Electronic Trial Banks: A Complementary Method for Reporting Randomized Trials

Sim, Ida; Owens, Douglas K; Lavori, Philip W.; Rennels, Glenn D.

doi:10.1177/0272989x0002000408

Cited by 39 publications

(32 citation statements)

References 75 publications

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“…The Trial Bank project is a collaboration with the Annals of Internal Medicine and JAMA to capture the design and results of randomized trials directly into structured knowledge bases 17 and is a first step toward the transformation of text-based literature into a shared, machine-interpretable resource for evidence-adaptive CDSSs.…”

Section: Literature-based Evidencementioning

confidence: 99%

Clinical Decision Support Systems for the Practice of Evidence-based Medicine

Sim

Gorman

Greenes

et al. 2001

Journal of the American Medical Informatics Association

562

353

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Section: Literature-based Evidencementioning

confidence: 99%

Clinical Decision Support Systems for the Practice of Evidence-based Medicine

Sim

Gorman

Greenes

et al. 2001

Journal of the American Medical Informatics Association

562

353

View full text Add to dashboard Cite

show abstract

“…22 An additional initiative, the Trial Bank Project proof of concept, was undertaken in collaboration with JAMA and Annals of Internal Medicine to enter the design, methods, and results of randomized controlled trials into standardized ''trial banks'' (http://rctbank.ucsf.edu/); a similar Global Trial Bank is under development with the support of the American Medical Informatics Association (http://www.amia.org/gtb/). 23 Without better processes to synthesize new knowledge from clinical research, ensure it is relevant to the EM community, and then transfer it to clinicians and ED informaticians in a timely and usable format, the impact of CDSSs on care delivery will remain limited.…”

Section: Recommendationmentioning

confidence: 99%

Informatics and Knowledge Translation

Bullard

Emond

Graham

et al. 2007

Academic Emergency Medicine

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To ensure that the benefits of knowledge translation synthesis are accessible to care providers at the point of decision-making, fast, efficient, usable clinical information systems are required. Medical informatics appears to hold the greatest promise to be able to create systems with the necessary capacity and functionality. Emergency medicine needs to be actively engaged at all levels of the process. This includes driving the development and filtering of emergency-specific synopses and summaries. It requires advocating for hardware and software that suit the needs of the emergency department environment. It is increasingly important to educate and participate on committees with funders and policy-makers to ensure they support this growing evolution. To determine the outcome of these initiatives, careful evaluation is required to inform the discussion. End-users need to be actively involved in the development and usability testing of clinical information retrieval technology and clinical decision-support systems and make certain relevant best evidence is readily accessible and formatted to meet the needs of the working emergency physician. The integration of knowledge translation into clinical practice, and the impact of delivering electronic clinical decision-support, requires methodologically sound studies to confirm or refute its benefits and guide future development of medical informatics.

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“…Despite its importance, gray literature is difficult to obtain and is thus included in only 33% of systematic reviews (McAuley et al, 2000). Researchers have established trial repositories to ease the identification of gray literature, such as TrialBank (Sim, Owens, Lavori, & Rennels, 2000) and the Cochrane Central Register of Controlled Trials .…”

Section: Information Related To the Medical Conditionmentioning

confidence: 99%

Collaborative information synthesis I: A model of information behaviors of scientists in medicine and public health

Blake

Pratt

2006

J. Am. Soc. Inf. Sci.

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Scientists engage in the discovery process more than any other user population, yet their day-to-day activities are often elusive. One activity that consumes much of a scientist's time is developing models that balance contradictory and redundant evidence. Driven by our desire to understand the information behaviors of this important user group, and the behaviors of scientific discovery in general, we conducted an observational study of academic research scientists as they resolved different experimental results reported in the biomedical literature. This article is the first of two that reports our findings. In this article, we introduce the Collaborative Information Synthesis (CIS) model that reflects the salient information behaviors that we observed. The CIS model emerges from a rich collection of qualitative data including interviews, electronic recordings of meetings, meeting minutes, e-mail communications, and extraction worksheets. Our findings suggest that scientists provide two information constructs: a hypothesis projection and context information. They also engage in four critical tasks: retrieval, extraction, verification, and analysis. The findings also suggest that science is not an individual but rather a collaborative activity and that scientists use the results of one analysis to inform new analyses. In Part 2, we compare and contrast existing information and cognitive models that have inadvertently reported synthesis, and then provide five recommendations that will enable designers to build information systems that support the important synthesis activity. IntroductionScientists engage in the discovery process more than any other user population, yet their day-to-day activities are often elusive. Even a scientist who actively makes discoveries in one discipline can find the activities conducted in a related field a mystery. Regardless of their specific discipline, the role of a good scientist is to develop a model of the world that accurately explains the available evidence. The development of accurate models often requires that a scientist resolve conflicting evidence.One activity that consumes much of a scientists' time is synthesis, "the dialectic combination of thesis and antithesis into a higher stage of truth" (Merriam-Webster's Collegiate Dictionary, 2004). This dictionary definition reflects the alternative viewpoints that often occur when multiple empirical studies explore the same phenomena. The synthesis activity results in an overall finding-a higher stage of truthwhich scientists achieve by resolving conflicting evidence. Thus, the synthesis activity requires accurately weighing a body of evidence that includes contradictions (when the study results differ) and redundancies (when study results concur) that are inevitable when multiple studies explore the same natural phenomena. In this article, we consider synthesis activities that involve evidence reported in existing literature rather than synthesis activities that require additional data collection through experimentation.New te...

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Electronic Trial Banks: A Complementary Method for Reporting Randomized Trials

Cited by 39 publications

References 75 publications

Clinical Decision Support Systems for the Practice of Evidence-based Medicine

Clinical Decision Support Systems for the Practice of Evidence-based Medicine

Informatics and Knowledge Translation

Collaborative information synthesis I: A model of information behaviors of scientists in medicine and public health

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