Zignifica Prototype

We Have Developed a Zignifica Prototype – and We Want to Hear from You

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[/bsg_col][bsg_col size=”7/12″] We are developing Zignifica to make it possible for everyone to get an evaluation of the clinical relevance of a scientific claim in medicine. This development is an ongoing process, and now we have developed the Zignifica Prototype App to test the idea, concept, and presentation.

The Zignifica Prototype App contains more than 100 handpicked scientific papers in the field of pain management and a few in diabetes. We have chosen this limitation to be able to pinpoint what is working, and where we need to make improvements. The full version of Zignifica will, of course, include many other relevant areas in healthcare and medical research like diabetes, cardiovascular diseases, COPD, cholesterol, and much more.

Download the Zignifica Prototype App – test it and help us with feedback



Why do We Need Zignifica?

Studies presented in scientific papers may lack clinical relevance for many reasons. Both the research method, study design and the results may be without relevance in real life care, and thereby compromise the trustworthiness of the study.

Researchers from Stanford University has estimated that 85% of resources spent on clinical research is wasted.

The results in medical papers are of course correct in analyzing the trials data, but that is only an analysis of data collected in that specific study not the answer to the research question. That is why the study design and used method are crucial to providing trustworthy results. Furthermore, has it become a golden standard to report statistical significance, which is a statistical calculation without correlation to clinical significance.

Unfortunately is clinical usefulness or relevance at the point of care not guaranteed by the paper being peer reviewed or published in a high ranking medical journal. 

Critically analyzing medical papers is time-consuming and require education in statistics. We are developing Zignifica to make this analysis, and make it easy to distinguish between clinically relevant and not relevant studies by analyzing both method, design and results in papers presenting data from clinical trials. Using sophisticated Zignifica algorithms results are portrayed as two scores. These scores are combined and converted to a Zignifica grading system going from “A” (highly clinical relevant) to “F” (not clinically relevant). Each Zignifica class include several subgroups enabling detailed information e.g. “Cr: Reduced Clinical Relevance. Clinical Relevant Results, but “Method/Design are weak. Look for studies with better method/design.”