guideline for better systems should go beyond the scope of a literature review.

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Year:  2013        PMID: 23958964     DOI: 10.1097/01.NCN.0000432127.99644.25

Source DB:  PubMed          Journal:  Comput Inform Nurs        ISSN: 1538-2931            Impact factor:   1.985


  8 in total

Review 1.  A 2014 medical informatics perspective on clinical decision support systems: do we hit the ceiling of effectiveness?

Authors:  J Bouaud; J-B Lamy
Journal:  Yearb Med Inform       Date:  2014-08-15

2.  Evaluation of User-Interface Alert Displays for Clinical Decision Support Systems for Sepsis.

Authors:  Devida Long; Muge Capan; Susan Mascioli; Danielle Weldon; Ryan Arnold; Kristen Miller
Journal:  Crit Care Nurse       Date:  2018-08       Impact factor: 1.708

Review 3.  Interface, information, interaction: a narrative review of design and functional requirements for clinical decision support.

Authors:  Kristen Miller; Danielle Mosby; Muge Capan; Rebecca Kowalski; Raj Ratwani; Yaman Noaiseh; Rachel Kraft; Sanford Schwartz; William S Weintraub; Ryan Arnold
Journal:  J Am Med Inform Assoc       Date:  2018-05-01       Impact factor: 4.497

4.  Automation in nursing decision support systems: A systematic review of effects on decision making, care delivery, and patient outcomes.

Authors:  Saba Akbar; David Lyell; Farah Magrabi
Journal:  J Am Med Inform Assoc       Date:  2021-10-12       Impact factor: 7.942

Review 5.  The design of decisions: Matching clinical decision support recommendations to Nielsen's design heuristics.

Authors:  Kristen Miller; Muge Capan; Danielle Weldon; Yaman Noaiseh; Rebecca Kowalski; Rachel Kraft; Sanford Schwartz; William S Weintraub; Ryan Arnold
Journal:  Int J Med Inform       Date:  2018-05-21       Impact factor: 4.046

6.  The development of a nursing subset of patient problems to support interoperability.

Authors:  R A M M Kieft; E M Vreeke; E M de Groot; P A Volkert; A L Francke; D M J Delnoij
Journal:  BMC Med Inform Decis Mak       Date:  2017-12-04       Impact factor: 2.796

7.  Merits, features, and desiderata to be considered when developing electronic health records with embedded clinical decision support systems in Palestinian hospitals: a consensus study.

Authors:  Ramzi Shawahna
Journal:  BMC Med Inform Decis Mak       Date:  2019-11-08       Impact factor: 2.796

8.  Clinical decision support for intervention reduction in neonatal patients: A usability assessment.

Authors:  Patrice D Tremoulet
Journal:  Digit Health       Date:  2022-08-07
  8 in total

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