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The doctors are in at IBM Research: examining ways to improve the healthcare systems

The doctors are in at IBM Research: examining ways to improve the healthcare systems | Health IT ☤ Informatics | Scoop.it

IBM Research (@IBMResearch) may be best known for its scientists who have created technology breakthroughs from moving atoms to analytics systems like IBM Watson. But what might surprise many is the number of deep subject matter experts now working side-by-side with computer scientists to redefine how industries apply technology to improve the services they offer.


The world's healthcare systems, for example, are aging and increasingly complex. Despite amazing advances in medicine and patient care, the system is still plagued by misdiagnosis, misaligned incentives that increase cost, and lack of access to the latest information on patient medical history and treatment options.


Today, a team of medical doctors with more than a century of combined experience is working inside IBM Research with scientists from a variety of disciplines. They are examining ways to improve the healthcare system from all angles - from using data analytics for better-informed diagnoses to understanding why certain diseases flourish in some regions of the world but not others. Perhaps most importantly, they are helping researchers deepen their understanding of the industry, in order to apply technology more effectively.

In the U.S. alone, it is estimated that up to 20 percent of diagnoses are either incorrect or incomplete. In addition, there are an estimated 1.5 million errors in the way medications are prescribed, delivered and taken in the U.S. every year.


These mistakes could be greatly reduced if doctors had access to the latest relevant medical information. But there is so much medical data in the world that it is impossible to keep track of it all.


The MDs are now working with researchers to apply IBM Watson's capabilities to answer natural language queries - which it first demonstrate by defeating the world's best human contestants on the quiz show Jeopardy! - to search through tremendous amounts of both structured and unstructured medical data, from journals to CAT scans, to provide practitioners with vital information.

 

"Watson will leverage existing evidence in new ways," said Josko Silobrcic, MD, Senior Medical Scientist at IBM Research, "and with natural language processing and machine learning, it may uncover new patterns that may not have been recognized before."


Martin Kohn, MD, Chief Medical Scientist for Care Delivery Systems at IBM Research, is helping design Watson's capabilities in a manner that best supports the way clinicians work. He said physicians tell him, "I'm looking for something to bring help to me when I need it, in a format that is useful."


Via Andrew Spong
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Health IT's Next Big Challenge: Comparative Effectiveness Research

Health IT's Next Big Challenge: Comparative Effectiveness Research | Health IT ☤ Informatics | Scoop.it

EHR systems are now collecting invaluable information that physicians can use to detect disease patterns, clusters of patients exposed to specific toxins, and groups of patients who respond well to various drug regimens. We can't waste this gold mine.

 

Healthcare providers are being pushed to deliver more cost effective medical care and to improve the health of not just individual patients but large populations. One key to carrying out both mandates is finding more clinically effective treatment options.


Many academic medical thought leaders insist that the best way to find those treatment protocols is to test them in randomized controlled trials. Such RCTs require a large group of control subjects to receive either a placebo or conventional therapy and a large group to receive the experimental treatment in question. The problem is RCTs are outrageously expensive. In today's cost conscious healthcare system, that's a problem.


Enter comparative effectiveness research. CER compares two or more accepted treatments to determine which are most effective. Medical informatics comes into the picture because it's now possible to get these projects off the ground by analyzing huge patient databases. And much of that patient data can now be gleaned from electronic health record systems.


Via nrip
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