JMIR Publications

ABSTRACT

Background:

The continued digitization and maturation of healthcare information technology has made access to real-time data easier and more feasible for more healthcare organizations. With this increased availability, the promise of using data to algorithmically detect healthcare-related events in real-time has become more of a reality. However, as more researchers and clinicians have utilized real-time data delivery capabilities, it has become apparent that simply gaining access to the data is not a panacea and some unique data challenges have come to the forefront in the process.

Objective:

To highlight some of the challenges that are germane to real-time processing of healthcare system-generated data and the accurate interpretation of the results.

Methods:

Distinct challenges related to the use and processing of real-time data for safety event detection were compiled and reported by several informatics and clinical experts at a quaternary pediatric academic institution. The challenges were collated from the experiences of the researchers implementing real-time event detection on more than half a dozen distinct projects. The challenges are presented in a challenge category/specific challenge/example format.

Results:

Eight major types of challenge categories are reported, with 13 specific challenges and 9 specific examples detailed to provide a context for the challenges. The examples reported are anchored to a specific project using medication order, medication administration record, and smart infusion pump data to detect discrepancies and errors between the three data sets.

Conclusions:

The use of real-time data to drive safety event detection and clinical decision support is extremely powerful, but presents its own set of challenges including data quality and technical complexity. These challenges must be recognized and accommodated for if the full promise of accurate, real-time safety event clinical decision support is to be realized.