Transforming Decision Support and Reporting
New technology is enabling easier access to information, creating collaborative care team interaction and improved clinical outcomes.
This article first appeared in the November 2014 issue of HealthLeaders magazine.
The next generation of decision-support technology leverages natural language processing (NLP)and continues to evolve by scouring unstructured text and presenting evidence-based medicine to providers in new, accessible, and interesting ways.
In two of the latest examples, clinicians themselves contribute via a growing set of predefined queries, as evidenced by Partner HealthCare's use of QPID, a queriable patient inference dossier technology recently spun out into its own Boston-based company; as well as threaded, Facebook-like conversations behind the firewall, as epitomized by the Mayo Clinic's recent six-month pilot test of Dabo, a technology developed by a San Francisco–based company in which Mayo has an ongoing investment. The result of both initiatives, executives say, is energized physicians who are helping themselves and each other achieve healthcare's Triple Aim: improving the patient experience of care, improving the health of populations, and reducing the per capita cost of healthcare.
The QPID technology originated when radiologists at Massachusetts General Hospital, a 999-bed teaching hospital in Boston, realized they were wasting too much time hunting through electronic medical records, looking for important information when making decisions, says Greg Pauly, chief operating officer of Massachusetts General Physicians Organization. "Once this bubbled up to management, there were a variety of other potential uses for this kind of technology," he says. "That's when we added to the resources to make it available to other departments, such as the ED, GI, and PATA [pre-admission testing area]."