Appl Clin Inform 2017; 08(04): 1197-1207
DOI: 10.4338/ACI-2017-04-RA-0060
Research Article
Schattauer GmbH Stuttgart

A Multisite Survey Study of EMR Review Habits, Information Needs, and Display Preferences among Medical ICU Clinicians Evaluating New Patients

Matthew E. Nolan
,
Rodrigo Cartin-Ceba
,
Pablo Moreno-Franco
,
Brian Pickering
,
Vitaly Herasevich
Further Information

Publication History

11 April 2017

12 July 2017

Publication Date:
22 December 2017 (online)

Abstract

Objective The electronic chart review habits of intensive care unit (ICU) clinicians admitting new patients are largely unknown but necessary to inform the design of existing and future critical care information systems.

Methods We conducted a survey study to assess the electronic chart review practices, information needs, workflow, and data display preferences among medical ICU clinicians admitting new patients. We surveyed rotating residents, critical care fellows, advanced practice providers, and attending physicians at three Mayo Clinic sites (Minnesota, Florida, and Arizona) via email with a single follow-up reminder message.

Results Of 234 clinicians invited, 156 completed the full survey (67% response rate). Ninety-two percent of medical ICU clinicians performed electronic chart review for the majority of new patients. Clinicians estimated spending a median (interquartile range (IQR)) of 15 (10–20) minutes for a typical case, and 25 (15–40) minutes for complex cases, with no difference across training levels. Chart review spans 3 or more years for two-thirds of clinicians, with the most relevant categories being imaging, laboratory studies, diagnostic studies, microbiology reports, and clinical notes, although most time is spent reviewing notes. Most clinicians (77%) worry about overlooking important information due to the volume of data (74%) and inadequate display/organization (63%). Potential solutions are chronologic ordering of disparate data types, color coding, and explicit data filtering techniques. The ability to dynamically customize information display for different users and varying clinical scenarios is paramount.

Conclusion Electronic chart review of historical data is an important, prevalent, and potentially time-consuming activity among medical ICU clinicians who would benefit from improved information display systems.

Funding

There were no specific intramural or extramural funds for this project. Mayo Clinic's installation of REDCap software is supported by the Mayo Clinic Center for Clinical and Translational Science, through an NIH Clinical and Translational Science Award (UL1 TR000135).


Supplementary Material

 
  • References

  • 1 Hanauer DA, Mei Q, Law J, Khanna R, Zheng K. Supporting information retrieval from electronic health records: a report of University of Michigan's nine-year experience in developing and using the Electronic Medical Record Search Engine (EMERSE). J Biomed Inform 2015; 55: 290-300
  • 2 Redd TK, Doberne JW, Lattin D. , et al. Variability in electronic health record usage and perceptions among specialty vs. primary care physicians. AMIA Annu Symp Proc 2015; 2015: 2053-2062
  • 3 Hilligoss B, Zheng K. Chart biopsy: an emerging medical practice enabled by electronic health records and its impacts on emergency department-inpatient admission handoffs. J Am Med Inform Assoc 2013; 20 (02) 260-267
  • 4 Block L, Habicht R, Wu AW. , et al. In the wake of the 2003 and 2011 duty hours regulations, how do internal medicine interns spend their time?. J Gen Intern Med 2013; 28 (08) 1042-1047
  • 5 Reichert D, Kaufman D, Bloxham B, Chase H, Elhadad N. Cognitive analysis of the summarization of longitudinal patient records. AMIA Annu Symp Proc 2010; 2010: 667-671
  • 6 Kannampallil TG, Franklin A, Mishra R, Almoosa KF, Cohen T, Patel VL. Understanding the nature of information seeking behavior in critical care: implications for the design of health information technology. Artif Intell Med 2013; 57 (01) 21-29
  • 7 Varpio L, Rashotte J, Day K, King J, Kuziemsky C, Parush A. The EHR and building the patient's story: a qualitative investigation of how EHR use obstructs a vital clinical activity. Int J Med Inform 2015; 84 (12) 1019-1028
  • 8 American EHR & the American Medical Association. Physicians Use of EHR Systems 2014. 2014. Available at: http://www.americanehr.com/research/reports/Physicians-Use-of-EHR-Systems-2014.aspx . Accessed April 10, 2017
  • 9 Schumacher RM, Patterson ES, North R, Quinn MT. NISTIR 7804 Technical Evaluation, Testing and Validation of the Usability of Electronic Health Records. National Institute of Standards and Technology, U.S. Department of Commerce; 2012
  • 10 Middleton B, Bloomrosen M, Dente MA. , et al; American Medical Informatics Association. Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA. J Am Med Inform Assoc 2013; 20 (e1): e2-e8
  • 11 Belden JL, Grayson R, Barnes J. Defining and Testing EMR Usability: Principles and Proposed Methods of EMR Usability Evaluation and Rating. Healthcare Information and Management Systems Society (HIMSS); 2009
  • 12 Committee on Patient Safety and Health Information Technology. Health IT and Patient Safety: Building Safer Systems for Better Care. Institute of Medicine. Washington, DC: National Academies Press; 2011
  • 13 Sittig DF, Ash JS, Singh H. The SAFER guides: empowering organizations to improve the safety and effectiveness of electronic health records. Am J Manag Care 2014; 20 (05) 418-423
  • 14 Manor-Shulman O, Beyene J, Frndova H, Parshuram CS. Quantifying the volume of documented clinical information in critical illness. J Crit Care 2008; 23 (02) 245-250
  • 15 Pickering BW, Gajic O, Ahmed A, Herasevich V, Keegan MT. Data utilization for medical decision making at the time of patient admission to ICU. Crit Care Med 2013; 41 (06) 1502-1510
  • 16 Nolan ME, Pickering BW, Herasevich V. Initial clinician impressions of a novel interactive Medical Record Timeline (MeRLin) to facilitate historical chart review during new patient encounters in the ICU. Am J Respir Crit Care Med 2016; 193: A1101
  • 17 Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)–a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009; 42 (02) 377-381
  • 18 Dalkey N, Helmer O. An experimental application of the DELPHI method to the use of experts. Manage Sci 1963; 9 (03) 458-467
  • 19 Pivovarov R, Elhadad N. Automated methods for the summarization of electronic health records. J Am Med Inform Assoc 2015; 22 (05) 938-947
  • 20 Kendall L, Klasnja P, Iwasaki J. , et al. Use of simulated physician handoffs to study cross-cover chart biopsy in the electronic medical record. AMIA Annu Symp Proc 2013; 2013: 766-775
  • 21 Weed LL. Medical records that guide and teach. N Engl J Med 1968; 278 (11) 593-600
  • 22 Tange HJ, Schouten HC, Kester ADM, Hasman A. The granularity of medical narratives and its effect on the speed and completeness of information retrieval. J Am Med Inform Assoc 1998; 5 (06) 571-582