scholarly journals Improving empirical antibiotic treatment using TREAT, a computerized decision support system: cluster randomized trial

2006 ◽  
Vol 58 (6) ◽  
pp. 1238-1245 ◽  
Author(s):  
Mical Paul ◽  
Steen Andreassen ◽  
Evelina Tacconelli ◽  
Anders D. Nielsen ◽  
Nadja Almanasreh ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Randomized Trial ◽  
Antibiotic Treatment ◽  
Support System ◽  
Cluster Randomized Trial ◽  
Computerized Decision Support ◽  
Empirical Antibiotic Treatment ◽  
Cluster Randomized

scholarly journals Effective Antimicrobial StewaRdship StrategIES (ARIES): Cluster Randomized Trial of Computerized Decision Support System and Prospective Review and Feedback

2020 ◽  
Vol 7 (7) ◽  
Author(s):  
Shi Thong Heng ◽  
Joshua Wong ◽  
Barnaby Young ◽  
Hui Lin Tay ◽  
Sock Hoon Tan ◽  
...  
Keyword(s):  
Decision Support ◽  
Length Of Stay ◽  
Decision Support System ◽  
Antimicrobial Stewardship ◽  
Support System ◽  
Broad Spectrum ◽  
Computerized Decision Support ◽  
Hospitalization Cost ◽  
Antibiotic Duration ◽  
Cluster Randomized

Abstract Background Prospective review and feedback (PRF) of antibiotic prescriptions and compulsory computerized decision support system (CDSS) are 2 strategies of antimicrobial stewardship. There are limited studies investigating their combined effects. We hypothesized that the use of on-demand (voluntary) CDSS would achieve similar patient outcomes compared with automatically triggered (compulsory) CDSS whenever broad-spectrum antibiotics are ordered. Methods A parallel-group, 1:1 block cluster randomized crossover study was conducted in 32 medical and surgical wards from March to August 2017. CDSS use for piperacillin-tazobactam or carbapenem in the intervention clusters was at the demand of the doctor, while in the control clusters CDSS use was compulsory. PRF was continued for both arms. The primary outcome was 30-day mortality. Results Six hundred forty-one and 616 patients were randomized to voluntary and compulsory CDSS, respectively. There were no differences in 30-day mortality (hazard ratio [HR], 0.87; 95% CI, 0.67–1.12), re-infection and re-admission rates, antibiotic duration, length of stay, or hospitalization cost. The proportion of patients receiving PRF recommendations was not significantly lower in the voluntary CDSS arm (62 [10%] vs 81 [13%]; P = .05). Appropriate indication of antibiotics was high in both arms (351/448 [78%] vs 330/433 [74%]; P = .18). However, in geriatric medicine patients where antibiotic appropriateness was <50%, prescription via compulsory CDSS resulted in a shorter length of stay and lower hospitalization cost. Conclusions Voluntary broad-spectrum antibiotics with PRF via CDSS did not result in differing clinical outcomes, antibiotic duration, or length of stay. However, in the setting of low antibiotic appropriateness, compulsory CDSS may be beneficial.

scholarly journals Improving empirical antibiotic treatment: prospective, nonintervention testing of a decision support system

1997 ◽  
Vol 242 (5) ◽  
pp. 395-400 ◽  
Author(s):  
L. Leibovici ◽  
V. Gitelman ◽  
Y. Yehezkelli ◽  
O. Poznanski ◽  
G. Milo ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Antibiotic Treatment ◽  
Support System ◽  
Empirical Antibiotic Treatment

859-P: Impact of a Prediabetes Clinical Decision Support System on CV Risk Factor Control in Primary Care: Randomized Trial

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 859-P
Author(s):  
JAY R. DESAI ◽  
A. LAUREN CRAIN ◽  
DANIEL SAMAN ◽  
JOANN M. SPERL-HILLEN ◽  
CLAYTON ALLEN ◽  
...  
Keyword(s):  
Primary Care ◽  
Risk Factor ◽  
Decision Support ◽  
Decision Support System ◽  
Randomized Trial ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Risk Factor Control

scholarly journals Penerapan Metode Rank Order Centroid dan Additive Ratio Assessment Pada Aplikasi Rekomendasi Supplier

2021 ◽  
Vol 5 (1) ◽  
pp. 31-40
Author(s):  
Ronny Addenan ◽  
◽  
Wilda Susanti ◽  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Selection Process ◽  
Rank Order ◽  
Spare Parts ◽  
Computerized Decision Support ◽  
K Value ◽  
Long Time ◽  
The Right

PT.Yanmarindo Perkasa is a company in the sale of diesel engines, generators, tooling tools and engine spare parts. Many suppliers want to distribute their goods through PT.Yanmarindo Perkasa, thus demanding the company to choose the right supplier, in order to ensure the smooth fulfillment of stock items. The process of selecting suppliers is still done manually with criteria limited to quantitative criteria, so that the process takes a long time and the results are not precise. The purpose of this study is to build a decision support system for supplier recommendations quickly and precisely in meeting the company's needs. The supplier selection process uses the Rank-Order Centroid (ROC) method in weighting the criteria and the Additive Ratio Assessment (ARAS) for ranking. ARAS value obtained is the K value that is ranked to get the best supplier by using a computerized decision support system. The application of these two methods can speed up the results of decisions, does not take a long time and the results obtained are also maximum.

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