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IOM calls for exploiting existing data for better cancer treatment

June 07, 2010 | Bernie Monegain, Editor

WASHINGTON – "Rapid learning" systems that use large electronic health record databases can quickly advance the delivery of cancer care and accelerate research, according to a new report from the Institute of Medicine.

Rapid learning systems exploit the wealth of existing data found in large EHR databases, representing the experience of millions of patients, in order to develop new treatments much faster than the current clinical model is capable of doing, the report asserts.

"A Foundation for Evidence-Driven Practice: A Rapid Learning System for Cancer Care," details how using health IT to drive the rapid learning, or RL system, could improve care and treatment for several diseases.

"It may seem as though new research emerges each day promising advances in cancer treatment, and some forms of cancer already are curable," the authors write. "Yet despite modern advances in health IT, the way that evidence on cancer screening, early detection, and treatment is gathered and applied has not moved forward rapidly enough."

The report recommends putting existing data to work.

"Researchers already gather data on effectiveness through clinical interaction with patients, as well as from cancer registries, clinical trials and networks of academic and community cancer centers," the report notes. "They could be sharing that information and aggregating it more effectively in order to accelerate advances. Healthcare payers, policymakers, and the public all could reap the benefits. Most importantly, patient care could be improved."

The IOM's National Cancer Policy Forum held a workshop October 5-6, 2009, to examine how to improve treatment and accelerate advances in cancer management by applying the concept of a rapid learning health system using advances in IT and improved information sources to deliver the best care, personalized for each patient.

The Robert Wood Johnson Foundation's Pioneer Portfolio is a proponent of rapid learning systems being used to accelerate treatment for a variety of diseases and to expand and advance the initiatives across a broad spectrum of healthcare, with the ultimate goal of embedding the RL concept as a proven and established part of national health policy and mainstream healthcare.

Related Topics:
  • cancer care
  • cancer treatment
  • cancer treatment
  • Institute of Medicine
  • Washington
  • Data Warehousing
  • Electronic Health Records
  • Health Information Exchange (HIE)

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