Clinical Decision Support (CDS) tools can make doctors, nurses and other healthcare workers smarter and more effective. But how close is the industry to truly realizing their promise?
The Office of the National Coordinator (ONC) for Health Information Technology (HealthIT.gov) defines CDS as a system that “provides clinicians, staff, patients or other individuals with knowledge and person-specific information, intelligently filtered or presented at appropriate times, to enhance health and health care.” Today’s CDS tools use data from a variety of sources – including medical sensors, electronic health records (EHRs), physicians’ and nurses’ observations and clinical knowledge bases – to provide real-time guidance to clinicians.
Done right, CDS tools can:
However, currently available tools only scratch the surface of what will be possible with advanced analytics and machine learning. Using these new technologies, clinicians, epidemiologists and researchers will soon be able to mine data from Electronic Health Records (EHR) and scientific literature to find patterns in the data that can be used to drive decisions for diagnosis, treatment, disease surveillance and product development.
This is already within reach using currently available technologies. However, limitations to usability and interoperability still present challenges that have prevented CDS from reaching its full potential. Before the industry can maximize the utility of CDS tools, significant market, technical and human constraints must be resolved. Once that happens, CDS and data analytics are poised to take healthcare to a whole new level.
Read the full article by Dr. Darryl W. Roberts and Dr. David Friedenberg here.