Literature DB >> 36170882

Using the Electronic Health Record User Context in Clinical Decision Support Criteria.

Hojjat Salmasian1,2, David Rubins1,2, David W Bates1,2.   

Abstract

BACKGROUND: Computerized clinical decision support (CDS) used in electronic health record systems (EHRs) has led to positive outcomes as well as unintended consequences, such as alert fatigue. Characteristics of the EHR session can be used to restrict CDS tools and increase their relevance, but implications of this approach are not rigorously studied.
OBJECTIVES: To assess the utility of using "login location" of EHR users-that is, the location they chose on the login screen-as a variable in the CDS logic.
METHODS: We measured concordance between user's login location and the location of the patients they placed orders for and conducted stratified analyses by user groups. We also estimated how often login location data may be stale or inaccurate.
RESULTS: One in five CDS alerts incorporated the EHR users' login location into their logic. Analysis of nearly 2 million orders placed by nearly 8,000 users showed that concordance between login location and patient location was high for nurses, nurse practitioners, and physician assistance (all >95%), but lower for fellows (77%) and residents (55%). When providers switched between patients in the EHR, they usually did not update their login location accordingly.
CONCLUSION: CDS alerts commonly incorporate user's login location into their logic. User's login location is often the same as the location of the patient the user is providing care for, but substantial discordance can be observed for certain user groups. While this may provide additional information that could be useful to the CDS logic, a substantial amount of discordance happened in specific user groups or when users appeared not to change their login location across different sessions. Those who design CDS alerts should consider a data-driven approach to evaluate the appropriateness of login location for each use case. Thieme. All rights reserved.

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Year:  2022        PMID: 36170882      PMCID: PMC9519266          DOI: 10.1055/s-0042-1756426

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.762


  9 in total

1.  Types of unintended consequences related to computerized provider order entry.

Authors:  Emily M Campbell; Dean F Sittig; Joan S Ash; Kenneth P Guappone; Richard H Dykstra
Journal:  J Am Med Inform Assoc       Date:  2006-06-23       Impact factor: 4.497

2.  Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review.

Authors:  D L Hunt; R B Haynes; S E Hanna; K Smith
Journal:  JAMA       Date:  1998-10-21       Impact factor: 56.272

3.  Clinical Decision Support in the Era of Artificial Intelligence.

Authors:  Edward H Shortliffe; Martin J Sepúlveda
Journal:  JAMA       Date:  2018-12-04       Impact factor: 56.272

4.  A Time-Motion Study of Primary Care Physicians' Work in the Electronic Health Record Era.

Authors:  Richard A Young; Sandra K Burge; Kaparaboyna A Kumar; Jocelyn M Wilson; Daniela F Ortiz
Journal:  Fam Med       Date:  2018-02       Impact factor: 1.756

Review 5.  Effect of clinical decision-support systems: a systematic review.

Authors:  Tiffani J Bright; Anthony Wong; Ravi Dhurjati; Erin Bristow; Lori Bastian; Remy R Coeytaux; Gregory Samsa; Vic Hasselblad; John W Williams; Michael D Musty; Liz Wing; Amy S Kendrick; Gillian D Sanders; David Lobach
Journal:  Ann Intern Med       Date:  2012-07-03       Impact factor: 25.391

6.  How Do Residents Spend Their Shift Time? A Time and Motion Study With a Particular Focus on the Use of Computers.

Authors:  Lena Mamykina; David K Vawdrey; George Hripcsak
Journal:  Acad Med       Date:  2016-06       Impact factor: 6.893

7.  Evaluating alert fatigue over time to EHR-based clinical trial alerts: findings from a randomized controlled study.

Authors:  Peter J Embi; Anthony C Leonard
Journal:  J Am Med Inform Assoc       Date:  2012-04-25       Impact factor: 4.497

8.  Clinical reminder alert fatigue in healthcare: a systematic literature review protocol using qualitative evidence.

Authors:  Ruth Backman; Susan Bayliss; David Moore; Ian Litchfield
Journal:  Syst Rev       Date:  2017-12-13

9.  Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials.

Authors:  Janice L Kwan; Lisha Lo; Jacob Ferguson; Hanna Goldberg; Juan Pablo Diaz-Martinez; George Tomlinson; Jeremy M Grimshaw; Kaveh G Shojania
Journal:  BMJ       Date:  2020-09-17
  9 in total

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