MeDS, the New Software to Detect Medical Research Data

by | Oct 24, 2008

As the issue of a patient’s privacy was remained well discussed issue since a very long time, virtually, from the start of medical practices. However, in the United States, this concern for the privacy security for patients, finally, entertained and regulated with the act of HIPAA (Health Insurance Portability and Accountability Act) as passed by US congress in 1996.

HIPAA though protect and provide privacy to the medical records of the patient yet the process get mixed up when the medical records are segregated for to develop new drug therapies, novel medical treatment, for the bigger causes like preventing epidemics and other life threatening hazards for whole mankind.

In a recent study discussed in the September-October issue of the Journal of the American Medical Informatics Association, Jeff Friedlin, D.O., of the Regenstrief Institute, Inc. and the Indiana University School of Medicine, provided a new computer program that have resolved the issues of  privacy vs. public good.

As according to Dr Friedlin a new Medical De-identification System (MeDS), a highly accurate and speedy computer software program has been developed and successfully tested by him for de-identifying patient information while preserving the important data input to medical research.

In Medical research, it is expected that a huge number of data is needed for the purpose of studies that data should be protected to a greater extent. This software termed as MeDS can classify data as from the records of history and physicals, discharge notes, laboratory, pathology and radiology reports.

As this software symbolizes deleted data in a manner a researcher can acknowledge something important has been taken out without telling about the nature of data in due  course that has been picked up out. In terms of efficiency this software can bring out that hefty medical data merely in 2 minutes that a human would take 6 hrs to segregate. It can also capable of detecting and eliminating misspelled names.

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