scholarly journals Real-World Evidence in Healthcare Decision Making: Global Trends and Case Studies From Latin America

2019 ◽  
Vol 22 (6) ◽  
pp. 739-749 ◽  
Author(s):  
Nahila Justo ◽  
Manuel A. Espinoza ◽  
Barbara Ratto ◽  
Martha Nicholson ◽  
Diego Rosselli ◽  
...  
2021 ◽  
Vol 24 ◽  
pp. S194
Author(s):  
L. Costa ◽  
A.L. Hincapie ◽  
R. Gilardino ◽  
B. Tang ◽  
G. Julian ◽  
...  

2021 ◽  
Vol 24 ◽  
pp. S157
Author(s):  
H. Monsanto ◽  
C. Parellada ◽  
J. Orengo ◽  
J.S. Velasco ◽  
Bavel J van ◽  
...  

2020 ◽  
Vol 36 (S1) ◽  
pp. 16-16
Author(s):  
Paola Andrea Rivera-Ramirez ◽  
Fabián Alejandro Fiestas-Saldarriaga

IntroductionIn the absence of direct evidence from randomized controlled trials (RCTs), real-world evidence (RWE) can play an important role in healthcare decision making. As part of a health technology assessment, we assessed the comparative risk of tuberculosis (TB) associated with using infliximab and etanercept in patients with rheumatoid arthritis.MethodsWe performed a systematic literature search using the PubMed database to identify relevant meta-analyses.ResultsWe located two relevant meta-analyses: one based on RCTs and one based on observational studies. Evidence from seven RCTs on infliximab (2,686 patients; 12 TB events) and two RCTs on etanercept (663 patients; 2 TB events) suggested no significant differences in the risk of TB between the two treatments, compared with placebo. In contrast, evidence from ten observational studies that directly compared the two treatments (443,941 patients; 253 TB events) indicated a significantly higher risk of TB with infliximab than with etanercept.ConclusionsAlthough RWE is prone to confounding and bias, in this case it had the advantage of providing direct comparisons with larger sample sizes and longer follow up than evidence from RCTs. As a result, RWE was used to inform decision making on the risk of TB with infliximab and etanercept in patients with rheumatoid arthritis.


2015 ◽  
Vol 18 (7) ◽  
pp. A693 ◽  
Author(s):  
L Degli Esposti ◽  
S Saragoni ◽  
D Sangiorgi ◽  
S Buda ◽  
A Cangini ◽  
...  

2017 ◽  
pp. 1157-1171 ◽  
Author(s):  
Zhecheng Zhu ◽  
Heng Bee Hoon ◽  
Kiok-Liang Teow

Data visualization techniques are widely applied in all kinds of organizations, turning tables of numbers into visualizations for discovery, information communication, and knowledge sharing. Data visualization solutions can be found everywhere in healthcare systems from hospital operations monitoring and patient profiling to demand projection and capacity planning. In this chapter, interactive data visualization techniques are discussed and their applications to various aspects of healthcare systems are explored. Compared to static data visualization techniques, interactive ones allow users to explore the data and find the insights themselves. Four case studies are given to illustrate how interactive data visualization techniques are applied in healthcare: summary and overview, information selection and filtering, patient flow visualization, and geographical and longitudinal analyses. These case studies show that interactive data visualization techniques expand the boundary of data visualization as a pure presentation tool and bring certain analytical capability to support better healthcare decision making.


Author(s):  
Zhecheng Zhu ◽  
Heng Bee Hoon ◽  
Kiok-Liang Teow

Data visualization techniques are widely applied in all kinds of organizations, turning tables of numbers into visualizations for discovery, information communication, and knowledge sharing. Data visualization solutions can be found everywhere in healthcare systems from hospital operations monitoring and patient profiling to demand projection and capacity planning. In this chapter, interactive data visualization techniques are discussed and their applications to various aspects of healthcare systems are explored. Compared to static data visualization techniques, interactive ones allow users to explore the data and find the insights themselves. Four case studies are given to illustrate how interactive data visualization techniques are applied in healthcare: summary and overview, information selection and filtering, patient flow visualization, and geographical and longitudinal analyses. These case studies show that interactive data visualization techniques expand the boundary of data visualization as a pure presentation tool and bring certain analytical capability to support better healthcare decision making.


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