Literature DB >> 31750912

Using electronic health record audit logs to study clinical activity: a systematic review of aims, measures, and methods.

Adam Rule1, Michael F Chiang1,2, Michelle R Hribar1,2.   

Abstract

OBJECTIVE: To systematically review published literature and identify consistency and variation in the aims, measures, and methods of studies using electronic health record (EHR) audit logs to observe clinical activities.
MATERIALS AND METHODS: In July 2019, we searched PubMed for articles using EHR audit logs to study clinical activities. We coded and clustered the aims, measures, and methods of each article into recurring categories. We likewise extracted and summarized the methods used to validate measures derived from audit logs and limitations discussed of using audit logs for research.
RESULTS: Eighty-five articles met inclusion criteria. Study aims included examining EHR use, care team dynamics, and clinical workflows. Studies employed 6 key audit log measures: counts of actions captured by audit logs (eg, problem list viewed), counts of higher-level activities imputed by researchers (eg, chart review), activity durations, activity sequences, activity clusters, and EHR user networks. Methods used to preprocess audit logs varied, including how authors filtered extraneous actions, mapped actions to higher-level activities, and interpreted repeated actions or gaps in activity. Nineteen studies validated results (22%), but only 9 (11%) through direct observation, demonstrating varying levels of measure accuracy. DISCUSSION: While originally designed to aid access control, EHR audit logs have been used to observe diverse clinical activities. However, most studies lack sufficient discussion of measure definition, calculation, and validation to support replication, comparison, and cross-study synthesis.
CONCLUSION: EHR audit logs have potential to scale observational research but the complexity of audit log measures necessitates greater methodological transparency and validated standards.
© The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Keywords:  audit logs; electronic health records; systematic review; usability; workflow

Mesh:

Year:  2020        PMID: 31750912      PMCID: PMC7025338          DOI: 10.1093/jamia/ocz196

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  105 in total

1.  Use of electronic clinical documentation: time spent and team interactions.

Authors:  George Hripcsak; David K Vawdrey; Matthew R Fred; Susan B Bostwick
Journal:  J Am Med Inform Assoc       Date:  2011-02-02       Impact factor: 4.497

2.  TURF: toward a unified framework of EHR usability.

Authors:  Jiajie Zhang; Muhammad F Walji
Journal:  J Biomed Inform       Date:  2011-08-16       Impact factor: 6.317

3.  The impact of electronic health record use on physician productivity.

Authors:  Julia Adler-Milstein; Robert S Huckman
Journal:  Am J Manag Care       Date:  2013-11       Impact factor: 2.229

4.  Medical students and the electronic health record: 'an epic use of time'.

Authors:  Jeffrey Chi; John Kugler; Isabella M Chu; Pooja D Loftus; Kambria H Evans; Tomiko Oskotsky; Preetha Basaviah; Clarence H Braddock
Journal:  Am J Med       Date:  2014-06-04       Impact factor: 4.965

5.  The electronic health record audit file: the patient is waiting.

Authors:  Annemarie G Hirsch; J B Jones; Virginia R Lerch; Xiaoqin Tang; Andrea Berger; Deserae N Clark; Walter F Stewart
Journal:  J Am Med Inform Assoc       Date:  2017-04-01       Impact factor: 4.497

Review 6.  Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research.

Authors:  Nicole Gray Weiskopf; Chunhua Weng
Journal:  J Am Med Inform Assoc       Date:  2012-06-25       Impact factor: 4.497

7.  Usage Pattern Differences and Similarities of Mobile Electronic Medical Records Among Health Care Providers.

Authors:  Yura Lee; Yu Rang Park; Junetae Kim; Jeong Hoon Kim; Woo Sung Kim; Jae-Ho Lee
Journal:  JMIR Mhealth Uhealth       Date:  2017-12-13       Impact factor: 4.773

8.  Evaluation of multidisciplinary collaboration in pediatric trauma care using EHR data.

Authors:  Ashimiyu B Durojaiye; Scott Levin; Matthew Toerper; Hadi Kharrazi; Harold P Lehmann; Ayse P Gurses
Journal:  J Am Med Inform Assoc       Date:  2019-06-01       Impact factor: 4.497

9.  The impact of EHR and HIE on reducing avoidable admissions: controlling main differential diagnoses.

Authors:  Ofir Ben-Assuli; Itamar Shabtai; Moshe Leshno
Journal:  BMC Med Inform Decis Mak       Date:  2013-04-17       Impact factor: 2.796

10.  Analysis of the factors influencing healthcare professionals' adoption of mobile electronic medical record (EMR) using the unified theory of acceptance and use of technology (UTAUT) in a tertiary hospital.

Authors:  Seok Kim; Kee-Hyuck Lee; Hee Hwang; Sooyoung Yoo
Journal:  BMC Med Inform Decis Mak       Date:  2016-01-30       Impact factor: 2.796

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  30 in total

1.  Context is Key: Using the Audit Log to Capture Contextual Factors Affecting Stroke Care Processes.

Authors:  Morteza Noshad; Christian C Rose; Robert Thombley; Jonathan Chiang; Conor K Corbin; Minh Nguyen; Vincent X Liu; Julia Adler-Milstein; Jonathan H Chen
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

2.  Predicting physician burnout using clinical activity logs: Model performance and lessons learned.

Authors:  Sunny S Lou; Hanyang Liu; Benjamin C Warner; Derek Harford; Chenyang Lu; Thomas Kannampallil
Journal:  J Biomed Inform       Date:  2022-02-05       Impact factor: 6.317

3.  Measuring Electronic Health Record Use in the Pediatric ICU Using Audit-Logs and Screen Recordings.

Authors:  Amrita Sinha; Lindsay A Stevens; Felice Su; Natalie M Pageler; Daniel S Tawfik
Journal:  Appl Clin Inform       Date:  2021-08-11       Impact factor: 2.762

4.  Accuracy of Physician Electronic Health Record Usage Analytics using Clinical Test Cases.

Authors:  Brian Lo; Lydia Sequeira; Gillian Strudwick; Damian Jankowicz; Khaled Almilaji; Anjchuca Karunaithas; Dennis Hang; Tania Tajirian
Journal:  Appl Clin Inform       Date:  2022-10-05       Impact factor: 2.762

5.  Measuring time clinicians spend using EHRs in the inpatient setting: a national, mixed-methods study.

Authors:  Genna R Cohen; Jessica Boi; Christian Johnson; Llew Brown; Vaishali Patel
Journal:  J Am Med Inform Assoc       Date:  2021-07-30       Impact factor: 4.497

6.  Conceptual considerations for using EHR-based activity logs to measure clinician burnout and its effects.

Authors:  Thomas Kannampallil; Joanna Abraham; Sunny S Lou; Philip R O Payne
Journal:  J Am Med Inform Assoc       Date:  2021-04-23       Impact factor: 4.497

7.  Mining tasks and task characteristics from electronic health record audit logs with unsupervised machine learning.

Authors:  Bob Chen; Wael Alrifai; Cheng Gao; Barrett Jones; Laurie Novak; Nancy Lorenzi; Daniel France; Bradley Malin; You Chen
Journal:  J Am Med Inform Assoc       Date:  2021-06-12       Impact factor: 4.497

8.  Multicenter Analysis of Electronic Health Record Use among Ophthalmologists.

Authors:  Sally L Baxter; Helena E Gali; Mitul C Mehta; Scott E Rudkin; John Bartlett; James D Brandt; Catherine Q Sun; Marlene Millen; Christopher A Longhurst
Journal:  Ophthalmology       Date:  2020-06-07       Impact factor: 12.079

9.  Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis.

Authors:  Edward R Melnick; Shawn Y Ong; Allan Fong; Vimig Socrates; Raj M Ratwani; Bidisha Nath; Michael Simonov; Anup Salgia; Brian Williams; Daniel Marchalik; Richard Goldstein; Christine A Sinsky
Journal:  J Am Med Inform Assoc       Date:  2021-07-14       Impact factor: 4.497

10.  Impact of Changes in EHR Use during COVID-19 on Physician Trainee Mental Health.

Authors:  Katherine J Holzer; Sunny S Lou; Charles W Goss; Jaime Strickland; Bradley A Evanoff; Jennifer G Duncan; Thomas Kannampallil
Journal:  Appl Clin Inform       Date:  2021-06-02       Impact factor: 2.762

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