Say What You Do. Do What You Say.
The problem with promotional and marketing materials is that the claims seldom match the reality. That's because when any firm writes marketing materials the objective is to be completely persuasive -- not completely truthful.
DecisionQ believes that the best promotion is true and accurate accounts of your actual successes. Say what you do, and then defend it in front of a tough audience.
To that end we are participants in - and strong supporters of - the academic peer-review and publication process. In order to be chosen to publish your work you must first make a substantial and novel contribution to the body of science and then defend your work to a jury of your scientific and academic peers who will scrutinize your every statement for accuracy and completeness.
If you can get through the process, the publication that results is both substantial and thoroughly vetted so that the reader can rely on the fact that you say what you do and do what you say.
It's a high hurdle to clear and the kind of real marketing we think is worth the investment in time and treasure.
Below is a very small sample of over forty peer reviewed publications and presentations from our work in healthcare and life sciences. Materials from our work in national defense and other industries as well as more of our work in the life sciences are available upon request.
(click on the case studies below to view PDF)
- Assessing Differences Between Realized and Anticipated Gains from Electronic Health Record Adoption. Annual Meeting of the Academy of Management Best Paper Proceedings, August 2009.
- Application of multivariate probabilistic (Bayesian) networks to screening for Chemical Dependency Cases and Estimating Cost. Perspectives in Health Information Management, Fall 2009
- Healthcare Fraud and Abuse. Perspectives in Health Information Management, Fall 2009
Clinical Decision Support
- Development of a clinical decision model for thyroid nodules. BMC Surgery, August 2009
- Development of a Bayesian Classifier for Breast Cancer Risk Stratification: A Feasibility Study. ePlasty Open Access Journal March, 2010
- Bayesian Delta Error Value - A new metric for near real-time error detection. 2006 American Association of Clinical Chemistry.
- Probabilistic (Bayesian) modeling of gene expression in transplant glomerulopathy. Journal of Molecular Diagnostics, September 2010