Literature DB >> 34241631

Differences in Clinician Electronic Health Record Use Across Adult and Pediatric Primary Care Specialties.

Lisa S Rotenstein1,2, A Jay Holmgren1,3, N Lance Downing4, Christopher A Longhurst5, David W Bates1,2,6.   

Abstract

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Year:  2021        PMID: 34241631      PMCID: PMC8271359          DOI: 10.1001/jamanetworkopen.2021.16375

Source DB:  PubMed          Journal:  JAMA Netw Open        ISSN: 2574-3805


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Introduction

Clinicians spend a large proportion of their days using the electronic health record (EHR). There are known negative associations between measures of EHR use and clinician experience.[1] Primary care clinicians spend significantly more total and after-hours time in the EHR than medical specialty and surgical colleagues.[2] However, little is known regarding variation in EHR use across primary care specialties, such as between adult and pediatric care. In this cross-sectional study, we compared EHR use across general pediatrics, general internal medicine, and family medicine clinicians.

Methods

The Stanford University institutional review board deemed this cross-sectional study exempt from approval and informed consent because it used deidentified data and was not considered human participant research. This report followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. The sample included 349 US-based ambulatory health care organizations using the same EHR vendor (Epic Systems) between January and August 2019. The sample included all clinicians with scheduled outpatient appointments, including physicians and advance practice practitioners. Using EHR metadata,[3] we measured total daily time actively using the EHR (time performing active tasks) and time spent after-hours per clinician (eMethods in the Supplement). EHR time was categorized into clinical review, notes, in-basket messages, and orders. We measured the mean number of messages received per clinician per day, overall and by source. We compared these metrics across general pediatric, general internal medicine, and family medicine clinicians. We used ordinary least squares regression to examine associations of total EHR time and after-hours EHR time with specialty, adjusting for organizational characteristics and mean daily patient volume per clinician, with robust SEs clustered at the organizational level. All analyses were conducted in Stata statistical software version 16.1 (StataCorp), with 2-sided α assessed at .05. Data were analyzed from January to March 2021.

Results

A total of 349 health systems were included in the analysis. Clinicians across these organizations had a mean (SD) of 12.9 (4.4) encounters per day among general pediatrics clinicians, 11.5 (3.6) encounters per day among general internal medicine clinicians, and 12.8 (3.4) encounters per day among family medicine clinicians. Mean (SD) daily total active EHR time was 94.7 (26.3) minutes among general pediatrics clinicians, 121.5 (34.4) minutes among general internal medicine clinicians, and 127.8 (26.6) minutes among family medicine clinicians. Mean (SD) daily after-hours active time was 23.6 (11.0) minutes among general pediatrics clinicians, 34.4 (13.8) minutes among general internal medicine clinicians, and 31.2 (10.5) minutes among family medicine clinicians. Differences in total and after-hours time persisted in multivariable regression (Figure 1).
Figure 1.

Comparisons of Total and After-Hours Time Spent on Electronic Health Records (EHR) Per Day Among Primary Care Specialty Types

Point estimates and 95% CIs calculated using ordinary least squares regressions that include controls for organization type, organization structure, number of employed physicians, number of annual visits, and mean daily patient volume per clinician, with robust SEs clustered at the organization level.

Comparisons of Total and After-Hours Time Spent on Electronic Health Records (EHR) Per Day Among Primary Care Specialty Types

Point estimates and 95% CIs calculated using ordinary least squares regressions that include controls for organization type, organization structure, number of employed physicians, number of annual visits, and mean daily patient volume per clinician, with robust SEs clustered at the organization level. Pediatric clinicians spent approximately half as long on in-basket messages (mean [SD], 9.4 [4.1] minutes) as family medicine (mean [SD], 18.0 [6.0] minutes) and general medicine (mean [SD], 18.4 [7.2] minutes) clinicians, and two-thirds as much time on clinical review and orders (Figure 2). Time spent on notes was comparable among primary care specialties. Compared with family medicine and general medicine clinicians, pediatric clinicians received one-fifth as many prescription messages, one-third as many patient messages, one-half as many team messages, and less than one-half as many results messages (Figure 2).
Figure 2.

Distribution of Time Spent on Electronic Health Records (EHR) by Primary Care Specialty Type

Discussion

This cross-sectional study found that pediatric clinicians spent significantly less total and after-hours time actively using the EHR compared with general medicine and family medicine clinicians, even after adjusting for organizational characteristics and clinical volume. While previous studies have detailed how pediatricians and internists use the EHR,[4,5] we found significant differences in EHR use across primary care specialties. Some differences may be attributed to the lesser medical complexity of pediatric patients. It is also possible that pediatricians are spending more time on clinical care outside of the EHR. However, it is notable that time spent on notes was similar across specialties, suggesting that documentation burdens may be driven by factors beyond patient complexity. Our study’s strengths include the availability of granular EHR metrics and data from a broad set of institutions. Limitations include a measure of EHR time that considers only active use and may differ from other measures used in the field,[6] use of data from a single EHR vendor, and inability to adjust for panel or clinician characteristics. Our findings suggest that there was a disproportionate burden of EHR time for general internal medicine and family medicine clinicians compared with pediatric clinicians. While some differences may be influenced by differences in clinical complexity, our findings highlight opportunities to streamline diverse EHR functions, with particular focus on messaging functions, for adult primary care clinicians and to streamline documentation requirements for all primary care clinicians.
  6 in total

1.  Implementing Measurement Science for Electronic Health Record Use.

Authors:  Edward R Melnick; Christine A Sinsky; Harlan M Krumholz
Journal:  JAMA       Date:  2021-06-01       Impact factor: 56.272

2.  Factors Affecting Physician Professional Satisfaction and Their Implications for Patient Care, Health Systems, and Health Policy.

Authors:  Mark W Friedberg; Peggy G Chen; Kristin R Van Busum; Frances Aunon; Chau Pham; John Caloyeras; Soeren Mattke; Emma Pitchforth; Denise D Quigley; Robert H Brook; F Jay Crosson; Michael Tutty
Journal:  Rand Health Q       Date:  2014-12-01

3.  Physician Time Spent Using the Electronic Health Record During Outpatient Encounters: A Descriptive Study.

Authors:  J Marc Overhage; David McCallie
Journal:  Ann Intern Med       Date:  2020-01-14       Impact factor: 25.391

4.  Pediatrician Electronic Health Record Time Use for Outpatient Encounters.

Authors:  J Marc Overhage; Kevin B Johnson
Journal:  Pediatrics       Date:  2020-11-02       Impact factor: 7.124

5.  Differences in Total and After-hours Electronic Health Record Time Across Ambulatory Specialties.

Authors:  Lisa S Rotenstein; A Jay Holmgren; N Lance Downing; David W Bates
Journal:  JAMA Intern Med       Date:  2021-06-01       Impact factor: 21.873

6.  Assessment of Electronic Health Record Use Between US and Non-US Health Systems.

Authors:  A Jay Holmgren; N Lance Downing; David W Bates; Tait D Shanafelt; Arnold Milstein; Christopher D Sharp; David M Cutler; Robert S Huckman; Kevin A Schulman
Journal:  JAMA Intern Med       Date:  2021-02-01       Impact factor: 21.873

  6 in total
  5 in total

1.  Primary care physicians' electronic health record proficiency and efficiency behaviors and time interacting with electronic health records: a quantile regression analysis.

Authors:  Oliver T Nguyen; Kea Turner; Nate C Apathy; Tanja Magoc; Karim Hanna; Lisa J Merlo; Christopher A Harle; Lindsay A Thompson; Eta S Berner; Sue S Feldman
Journal:  J Am Med Inform Assoc       Date:  2022-01-29       Impact factor: 4.497

2.  Assessing the impact of patient access to clinical notes on clinician EHR documentation.

Authors:  A Jay Holmgren; Nate C Apathy
Journal:  J Am Med Inform Assoc       Date:  2022-09-12       Impact factor: 7.942

3.  Primary Care Physician Gender and Electronic Health Record Workload.

Authors:  Eve Rittenberg; Jeffrey B Liebman; Kathryn M Rexrode
Journal:  J Gen Intern Med       Date:  2022-01-06       Impact factor: 6.473

4.  Assessment of Satisfaction With the Electronic Health Record Among Physicians in Physician-Owned vs Non-Physician-Owned Practices.

Authors:  Lisa S Rotenstein; Nate Apathy; Bruce Landon; David W Bates
Journal:  JAMA Netw Open       Date:  2022-04-01

5.  Characterization of Electronic Health Record Use Outside Scheduled Clinic Hours Among Primary Care Pediatricians: Retrospective Descriptive Task Analysis of Electronic Health Record Access Log Data.

Authors:  Selasi Attipoe; Jeffrey Hoffman; Steve Rust; Yungui Huang; John A Barnard; Sharon Schweikhart; Jennifer L Hefner; Daniel M Walker; Simon Linwood
Journal:  JMIR Med Inform       Date:  2022-05-12
  5 in total

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