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All Posts in Category: Landon’s Notes


Translating Academic Research into QualOptima Trigger Algorithms

Triggers as Signals

Isaac Kohane, M.D., Ph.D., Professor & Co-Director of the Center for Biomedical Informatics, Harvard Medical School, explains how health care is missing huge signals by not paying attention. He gives the example of two top hospitals in Boston which had an 18% increase in heart attacks. He likens it to flying a thousand 747’sd1 filled with patients into this mountain of heart attacks, illustrated in the graph below as published in “The Telltale Heart: Population-Based Surveillance Reveals an Association of Robecoxib and Celecoxib with Myocardial Infarction,” PLoS one, Issue 9 (Sept. 2007). Most dramatically, as Dr. Kohane points out in his presentation, Exponential Growth of Bad Medicine, at Exponential Medicine, “not only did no one ever notice it, we actually caused it by giving the drug Vioxx to our patients” (causing cardiotoxicity).

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“Our customers and potential customers, as well as our investors and potential investors, need to understand the significance of Quture’s focus for QualOptima v1.3 – to install it on cloud servers with intense security and massive functionality as a data warehouse. Quture looks forward to announcing our successful completion of this major, demanding and expensive undertaking and sales and marketing that will flow when this installation is completed.”

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The first Note posted was about risk predictive factors, ranging from traditional factors, such as family history or race and ethnicity (which are “phenotype”) patient factors to novel genome and biomarker (“genotype”) factors. Quture’s method of establishing a library of traditional and novel risk factors relies upon a systematic medical literature review, incidence and prevalence analysis of claims databases, and proof of concept analytics in de-identified patient databases.

To understand where Quture is today and how we got to our QualOptima experiential learning platform, think back to 2010 – 2012 and our formal clinical trial at the University 1bof Miami, Miller School of Medicine and Jackson Memorial Hospital. With the leadership of Quture’s Associate Medical Director, Keith A. Candiotti, M.D., we first introduced our risk stratified analytics system to measure clinical performance and outcomes (see Success Stories: University of Miami Clinical Trial). One of the primary risk factors for post-operative nausea and vomiting (PONV) is gender-specific – being a female (a phenotype risk factor). Our data analytics can be used not only to measure performance and outcomes, but as an experiential learning platform to learn from clinical patient-specific experience. For example, the different reactions of men and women to the antiemetic drugs, from different pharmaceutical companies, administered in different combinations, sequencing, and dosages, can be studied to understand how to achieve optimal clinical performance and outcomes. And in our study, we even began with the female gender being more at risk than males.

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At Quture, we have worked in measuring healthcare performance & outcomes since we sponsored the first Dialogues in Obstetrics at the Del Coronado back in the 1980’s. Our first customer in external peer review, Daughters of Charity (now Ascension Health) came to us in a predecessor company. That was back in the days when you handed a chart to a physician and asked him/her a paper record, gave them either a Dictaphone or pad of paper and asked: “Tell me what you think of the care in this case.” As the pioneer of external peer review, we matured that process to a structured and more objective process with a software

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