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Everything [DQM] Must Have Balance
Introduction:
SIX HUNDRED BILLION DOLLARS LOST EVERY YEAR –
Got your attention, huh? That is what poor data quality costs
U.S. businesses, according to the Data Warehousing Institute. 1
Poor Data Quality Management (DQM) is also the leading
cause of many Healthcare Technology Managers project failures, inaccurate manpower management, erroneous hazard device reporting, wrong maintenance intervals as well as the inability to improve information quality, department operations and
provide better overall decisions [garbage in equal‘s garbage
out]. Therefore given that this is such a serious problem, why
aren‘t more companies, especially healthcare organizations addressing it more aggressively?
What is Data Quality?
It is data that is incomplete, inaccurate, out-of-date, or contains errors. The growing volume of data used and stored in
healthcare organizations, along with an increasing number of
different data storage devices, is leading to a serious dirty data
problem. Spelling differences or incomplete names, multiple like
serial numbers, missing or partial equipment data, and datavalue variations are much more likely to occur when a tremendous amount of data is spread out among multiple data storages or untrained technicians. The data fields of every device
make that item unique, identifiable, and traceable between our
hospital organization and the Original Equipment Manufacturer
(OEM) that will improve patient safety.
Materials:
A Department of Defense Computerized Maintenance Management System called Defense Medical Logistics Standard
Support (DMLSS). A 240,000+ medical device database utilizing
each medical devices historical data for demonstration. This
DMLSS system was checked against one Air Force Base to be
used in this study.