Program

This international symposium will focus on Patient Reported Outcomes (PRO) and Medical Digital Revolution, the two major trends that are pushing the paradigm shift in health care in a global scale. Dr. John E. Ware, the world class authority from U.S.A. in the field of PRO research, will give a lecture on the cutting edge of PRO measurement evaluation method. Drs. Mutoh and Sawa, who are currently working in the forefront of Medical Digital Revolution, will talk about their work and future perspectives. Dr. Fukuhara will give a lecture on possible impact on Clinical Research of Digital Revolution and full application of PRO.

Chairs : Ryozo Nagai(President, Jichi Medical University)

Yoshiyuki Kakei(President, Kagawa University)

Speakers :
John E. Ware, PhD(Professor, The University of Massachusetts) Abstract

Tomohiro Sawa(Professor, Teikyo University Medical Information System Research Center) Abstract

Shinsuke Muto(President, Tetsuyu Institute Medical Corporation) Abstract

Shunichi Fukuhara(Professor, Kyoto University/Vice President, Fukushima Medical University) Abstract

Professor John Ware, the developer of SF-36 and other short form surveys widely-used worldwide, will introduce a much-improved 10-item quality of life short-form developed in the US and normed in Japan as an SF-36 replacement and will explain how QGEN-10 fits into a system that better integrates generic and disease-specific outcome measures for those with multiple chronic conditions. Professor Ware will illustrate how this new measure is used for orthopedic patients, such as those with chronic kidney disease, dialysis care and kidney transplantation.
He will also explain how QDIS uses disease-specific attributions such as patients with chronic or end-stage kidney disease to increase responsiveness to one condition in the presence of multi-morbidity, while also allowing disease impact to be compared across diseases and aggregated into a total impact score. For all disease conditions, measures are scored using the same metric and are interpreted using norms for the US chronically-ill populations.