When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record

Area of Science:

• Health Informatics
• Clinical Workflow Analysis
• Electronic Health Records (EHR)

Background:

• Order sets are integral to electronic health records (EHRs) for enhancing healthcare quality.
• Limited understanding exists regarding how effectively order sets support clinician workflow.
• Assessing EHR order set usage patterns is crucial for identifying potential workflow misalignments.

Purpose of the Study:

• To evaluate the alignment between electronic health record (EHR) order set design and clinician workflow requirements.
• To identify and quantify indicators of misalignment between order sets and clinical practice.
• To provide data-driven insights for optimizing EHR order sets.

Main Methods:

• Utilized EHR data from an academic hospital, encompassing medication, laboratory, imaging, and blood product orders.
• Employed an itemset mining approach to identify frequently co-occurring orders with order set usage.
• Defined four key indicators: infrequent order set item ordering, rapid medication order retraction, additional 'a la carte' ordering, and 'a la carte' ordering of included items.

Main Results:

• Observed substantial workflow alignment variability across 11,762 order set items and 77,421 inpatient encounters (2014-2017).
• Median ordering rate was 4.1%, and median medication retraction rate was 4%.
• Significant proportions of order sets showed misalignment, with 39% associated with frequent 'a la carte' additions and 45% containing items more often ordered 'a la carte'.

Conclusions:

• Order sets frequently do not match clinician needs at the point of care.
• Quantitative analysis of EHR data can reveal critical insights into order set functionality.
• Optimization of EHR order sets is necessary to better facilitate clinician workflow and improve healthcare delivery.