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Healthcare Analytics: Mining Electronic Records Part 2

Posted Jan 19 2013 12:15pm

Teacher

Part 2 touches on the hidden costs of Healthcare Information Technology (HIT) and drivers for improving quality of patient care.

Go to Part 1

The largest investment in Healthcare technology goes beyond installation and to the training and use of these systems. Training is often a hidden cost which impacts perspective on Total Cost of Ownership that may, in fact, be one of the largest costs.

Keep in mind that from a clinical perspective, one of the most important benefits of HIT is to reduce inefficiencies and improve the quality of care. So, there are some costs savings to be realized when the technology is used accurately.

Improving the quality of patient care is a major goal for healthcare, across all disciplines, driven by the National Quality Strategy (among others) for adoption of quality and compliance measures to monitor quality of care. Compliance with these aims can be monitored in the aggregate or at a patient level in most CDS systems.

The National Quality Strategy is driving change in healthcare to improve quality. The 3 aims of the National Quality Strategy are:

Better Care: Improve the overall quality, by making health care more patient-centered, reliable, accessible, and safe.

Healthy People and Communities: Improve the health of the U.S. population by supporting proven interventions to address behavioral, social, and environmental determinants of health in addition to delivering higher-quality care.

Affordable Care: Reduce the cost of quality health care for individuals, families, employers, and government.

But a new twist on the value of Clinical Data available for "mining" and "drilling" are "databases of clinical information" that can be used for medical research.

Given this opportunity, some costs associated with traditional Clinical Trials may be mitigated by using information obtained from an EMR and Clinical Decision Support system (CDS).

Using this technology, data can be massaged and analyzed in a manner that provides retrospective views of medical data for research.  These technologies become enablers for Medical Research and Clinical Decision Support Analysis.


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