Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2023 May 29:2023:8550905.
doi: 10.1155/2023/8550905. eCollection 2023.

The Application of Knowledge-Based Clinical Decision Support Systems to Enhance Adherence to Evidence-Based Medicine in Chronic Disease

Marsa Gholamzadeh  1   2 , Hamidreza Abtahi  3 , Reza Safdari  4
Affiliations
Review

The Application of Knowledge-Based Clinical Decision Support Systems to Enhance Adherence to Evidence-Based Medicine in Chronic Disease

Marsa Gholamzadeh et al. J Healthc Eng. .

Abstract

Among the technology-based solutions, clinical decision support systems (CDSSs) have the ability to keep up with clinicians with the latest evidence in a smart way. Hence, the main objective of our study was to investigate the applicability and characteristics of CDSSs regarding chronic disease. The Web of Science, Scopus, OVID, and PubMed databases were searched using keywords from January 2000 to February 2023. The review was completed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Then, an analysis was done to determine the characteristics and applicability of CDSSs. The quality of the appraisal was assessed using the Mixed Methods Appraisal Tool checklist (MMAT). A systematic database search yielded 206 citations. Eventually, 38 articles from sixteen countries met the inclusion criteria and were accepted for final analysis. The main approaches of all studies can be classified into adherence to evidence-based medicine (84.2%), early and accurate diagnosis (81.6%), identifying high-risk patients (50%), preventing medical errors (47.4%), providing up-to-date information to healthcare providers (36.8%), providing patient care remotely (21.1%), and standardizing care (71.1%). The most common features among the knowledge-based CDSSs included providing guidance and advice for physicians (92.11%), generating patient-specific recommendations (84.21%), integrating into electronic medical records (60.53%), and using alerts or reminders (60.53%). Among thirteen different methods to translate the knowledge of evidence into machine-interpretable knowledge, 34.21% of studies utilized the rule-based logic technique while 26.32% of studies used rule-based decision tree modeling. For CDSS development and translating knowledge, diverse methods and techniques were applied. Therefore, the development of a standard framework for the development of knowledge-based decision support systems should be considered by informaticians.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no conflicts of interest.

Figures

Figure 1
Figure 1
The flow diagram of the screening process based on the PRISMA method.
Figure 2
Figure 2
The distribution of studies on the map of the world.
Figure 3
Figure 3
The frequency of the main approaches of developed knowledge-based CDSSs.
Figure 4
Figure 4
The features and capabilities of knowledge-based CDSSs.
Figure 5
Figure 5
Effectiveness of applied methods based on their users.
Figure 6
Figure 6
The general model of knowledge-based CDSS.
See this image and copyright information in PMC

References

    1. Hisham R., Ng C. J., Liew S. M., et al. Development and validation of the Evidence Based Medicine Questionnaire (EBMQ) to assess doctors’ knowledge, practice and barriers regarding the implementation of evidence-based medicine in primary care. BMC Family Practice . 2018;19(1) doi: 10.1186/s12875-018-0779-5. - DOI - PMC - PubMed
    1. Sutton R. T., Pincock D., Baumgart D. C., Sadowski D. C., Fedorak R. N., Kroeker K. I. An overview of clinical decision support systems: benefits, risks, and strategies for success. Npj Digital Medicine . 2020;3(1) doi: 10.1038/s41746-020-0221-y. - DOI - PMC - PubMed
    1. Hisham R., Ng C. J., Liew S. M., Hamzah N., Ho G. J. Why is there variation in the practice of evidence-based medicine in primary care? A qualitative study. BMJ Open . 2016;6(3) doi: 10.1136/bmjopen-2015-010565. - DOI - PMC - PubMed
    1. Ulvenes L. V., Aasland O., Nylenna M., Kristiansen I. S. Norwegian physicians’ knowledge of and opinions about evidence-based medicine: cross-sectional study. PLoS One . 2009;4(11) doi: 10.1371/journal.pone.0007828. - DOI - PMC - PubMed
    1. Masic I., Miokovic M., Muhamedagic B. Evidence based medicine - new approaches and challenges. Acta Informatica Medica . 2008;16(4):219–225. doi: 10.5455/aim.2008.16.219-225. - DOI - PMC - PubMed

Publication types

LinkOut - more resources