Cost‐benefit analysis of implementing a pediatric early warning system at a pediatric oncology hospital in a low‐middle income country

Cancer ◽  
2019 ◽  
Vol 125 (22) ◽  
pp. 4052-4058 ◽  
Author(s):  
Asya Agulnik ◽  
Federico Antillon‐Klussmann ◽  
Dora Judith Soberanis Vasquez ◽  
Rosa Arango ◽  
Elmer Moran ◽  
...  
2020 ◽  
Vol 47 ◽  
pp. 101534 ◽  
Author(s):  
Rajesh Kumar Rai ◽  
Marc J.C. van den Homberg ◽  
Gopal Prasad Ghimire ◽  
Colin McQuistan

Cancer ◽  
2017 ◽  
Vol 123 (24) ◽  
pp. 4903-4913 ◽  
Author(s):  
Asya Agulnik ◽  
Alejandra Méndez Aceituno ◽  
Lupe Nataly Mora Robles ◽  
Peter W. Forbes ◽  
Dora Judith Soberanis Vasquez ◽  
...  

Landslides ◽  
2018 ◽  
Vol 15 (8) ◽  
pp. 1631-1644 ◽  
Author(s):  
N. Dixon ◽  
A. Smith ◽  
J. A. Flint ◽  
R. Khanna ◽  
B. Clark ◽  
...  

2018 ◽  
Vol 3 (2) ◽  
pp. e065
Author(s):  
Asya Agulnik ◽  
Sherry Johnson ◽  
Regina Wilkes ◽  
Lane Faughnan ◽  
Angela Carrillo ◽  
...  

2020 ◽  
Vol 9 (1) ◽  
pp. 22-24
Author(s):  
Paul Malherbe

Around the world, especially in low- and middle-income countries, national regulatory authorities are struggling with registration backlogs and the affordability of medicines. This paper draws on the example of cancer biosimilars in South Africa to illustrate how non-governmental organizations can help regulatory authorities decide which registration applications to prioritize by providing information on clinical need, cost-benefit analysis and insight into the potential for cost reduction through biosimilar competition.


Cancer ◽  
2017 ◽  
Vol 123 (15) ◽  
pp. 2965-2974 ◽  
Author(s):  
Asya Agulnik ◽  
Lupe Nataly Mora Robles ◽  
Peter W. Forbes ◽  
Doris Judith Soberanis Vasquez ◽  
Ricardo Mack ◽  
...  

2018 ◽  
Vol 46 (1) ◽  
pp. 631-631 ◽  
Author(s):  
Asya Agulnik ◽  
Sherry Johnson ◽  
Regina Wilkes ◽  
Lane Faughnan ◽  
Angela Carrillo ◽  
...  

2012 ◽  
Vol 40 (5) ◽  
pp. e186
Author(s):  
Kyle Johnson ◽  
Miriam Gonzalez ◽  
Mario Melgar ◽  
Maria Mercedes Somarriba ◽  
Federico Antillon-Klussmann ◽  
...  

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