The Application of Knowledge-Based Clinical Decision Support Systems to Enhance Adherence to Evidence-Based Medicine in Chronic Disease.
Journal
Journal of healthcare engineering
ISSN: 2040-2309
Titre abrégé: J Healthc Eng
Pays: England
ID NLM: 101528166
Informations de publication
Date de publication:
2023
2023
Historique:
received:
29
07
2022
revised:
07
02
2023
accepted:
19
02
2023
medline:
9
6
2023
pubmed:
7
6
2023
entrez:
7
6
2023
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 37284487
doi: 10.1155/2023/8550905
pmc: PMC10241579
doi:
Types de publication
Journal Article
Review
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
8550905Informations de copyright
Copyright © 2023 Marsa Gholamzadeh et al.
Déclaration de conflit d'intérêts
The authors declare that they have no conflicts of interest.
Références
J Telemed Telecare. 2021 May;27(4):217-230
pubmed: 31438761
J Am Med Inform Assoc. 2013 Jul-Aug;20(4):749-57
pubmed: 23564631
Implement Sci. 2014 Nov 23;9:172
pubmed: 25417046
Chest. 2011 Jul;140(1):198-204
pubmed: 21193532
Lancet. 2018 Sep 22;392(10152):1072-1088
pubmed: 30264707
Int J Nurs Stud. 2012 Jan;49(1):47-53
pubmed: 21835406
J Transl Med. 2014 Nov 28;12 Suppl 2:S9
pubmed: 25471545
Sensors (Basel). 2015 Aug 28;15(9):21294-314
pubmed: 26343669
BMC Med Inform Decis Mak. 2018 May 29;18(1):31
pubmed: 29843767
JMIR Mhealth Uhealth. 2021 Feb 19;9(2):e23737
pubmed: 33605886
Implement Sci. 2013 Feb 13;8:18
pubmed: 23406398
PLoS One. 2009 Nov 13;4(11):e7828
pubmed: 19915708
JAMA Netw Open. 2019 Dec 2;2(12):e1917094
pubmed: 31825499
J Headache Pain. 2014 Jun 16;15:40
pubmed: 24934331
Clin Pediatr (Phila). 2017 Jun;56(6):571-578
pubmed: 27798385
Stud Health Technol Inform. 2022 Aug 17;296:1-8
pubmed: 36073482
JMIR Med Inform. 2018 Apr 18;6(2):e24
pubmed: 29669706
Interact J Med Res. 2023 Jan 30;12:e42540
pubmed: 36645840
JAMA Pediatr. 2017 Apr 1;171(4):327-334
pubmed: 28192551
Int J Health Care Qual Assur. 2014;27(8):707-18
pubmed: 25417376
PLoS One. 2016 Dec 15;11(12):e0167683
pubmed: 27977697
J Family Med Prim Care. 2020 Dec 31;9(12):6078-6084
pubmed: 33681044
BMC Fam Pract. 2019 Dec 6;20(1):171
pubmed: 31810450
Pain Med. 2010 Apr;11(4):575-85
pubmed: 20202142
JMIR Form Res. 2022 Aug 2;6(8):e27990
pubmed: 35916719
NPJ Digit Med. 2020 Feb 6;3:17
pubmed: 32047862
Open Med. 2009;3(3):e123-30
pubmed: 21603045
J Clin Epidemiol. 2012 Nov;65(11):1163-70
pubmed: 22858301
Stud Health Technol Inform. 2017;245:1148-1152
pubmed: 29295282
J Am Med Inform Assoc. 2020 May 1;27(5):726-737
pubmed: 32274495
Healthc Inform Res. 2014 Jul;20(3):173-82
pubmed: 25152830
Acta Inform Med. 2008;16(4):219-25
pubmed: 24109156
Neth Heart J. 2019 Sep;27(9):435-442
pubmed: 31372838
BMC Fam Pract. 2020 Jul 22;21(1):147
pubmed: 32698768
Pancreas. 2020 Nov/Dec;49(10):1276-1282
pubmed: 33122514
J Med Life. 2020 Oct-Dec;13(4):612-623
pubmed: 33456613
BMC Nephrol. 2015 Oct 15;16:163
pubmed: 26471846
BMC Fam Pract. 2018 Jun 23;19(1):98
pubmed: 29935527
BMC Med Inform Decis Mak. 2018 Dec 7;18(Suppl 5):118
pubmed: 30526596
Front Pediatr. 2022 Dec 15;10:1047202
pubmed: 36589162
J Am Med Inform Assoc. 2020 Dec 9;27(12):1968-1976
pubmed: 33120430
NPJ Digit Med. 2020 Aug 27;3:110
pubmed: 32904379
J Am Med Inform Assoc. 2019 Jun 1;26(6):524-536
pubmed: 31087071
Stud Health Technol Inform. 2012;180:492-6
pubmed: 22874239
JAMA Pediatr. 2014 Sep;168(9):815-21
pubmed: 25022724
BMC Med Inform Decis Mak. 2022 Sep 10;22(1):238
pubmed: 36088328
Int J Nurs Knowl. 2017 Jan;28(1):4-12
pubmed: 26011435
J Am Board Fam Med. 2015 May-Jun;28(3):382-93
pubmed: 25957371
Ophthalmol Sci. 2022 Oct 07;3(1):100231
pubmed: 36439697
BMJ Open. 2016 Mar 09;6(3):e010565
pubmed: 26962037
J Am Med Inform Assoc. 2001 Nov-Dec;8(6):527-34
pubmed: 11687560
JMIR Med Inform. 2021 Mar 10;9(3):e13182
pubmed: 33709932
J Diabetes Sci Technol. 2018 Mar;12(2):381-388
pubmed: 28905658
Implement Sci Commun. 2022 Jul 16;3(1):76
pubmed: 35850778
Appl Clin Inform. 2018 Jan;9(1):62-71
pubmed: 29365341
EGEMS (Wash DC). 2018 May 30;6(1):12
pubmed: 30094284