Table 1.

Major challenge types, specific challenges, and specific examples related to use of real-time data.

Challenge category	Specific challenge	Example
Selecting the correct data elements	Selecting the right action state and timestamp	Selecting the right action state in medication order data
		Selecting the right timestamp
Other timestamp-related considerations	Delayed documentation—verbal orders	—a
	Timestamp conversion and formatting	—
	Visualizing time series data to understand temporal patterns	Raw time data table versus data visualization
Metadata attributes	Misleading (meta)data labels	Shown to user data column label
Workflow imprints	Issues that affect performance and capabilities of algorithms	Patient deterioration in the Neonatal Intensive Care Unit necessitates verbal orders
	Delayed action on active orders	—
	Priming pumps: Speeding up infusion pump rates to prime may look like an error, but has no clinical consequence	—
Unstructured data entry	Complexity of human language	Free text dosing of Total Parenteral Nutrition
	Heterogeneity of human language	—
Fusing datasets and the role of device integration	Merging datasets from multiple sources requires valid linking identifiers	The nonintegration of smart pumps with electronic health records
	Clinical decision support blind spots	Use of smart infusion pump drug libraries
Retrospective versus prospective data or detection	Retrospective data and real-time data are processed and accessed differently	The order audit modification issue
Technical versus clinical validity	—	—

^aNot applicable.