scholarly journals Can evidence-based decision support tools transform antibiotic management? A systematic review and meta-analyses

2020 ◽  
Vol 75 (5) ◽  
pp. 1099-1111 ◽  
Author(s):  
Mah Laka ◽  
Adriana Milazzo ◽  
Tracy Merlin

Abstract Objectives To assess the effectiveness of clinical decision support systems (CDSSs) at reducing unnecessary and suboptimal antibiotic prescribing within different healthcare settings. Methods A systematic review of published studies was undertaken with seven databases from database inception to November 2018. A protocol was developed using the PRISMA-P checklist and study selection criteria were determined prior to performing the search. Critical appraisal of studies was undertaken using relevant tools. Meta-analyses were performed using a random-effects model to determine whether CDSS use affected optimal antibiotic management. Results Fifty-seven studies were identified that reported on CDSS effectiveness. Most were non-randomized studies with low methodological quality. However, randomized controlled trials of moderate methodological quality were available and assessed separately. The meta-analyses indicated that appropriate antibiotic therapy was twice as likely to occur following the implementation of CDSSs (OR 2.28, 95% CI 1.82–2.86, k = 20). The use of CDSSs was also associated with a relative decrease (18%) in mortality (OR 0.82, 95% CI 0.73–0.91, k = 18). CDSS implementation also decreased the overall volume of antibiotic use, length of hospital stay, duration and cost of therapy. The magnitude of the effect did vary by study design, but the direction of the effect was consistent in favouring CDSSs. Conclusions Decision support tools can be effective to improve antibiotic prescribing, although there is limited evidence available on use in primary care. Our findings suggest that a focus on system requirements and implementation processes would improve CDSS uptake and provide more definitive benefits for antibiotic stewardship.

2019 ◽  
Vol 69 (689) ◽  
pp. e809-e818 ◽  
Author(s):  
Sophie Chima ◽  
Jeanette C Reece ◽  
Kristi Milley ◽  
Shakira Milton ◽  
Jennifer G McIntosh ◽  
...  

BackgroundThe diagnosis of cancer in primary care is complex and challenging. Electronic clinical decision support tools (eCDSTs) have been proposed as an approach to improve GP decision making, but no systematic review has examined their role in cancer diagnosis.AimTo investigate whether eCDSTs improve diagnostic decision making for cancer in primary care and to determine which elements influence successful implementation.Design and settingA systematic review of relevant studies conducted worldwide and published in English between 1 January 1998 and 31 December 2018.MethodPreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials were searched, and a consultation of reference lists and citation tracking was carried out. Exclusion criteria included the absence of eCDSTs used in asymptomatic populations, and studies that did not involve support delivered to the GP. The most relevant Joanna Briggs Institute Critical Appraisal Checklists were applied according to study design of the included paper.ResultsOf the nine studies included, three showed improvements in decision making for cancer diagnosis, three demonstrated positive effects on secondary clinical or health service outcomes such as prescribing, quality of referrals, or cost-effectiveness, and one study found a reduction in time to cancer diagnosis. Barriers to implementation included trust, the compatibility of eCDST recommendations with the GP’s role as a gatekeeper, and impact on workflow.ConclusioneCDSTs have the capacity to improve decision making for a cancer diagnosis, but the optimal mode of delivery remains unclear. Although such tools could assist GPs in the future, further well-designed trials of all eCDSTs are needed to determine their cost-effectiveness and the most appropriate implementation methods.


2019 ◽  
Vol 41 (3) ◽  
pp. 552-581 ◽  
Author(s):  
Eduardo Carracedo-Martinez ◽  
Christian Gonzalez-Gonzalez ◽  
Antonio Teixeira-Rodrigues ◽  
Jesus Prego-Dominguez ◽  
Bahi Takkouche ◽  
...  

10.2196/12448 ◽  
2018 ◽  
Vol 20 (12) ◽  
pp. e12448 ◽  
Author(s):  
Ching Lam ◽  
Edward Meinert ◽  
Abrar Alturkistani ◽  
Alison R Carter ◽  
Jeffrey Karp ◽  
...  

2018 ◽  
Author(s):  
Ching Lam ◽  
Edward Meinert ◽  
Abrar Alturkistani ◽  
Alison Carter ◽  
Jeffery M. Karp ◽  
...  

2019 ◽  
Vol 45 (4) ◽  
pp. 386-393 ◽  
Author(s):  
Valle Coronado-Vázquez ◽  
Juan Gómez-Salgado ◽  
Javier Cerezo-Espinosa de los Monteros ◽  
Miren Arantzazu García-Colinas

Author(s):  
Mah Laka ◽  
Adriana Milazzo ◽  
Tracy Merlin

The study evaluated individual and setting-specific factors that moderate clinicians’ perception regarding use of clinical decision support systems (CDSS) for antibiotic management. A cross-sectional online survey examined clinicians’ perceptions about CDSS implementation for antibiotic management in Australia. Multivariable logistic regression determined the association between drivers of CDSS adoption and different moderators. Clinical experience, CDSS use and care setting were important predictors of clinicians’ perception concerning CDSS adoption. Compared to nonusers, CDSS users were less likely to lack confidence in CDSS (OR = 0.63, 95%, CI = 0.32, 0.94) and consider it a threat to professional autonomy (OR = 0.47, 95%, CI = 0.08, 0.83). Conversely, there was higher likelihood in experienced clinicians (>20 years) to distrust CDSS (OR = 1.58, 95%, CI = 1.08, 2.23) due to fear of comprising their clinical judgement (OR = 1.68, 95%, CI = 1.27, 2.85). In primary care, clinicians were more likely to perceive time constraints (OR = 1.96, 95%, CI = 1.04, 3.70) and patient preference (OR = 1.84, 95%, CI = 1.19, 2.78) as barriers to CDSS adoption for antibiotic prescribing. Our findings provide differentiated understanding of the CDSS implementation landscape by identifying different individual, organisational and system-level factors that influence system adoption. The individual and setting characteristics can help understand the variability in CDSS adoption for antibiotic management in different clinicians.


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