Almost 50 percent of hospitals with 200 or more beds will purchase a new electronic medical record system by 2016, according to a KLAS report. Even after sizable investments in new EMRs that meet meaninful use guidelines, complete and accurate patient information available to physicians, much less the enterprise, remains elusive.
New EMRs are often integrated with legacy systems, yet considerable data remains outside the application. This difficult-to-incorporate data includes critical information like external lab results and PDFs attached to the patient record. And this mountain of unstructured data continues to grow.
Effective data management plays an important role in improving the performance of an organization. Quality decision support requires timely, accurate and accessible patient information. Collecting, analyzing, interpreting, and acting on data in aggregate for specific performance measures allows healthcare professionals to identify where track outcomes and make corrective adjustments.
Many experts say unstructured data holds the key to intelligent healthcare systems. But what happens when health systems aren't extracting the intelligence from this mountain of difficult-to-incorporate data? Are there risks inherent in terms of quality of care, staff retention and accreditation?
About the Author: Greg Gies
For 20 years in the software industry, Greg Gies has been helping businesses, government agencies and healthcare organizations achieve their goals and carry out their missions by making better use of information and automating business processes. Greg has held positions in sales, product management and marketing and holds an MBA from Babson College. He works and lives with his wife and three boys in the Boston area.