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http://hdl.handle.net/11375/22041
Title: | The Role of Randomized and Non-Randomized Studies in Knowledge Synthesis of Health Interventions. |
Other Titles: | Randomized and Non-Randomized Studies in Health Syntheses |
Authors: | Cuello-Garcia, Carlos Alberto |
Advisor: | Schunemann, Holger |
Department: | Health Research Methodology |
Keywords: | Systematic Reviews;Clinical Trials;Randomized Trials;Clinical Guidelines;GRADE;Evidence Syntheses;Knowledge Syntheses |
Publication Date: | Nov-2017 |
Abstract: | Randomized studies (RS) are considered the best source of evidence for knowledge syntheses (e.g., systematic reviews, health technology assessments, health guidelines, among others) about healthcare interventions. Historically, non-randomized studies (NRS) have been usually discarded from knowledge syntheses of interventions due to their intrinsic risk of bias and confounding, and they are used only when RS are considered unfeasible or unethical to conduct. With better research methods in observational studies and new tools for the evaluation of risk of bias, NRS are more likely to be a helpful source of information when used as replacement, sequential, or complementary evidence. This, together with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach, provide an opportunity for guiding decisions about using RS and NRS in knowledge synthesis and increasing our certainty in a body of evidence. This work aims to improve research synthesis methods by assessing the role and use of RS and NRS in knowledge syntheses using GRADE. This can help health professionals, researchers, guideline developers, and policy-makers build better and more complete healthcare recommendations. |
Description: | PhD thesis assessing the role of non-randomized studies with randomized in evidence syntheses of health interventions. |
URI: | http://hdl.handle.net/11375/22041 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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cuello_carlos_201709_PhD.pdf | PhD thesis | 13.03 MB | Adobe PDF | View/Open |
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