Assessment of Electronic Health Record Search Patterns and Practices by Practitioners in a Large Integrated Health Care System

Halley Ruppel,Julia Adler-Milstein,Aashish Bhardwaj,Vincent X Liu,Manuel Ballesca,Raj N Manickam,Marc Flagg

doi:10.1001/jamanetworkopen.2020.0512

Abstract

The electronic health record (EHR) is a source of practitioner dissatisfaction in part because of challenges with information retrieval. To improve data accessibility, a better understanding of practitioners' information needs within individual patient records is needed. To assess EHR users' searches using data from a large integrated health care system. This retrospective cross-sectional analysis used EHR search data from Kaiser Permanente Northern California, an integrated health care delivery system with more than 4.4 million members. Users' EHR search activity data were obtained from April 1, 2018, to May 15, 2019. Search term frequency was grouped by user and practitioner types. Network analyses were performed of co-occurring search terms within a single search episode, and centrality measures for search terms (degree and betweenness centrality) were calculated. A total of 12 313 047 search activities (including 4 328 330 searches and 7 984 717 result views) conducted by 34 735 unique users within 977 160 unique patient EHRs were identified. In aggregate, users searched for 208 374 unique search terms and conducted a median of 4 searches (interquartile range, 1-28 searches). Of all 97 367 active EHR users, 34 735 (35.7%) conducted at least 1 search. However, of all 12 968 active EHR physician users, 9801 (75.6%) conducted at least 1 search, and of all 1908 active pharmacist users, 1402 (73.5%) conducted at least 1 search. The top 3 most commonly searched terms were statin (75 017 searches [1.7%]), colonoscopy (73 545 [1.7%]), and pft (54 990 [1.3%]). However, wide variation in top searches were noted across practitioner groups. Terms searched most often with another term in a single linked search episode included statin, lisinopril, colonoscopy, gabapentin, and aspirin. Although physicians and pharmacists were the most active users of EHR searches, search volume and frequently searched terms varied considerably by and within user role. Further customization of the EHR interface may help leverage users' search content and patterns to improve targeted information retrieval.

Highlights

IntroductionElectronic Health Record Search Patterns and Practices in a Large Integrated Health Care System documentation demands and the inaccessibility of data.[2,4,9] numerous studies[10,11,12,13,14,15] have examined documentation burden and practices, the challenges of electronic health record (EHR) information retrieval in clinical practice remain poorly understood.[16,17,18,19] Studying information retrieval is critically important because variability in documentation practices, usability challenges, and propagation of erroneous information[15,20] result in the need to navigate large volumes of low-value EHR data to locate clinically actionable patient information
The electronic health record (EHR) can be a major source of dissatisfaction for practitioners, contributing to burnout and stress.[1,2] Practitioners and patients largely agree that practitioners spend too much time in front of the computer, often at the expense of engaging with the patient.[3,4,5,6,7,8] Two major reasons for the excessive time spent in the EHR system include burdensomeOpen Access
Kaiser Permanente Northern California (KPNC) determined that this study did not meet the definition of human subject research, and the study was exempted from institutional review board approval

Summary

Introduction

Electronic Health Record Search Patterns and Practices in a Large Integrated Health Care System documentation demands and the inaccessibility of data.[2,4,9] numerous studies[10,11,12,13,14,15] have examined documentation burden and practices, the challenges of EHR information retrieval in clinical practice remain poorly understood.[16,17,18,19] Studying information retrieval is critically important because variability in documentation practices, usability challenges, and propagation of erroneous information[15,20] result in the need to navigate large volumes of low-value EHR data to locate clinically actionable patient information. Failure to identify relevant clinical data can lead to overuse of treatments or procedures, provision of low-quality care, and occurrence of medical errors.[15,21]

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Conclusion