Robotics was a big hit as usual, but at Case, they are now experimenting with Biologically Inspired Robotics. See the video:

Biologically Inspired Unmanned Ground Vehicles from CWRU Biorobotics Lab on Vimeo.

Other interesting exhibits included:

• Research Computing which is developing a high performance cluster for everything from medical imaging to metallurgy and astronomy.
• A Digital Health Management Consultant: Markov Models Made Accessible - making these complex statistical models simple, with a nice demo using health financial data.
• The Center for Statistical Research, Computing, and Collaboration with an emphasis on innovative interdisciplinary research.

Looking forward to working on next year’s showcase.

Two recent examples are beginning to move along this path in utilizing data to develop customized order sets. One is IBM Watson working with Memorial Sloan Kettering Cancer Center. Using its powerful natural language processing (NLP), Watson is able to match patient data including complex genomics with the wide array of order sets available for different types of cancer. ” The medical center has about 2,000 order sets it can pull from when choosing a cancer treatment.” And data on millions of patients. Finding patterns that match requires the speed and logic of the Watson engine.

A second example uses existing medical knowledge and updates it as published and then converts these into order sets for a procedure-based EMR system. With their combination of the knowledge of current practices in tools like Up-To-Date and an EMR called Provation, they are now combining these products to enable the regular updating of order sets in the EMR including integration with comprehensive EMRs. This demonstrates the last mile of clinical decision support and evidence-based medicine. Bringing the latest discoveries to EMR order sets through an integrated solutions.

Looking forward to more solutions that fulfill the vision of the Learning Healthcare System.

Health Informatics: Practical Guide for Healthcare and Information Technology Professionals

The book overall includes a broad variety of chapters reflecting the maturity of health informatics from bioinformatics to clinical informatics. Written as a textbook, it will no doubt serve the growing needs of health informatics programs popping up in every state.

Recommended changes include improving:

• the speed and efficiency of the design,
• launch, and conduct of trials;
• innovation in science and trial design;
• trial prioritization,selection, support, and completion; and
• incentives for patient and physician participation

The full IOM report lays out participation of key stakeholders, particularly patients and physicians. The emphasis on patient participation is strong and reminiscent of the e-Patient White Paper. While the concept of the Lethal Lag Time is not directly mentioned, the overtones can be heard. I recommend this report as key to the future of the conduct of clinical trials including innovative approaches.

• The average time between developing the concept for a study and getting it started is about 2.5 years.
• about 40 percent of all advanced clinical trials sponsored by the Cancer Institute are never completed

One of the recommendations is to reduce the number of cooperative groups and the levels of approval required.

In a related post on The Medical Quack, there is discussion of the clinical trial experience for the patient with an excellent video below.

In both cases what I hope we all come to realize soon is the lethal lag time – a articulate by e-patient White Paper – these long lead time for studies can prove lethal for those waiting for new treatments.

One outstanding story related to a patient’s right to their own data is from a Hepatitis C trial in which the subjects were not allowed to receive information on their viral load during the study as a way of discouraging drop outs. However, this in itself seems unethical in that the patient would not know whether the treatment was effective or ineffective and whether their disease was progressing. I hope that Institutional Review Boards would not approve such a procedure for trials involving serious illness. Much of the book looks at the issues with placebo controlled studies and blinding – it raises many questions which are yet to be resolved by medical scientist and bioethicists.

I would recommend this book for anyone involved in clinical research, whether in Pharma, medicine or as a patient.

Medpedia, despite its growth, has some gaps. For instance, if you look for articles by the alpha index, like leukemia, you find none, but do a search and dozens of very specific articles appear (hairy cell leukemia).  Overall the number of articles, organization and layout of Medpedia continues to improve.  Try out the Clinical Trials search for yourself and see what you think.