Real-time intervention in health care has been attempted before with poor results. What makes us think that we can do better this time?
Well, to start with, we have learned from previous experience that inundating clinicians with false-positive information and information that they already know but does not change their clinical practice is a no-no (see drug-drug interactions).
Clarifications of their documentation to support better billing and quality reporting, however, are seen as non-intrusive to their clinical care but improves the administrative practice.
Although clinical decision support is a requirement under Stage 2 Meaningful Use.
According to HealthIT.gov, and includes tools such as “computerized alerts and reminders to care providers and patients; clinical guidelines; condition-specific order sets; focused patient data reports and summaries; documentation templates; diagnostic support, and contextually relevant reference information,” these systems are not likely to be used unless the False Positive Rate is significantly reduced based on real clinical experience.
Only through machine learning, prescriptive and predictive analytics can the sensitivity of the systems be improved. Translational research has been used to apply new learnings from retrospective database research. The CDS Consortium, at the Vanderbilt has identified “knowledge translation and specification” as an important research objectives. In addition, the Consortium for Healthcare Informatics Research, a VA-based research program located at the University of Utah is also advancing many of the methods required to conduct better predictive and prescriptive analytics.
In the meantime, real-time alerts can help providers avoid mistakes and improve quality by focusing on a few set of prioritized reminders and notifications related to Performance Indicators which have been studied extensively by AHRQ, JCAHO and CMS, amongst others. Core Measures and Patient Safety Indicators are 2 general domains which are important to notify providers of relevant information.