PT - JOURNAL ARTICLE AU - Ron C Li AU - Jason K Wang AU - Christopher Sharp AU - Jonathan H Chen TI - When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record AID - 10.1136/bmjqs-2018-008968 DP - 2019 Dec 01 TA - BMJ Quality & Safety PG - 987--996 VI - 28 IP - 12 4099 - http://qualitysafety.bmj.com/content/28/12/987.short 4100 - http://qualitysafety.bmj.com/content/28/12/987.full SO - BMJ Qual Saf2019 Dec 01; 28 AB - Background Order sets are widely used tools in the electronic health record (EHR) for improving healthcare quality. However, there is limited insight into how well they facilitate clinician workflow. We assessed four indicators based on order set usage patterns in the EHR that reflect potential misalignment between order set design and clinician workflow needs.Methods We used data from the EHR on all orders of medication, laboratory, imaging and blood product items at an academic hospital and an itemset mining approach to extract orders that frequently co-occurred with order set use. We identified the following four indicators: infrequent ordering of order set items, rapid retraction of medication orders from order sets, additional a la carte ordering of items not included in order sets and a la carte ordering of items despite being listed in the order set.Results There was significant variability in workflow alignment across the 11 762 order set items used in the 77 421 inpatient encounters from 2014 to 2017. The median ordering rate was 4.1% (IQR 0.6%–18%) and median medication retraction rate was 4% (IQR 2%–10%). 143 (5%) medications were significantly less likely while 68 (3%) were significantly more likely to be retracted than if the same medication was ordered a la carte. 214 (39%) order sets were associated with least one additional item frequently ordered a la carte and 243 (45%) order sets contained at least one item that was instead more often ordered a la carte.Conclusion Order sets often do not align with what clinicians need at the point of care. Quantitative insights from EHRs may inform how order sets can be optimised to facilitate clinician workflow.