Using objective clinical metrics to understand the relationship between the electronic health record and physician well-being: observational pilot study

Measuring Documentation Burden in Healthcare

BACKGROUND

The enactment of the Health Information Technology for Economic and Clinical Health Act and the wide adoption of electronic health record (EHR) systems have ushered in increasing documentation burden, frequently cited as a key factor affecting the work experience of healthcare professionals and a contributor to burnout. This systematic review aims to identify and characterize measures of documentation burden.

METHODS

We integrated discussions with Key Informants and a comprehensive search of the literature, including MEDLINE, Embase, Scopus, and gray literature published between 2010 and 2023. Data were narratively and thematically synthesized.

RESULTS

We identified 135 articles about measuring documentation burden. We classified measures into 11 categories: overall time spent in EHR, activities related to clinical documentation, inbox management, time spent in clinical review, time spent in orders, work outside work/after hours, administrative tasks (billing and insurance related), fragmentation of workflow, measures of efficiency, EHR activity rate, and usability. The most common source of data for most measures was EHR usage logs. Direct tracking such as through time-motion analysis was fairly uncommon. Measures were developed and applied across various settings and populations, with physicians and nurses in the USA being the most frequently represented healthcare professionals. Evidence of validity of these measures was limited and incomplete. Data on the appropriateness of measures in terms of scalability, feasibility, or equity across various contexts were limited. The physician perspective was the most robustly captured and prominently focused on increased stress and burnout.

DISCUSSION

Numerous measures for documentation burden are available and have been tested in a variety of settings and contexts. However, most are one-dimensional, do not capture various domains of this construct, and lack robust validity evidence. This report serves as a call to action highlighting an urgent need for measure development that represents diverse clinical contexts and support future interventions.

Using K-Means Clustering to Identify Physician Clusters by Electronic Health Record Burden and Efficiency

Objectives: Electronic health records (EHRs) have transformed the way modern medicine is practiced, but they remain a major source of documentation burden among physicians. This study aims to use data from Signal, a tool provided by the Epic EHR, to analyze physician metadata in the Montefiore Health System via cluster analysis to assess EHR burden and efficiency. Methods: Data were obtained for a one-month period (July 2020) representing a return to normal operation post-telemedicine implementation. Six metrics from Signal were used to phenotype physicians: time on unscheduled days, pajama time, time outside of 7 AM to 7 PM, turnaround time, proficiency score, and visits closed the same day. k-Means clustering was employed to group physicians, and the clusters were assessed overall and by sex and specialty. Results: Our results demonstrate the partitioning of physicians into a higher-efficiency, lower-time outside of scheduled hours (TOSH) cluster and a lower-efficiency, higher-TOSH cluster even when stratified by sex and specialty. Intra-cluster comparisons showed general homogeneity of physician metrics with the exception of the higher-efficiency, lower-TOSH cluster when stratified by sex. Conclusions: Taken together, the clusters uniquely reflect the EHR efficiency-burden of the Montefiore Health System. Applying k-means clustering to readily available EHR data allows for a scalable, efficient, and adaptable approach of assessing physician EHR burden and efficiency, allowing health systems to examine documentation trends and target wellness interventions.

Uses of Electronic Health Record Data to Measure the Clinical Learning Environment of Graduate Medical Education Trainees: A Systematic Review

PURPOSE

This study systematically reviews the uses of electronic health record (EHR) data to measure graduate medical education (GME) trainee competencies.

METHOD

In January 2022, the authors conducted a systematic review of original research in MEDLINE from database start to December 31, 2021. The authors searched for articles that used the EHR as their data source and in which the individual GME trainee was the unit of observation and/or unit of analysis. The database query was intentionally broad because an initial survey of pertinent articles identified no unifying Medical Subject Heading terms. Articles were coded and clustered by theme and Accreditation Council for Graduate Medical Education (ACGME) core competency.

RESULTS

The database search yielded 3,540 articles, of which 86 met the study inclusion criteria. Articles clustered into 16 themes, the largest of which were trainee condition experience (17 articles), work patterns (16 articles), and continuity of care (12 articles). Five of the ACGME core competencies were represented (patient care and procedural skills, practice-based learning and improvement, systems-based practice, medical knowledge, and professionalism). In addition, 25 articles assessed the clinical learning environment.

CONCLUSIONS

This review identified 86 articles that used EHR data to measure individual GME trainee competencies, spanning 16 themes and 6 competencies and revealing marked between-trainee variation. The authors propose a digital learning cycle framework that arranges sequentially the uses of EHR data within the cycle of clinical experiential learning central to GME. Three technical components necessary to unlock the potential of EHR data to improve GME are described: measures, attribution, and visualization. Partnerships between GME programs and informatics departments will be pivotal in realizing this opportunity.

Effect of Telemedicine and the COVID-19 Pandemic on Medical Trainees' Usage of the Electronic Health Record in the Outpatient Setting

OBJECTIVES

This study aimed to (1) determine the impact of COVID-19 (coronavirus disease 2019) and the corresponding increase in use of telemedicine on volume, efficiency, and burden of electronic health record (EHR) usage by residents and fellows; and (2) to compare these metrics with those of attending physicians.

METHODS

We analyzed 11 metrics from Epic's Signal database of outpatient physician user logs for active residents/fellows at our institution across three 1-month time periods: August 2019 (prepandemic/pre-telehealth), May 2020 (mid-pandemic/post-telehealth implementation), and July 2020 (follow-up period) and compared these metrics between trainees and attending physicians. We also assessed how the metrics varied for medical trainees in primary care as compared with subspecialties.

RESULTS

Analysis of 141 residents/fellows and 495 attendings showed that after telehealth implementation, overall patient volume, Time in In Basket per day, Time outside of 7 a.m. to 7 p.m., and Time in notes decreased significantly compared with the pre-telehealth period. Female residents, fellows, and attendings had a lower same day note closure rate before and during the post-telehealth implementation period and spent greater time working outside of 7 a.m. to 7 p.m. compared with male residents, fellows, and attendings (p < 0.01) compared with the pre-telehealth period. Attending physicians had a greater patient volume, spent more time, and were more efficient in the EHR compared with trainees (p < 0.01) in both the post-telehealth and follow-up periods as compared with the pre-telehealth period.

CONCLUSION

The dramatic change in clinical operations during the pandemic serves as an inflection point to study changes in physician practice patterns in the EHR. We observed that (1) female physicians closed fewer notes the same day and spent more time in the EHR outside of normal working hours compared with male physicians, and (2) attending physicians had higher patient volumes and also higher efficiency in the EHR compared with resident physicians.

Utilizing Remote Access for Electronic Medical Records Reduces Overall EMR Time for Vascular Surgery Residents

INTRODUCTION

Survey data suggests that surgical residents spend 20-30% of training time using the electronic medical record (EMR), raising concerns about burnout and insufficient operative experience. We characterize trainee EMR activity in the vascular surgery service of a quaternary care center to identify modifiable factors associated with high EMR use.

METHODS

Resident activity while on the Vascular Surgery service was queried from the EMR. Weekends and holidays were excluded to focus on typical staffing periods. Variables including daily time spent, post-graduate year (PGY), remote access via mobile device or personal laptop, and patient census including operative caseload were extracted. Univariate analysis was performed with t-tests and chi-squared tests where appropriate. We then fit a linear mixed-effects model with normalized daily EMR time as the outcome variable, random slopes for resident and patient census, and fixed effects of PGY level, academic year, and fractional time spent using remote access.

RESULTS

EMR activity for 53 residents from July 2015 to June 2019 was included. The mean daily EMR usage was 1.6 hours, ranging from 3.6 hours per day in PGY1 residents to 1.1 hours in PGY4-5 residents. Across all post-graduate years, the most time-consuming EMR activities were chart review (43.0-46.6%) and notes review (22.4-27.0%). In the linear mixed-effects model, increased patient census was associated with increased daily EMR usage (Coefficient = 0.61, p-value < 0.001). Resident seniority (Coefficient = -1.2, p-value < 0.001) and increased remote access (Coefficient = -0.44, p-value < 0.001) were associated with reduced daily EMR usage. Over the study period, total EMR usage decreased significantly from the 2015-2016 academic year to 2018-2019 (mean difference 2.4 hours vs 1.78, p-value <0.001).

CONCLUSIONS

In an audit of EMR activity logs on a vascular surgery service, mean EMR time was 1.6 hours a day, which is lower than survey estimates. Resident seniority and remote access utilization were associated with reduced time spent on the EMR, independent of patient census. While increasing EMR accessibility via mobile devices and personal computers have been hypothesized to contribute to poor work-life balance, our study suggests a possible time-saving effect by enabling expedient access for data review, which constitutes the majority of resident EMR activity. Further research in other institutions and specialties is needed for external validation and exploring implications for resident wellness initiatives.

Digital disparities among healthcare workers in typing speed between generations, genders, and medical specialties: cross sectional study

OBJECTIVE

To investigate the typing skills of healthcare professionals.

DESIGN

Cross sectional study.

SETTING

Two large tertiary medical centres in Amsterdam, the Netherlands.

PARTICIPANTS

2690 hospital employees working in patient care, research, or medical education.

MAIN OUTCOME MEASURES

Participants completed a custom built, web based, Santa themed, typing test in 60 seconds and filled out an associated questionnaire. The primary outcome was corrected typing speed, defined as crude typing speed (words per minute) multiplied by accuracy (correct characters as a percentage of total characters in the final transcribed text). Feelings towards administrative tasks scored on the Visual Analogue Scale to Weigh Respondents' Internalised Typing Enjoyment (VAS-WRITE), in which 0 represents the most negative and 100 the most positive feelings towards administration, were also recorded.

RESULTS

Between 18 and 21 May 2021, a representative cohort of 2690 study participants was recruited (1942 (72.2%) were younger than 40 years; 2065 (76.8%) were women). Respondents' mean typing speed was 60.1 corrected words per minute (standard deviation 20.8; range 8.0-136.6) with substantial differences between professions and specialties, in which physicians in internal medicine were the fastest among the medical professionals. Typing speed decreased significantly with every age decade (rho -0.51, P<0.001), and people with a history of completing a typing course were more than 20% faster than those who had not (mean difference 12.1 words (standard error 0.8), (95% confidence interval 10.6 to 13.6), P<0.001). The corrected typing speed did not differ between genders (0.5 (0.9) words, (-1.4 to 2.4), P=0.61). Women were less negative towards administration than were men (mean difference VAS-WRITE score 7.68 (standard error 1.17), (95% confidence interval 5.33 to 10.03), P<0.001). Of all professional groups, medical staff reported the most negative feelings towards administration (mean VAS-WRITE score of 33.5 (standard deviation 22.9)).

CONCLUSIONS

Important differences were reported in typing proficiency between age groups, professions, and medical specialties. Specific groups are at a disadvantage in an increasingly digitalised healthcare system, and these data could inform the implementation of training modules and alternative methods of data entry to level the playing field.

Using event logs to observe interactions with electronic health records: an updated scoping review shows increasing use of vendor-derived measures

OBJECTIVE

The aim of this article is to compare the aims, measures, methods, limitations, and scope of studies that employ vendor-derived and investigator-derived measures of electronic health record (EHR) use, and to assess measure consistency across studies.

MATERIALS AND METHODS

We searched PubMed for articles published between July 2019 and December 2021 that employed measures of EHR use derived from EHR event logs. We coded the aims, measures, methods, limitations, and scope of each article and compared articles employing vendor-derived and investigator-derived measures.

RESULTS

One hundred and two articles met inclusion criteria; 40 employed vendor-derived measures, 61 employed investigator-derived measures, and 1 employed both. Studies employing vendor-derived measures were more likely than those employing investigator-derived measures to observe EHR use only in ambulatory settings (83% vs 48%, P = .002) and only by physicians or advanced practice providers (100% vs 54% of studies, P < .001). Studies employing vendor-derived measures were also more likely to measure durations of EHR use (P < .001 for 6 different activities), but definitions of measures such as time outside scheduled hours varied widely. Eight articles reported measure validation. The reported limitations of vendor-derived measures included measure transparency and availability for certain clinical settings and roles.

DISCUSSION

Vendor-derived measures are increasingly used to study EHR use, but only by certain clinical roles. Although poorly validated and variously defined, both vendor- and investigator-derived measures of EHR time are widely reported.

CONCLUSION

The number of studies using event logs to observe EHR use continues to grow, but with inconsistent measure definitions and significant differences between studies that employ vendor-derived and investigator-derived measures.