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Future research and methodological approaches

This supplement has explored the evidence for benefits from the participation of healthcare institutions and their patients in clinical research. The questions have been clarified. There is some encouragement that research active healthcare institutions may deliver improved outcomes compared to less...

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Hauptverfasser: Pater, Joseph (VerfasserIn) , Rochon, Justine (VerfasserIn) , Parmar, M. (VerfasserIn) , Selby, P. (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 2011
In: Annals of oncology
Year: 2011, Jahrgang: 22, Pages: vii57-vii61
ISSN:1569-8041
DOI:10.1093/annonc/mdr428
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1093/annonc/mdr428
Volltext
Verfasserangaben:J. Pater, J. Rochon, M. Parmar & P. Selby

MARC

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520 |a This supplement has explored the evidence for benefits from the participation of healthcare institutions and their patients in clinical research. The questions have been clarified. There is some encouragement that research active healthcare institutions may deliver improved outcomes compared to less research-active or research-inactive institutions but there is a pressing need for further research. In this chapter we explore the methodological challenges to evaluating the impact of the process of clinical research on hospitals and other healthcare organizations. The postulated mechanisms by which benefits may be accrued are important drivers of the types of research needed and these are emphasized. Study designs are explored including formal randomized trials, the stepped wedge randomized design, approaches to the design and analysis of observational studies particularly to examine whether a temporal or spatial relationship exists between changes in research activity and patients' outcomes. It is acknowledged that in most future studies the data available will be cross-sectional and observational, and such studies are susceptible to many types of bias. The importance of identifying and addressing such biases in multivariate analysis is discussed and examples of successful studies are given. 
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