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When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record
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 mis...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6868292/ https://www.ncbi.nlm.nih.gov/pubmed/31164486 http://dx.doi.org/10.1136/bmjqs-2018-008968 |
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author | Li, Ron C Wang, Jason K Sharp, Christopher Chen, Jonathan H |
author_facet | Li, Ron C Wang, Jason K Sharp, Christopher Chen, Jonathan H |
author_sort | Li, Ron C |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6868292 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-68682922019-12-01 When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record Li, Ron C Wang, Jason K Sharp, Christopher Chen, Jonathan H BMJ Qual Saf Original Research 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. BMJ Publishing Group 2019-12 2019-06-04 /pmc/articles/PMC6868292/ /pubmed/31164486 http://dx.doi.org/10.1136/bmjqs-2018-008968 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Original Research Li, Ron C Wang, Jason K Sharp, Christopher Chen, Jonathan H When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record |
title | When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record |
title_full | When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record |
title_fullStr | When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record |
title_full_unstemmed | When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record |
title_short | When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record |
title_sort | when order sets do not align with clinician workflow: assessing practice patterns in the electronic health record |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6868292/ https://www.ncbi.nlm.nih.gov/pubmed/31164486 http://dx.doi.org/10.1136/bmjqs-2018-008968 |
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