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EHR Overtime: An Analysis of Time Spent After Hours by Family Physicians
Abstract
Background and objectives:
Time spent in the electronic health record (EHR), away from direct patient care, is associated with physician burnout. Yet there is a lack of evidence quantifying EHR use among family physicians. The purpose of the study was to describe a method for quantifying habits and duration of use within the electronic health record in family medicine residents and faculty with particular attention paid to time spent after hours.
Methods:
We audited EHR time for family medicine residents and faculty using an EHR vendor-provided, web-based tracking system. We collected and analyzed the number of patient encounters, total time in the EHR per patient, total time in the EHR after hours by physicians for a 6-month time period.
Results:
Over the 6-month period reviewed, family medicine trainees and faculty saw between one and 164 patients monthly, spent between 17 and 217 minutes in the EHR per patient, and spent between 0 and 33 hours in the EHR after hours per month.
Conclusions:
Family medicine residents spend a significant amount of time completing EHR tasks after hours. Objective EHR data can be used by family medicine residency programs to devise interventions to decrease inefficient use of the EHR, decrease after-hours EHR use, and improve well-being.
... 75,93,94,113 Only one of the experimental studies was a randomized controlled trial. 75 Across both observational and experimental studies, 41 articles compared EHR use across different groups of users including comparisons by specialty (14 studies), 4,7,25,29,31,36,42,48,51,58,59,85,105,115 clinical role (12), 24,26,33,37,46,65,76,95,99,106,108,115 gender (8), 19,34,47,49,66,68,70,106 year in residency (8), 31,32,35,39,52,56,57,95 organization (3), 24,44,75 and country (1). 27 Vendor-measure studies were more likely than investigator-measure studies to make such comparisons of EHR use by user group (65% vs 25% of studies, P < .001). ...
... Reported time-based measures included total time in the EHR (49 articles), 3 3,4,19,[24][25][26][27]29,31,32,35,36,40,44,45,48,51,[55][56][57][58] and time outside of normal working hours (35 articles). 3,4,6,19,25,[27][28][29][30]32,34,[36][37][38][39][40][41][42][43][44][47][48][49][50][51]53,55,66,67,[69][70][71][72]77,119 Vendor-measure studies were more likely than investigator-measure studies to report each of these 6 time-based measures (P < .001 in each case). While all vendor-measure studies reported at least 1 duration of active EHR use (e.g., EHR time, inbox time), just 28% of investigator-measure studies did so, with the remainder reporting specific measures related to counts of EHR actions (e.g., number of records opened, number of searches performed), the structure of clinical teams (e.g., betweenness, centrality), or the duration of clinical events (e.g., exam length, duration of shift). ...
... Definitions of what constituted EHR use outside normal working hours varied (Table 1). Twenty-two studies reported a measure based on a set time period, of which 7 unique periods were used 4,6,19,25,27,29,32,34,36,39,40,42,48,49,51,53,55,66,[69][70][71] An overlapping set of 22 articles, including 9 that also reported time period-based measures, reported at least 1 measure based on clinician schedules. 4,6,19,27,28,30,34,37,38,40,41,43,44,[47][48][49][50]67,69,72,77,119 These included time outside scheduled hours on days with appointments, time on days without appointments, and time after the patient checked out. ...
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.
... More than half (13/25, 52%) of the study designs were qualitative in nature. Studies are ordered as most recent to oldest: 2021 (n=2) [24,25], 2020 (n=4) [11,[26][27][28], 2019 (n=6) [29][30][31][32][33][34], 2018 (n=8) [35][36][37][38][39][40][41][42], 2017 (n=2) [43,44], and 2016 (n=2) [45,46]. The 25 studies examined physician burnout with some intervention of the EHR before and during the COVID-19 pandemic. ...
... Not reported Anderson et al [26] Not reported EHR must undergo redesign, high number of clicks per process is inefficient. ...
... Researchers noted respondents to surveys worked 60-80 hours per week: The extra time was largely attributed to the EHR [25,45]. Physicians spent between 17 minutes and 217 minutes per patient in the EHR, resulting in up to 33 hours per month in the EHR after work hours: These longer hours were highly attributable to symptoms of burnout [26,34]. The nonintuitive nature of the EHR negatively impacted efficiency and contributed to the longer hours [37]. ...
Background:
Physician burnout has been a documented problem since the 1970s. This condition is detrimental to physician wellbeing which can lead to quality implication is the provision of care.
Objective:
To objectively analyze the literature over the last five years for empirical evidence of burnout incident to the EHR and to identify barriers, facilitators, associated patient satisfaction to using the EHR to improve symptoms of burnout.
Methods:
No human subjects were used in this review, however 100% of participants in studies analyzed were adult physicians. Four research databases and one targeted journal were queried for studies commensurate with the objective statement from January 1, 2016 through January 31st 2021 (n=25).
Results:
The hours spent in documentation and workflow are responsible for the sense of loss of autonomy, lack of work-life balance, lack of control of one's schedule, cognitive fatigue, a general loss of autonomy and poor relationships with colleagues. Researchers have identified training, local customization of templates and workflow, and the use of scribes to alleviate the administrative burden of the EHR and decreased symptoms of burnout.
Conclusions:
The solutions provided in the literature only addressed two of the three factors, workflow and documentation time, but not the third, usability. Practitioners and administrators should focus on the former two factors because they are within their sphere of control. EHR vendors should focus on empirical evidence to identify usability features with the greatest impact to improve. Researchers should design experiments to explore solutions that address all three factors of the EHR that contribute to burnout.
Clinicaltrial:
International registered report:
RR2-10.2196/15490.
... [77][78][79] Studies included a mix of ambulatory (n ¼ 22) 14 58,77 A majority of those studies involved single sites (77.1%) and were affiliated with an academic institution/teaching hospital (80.0%). One third used Epic systems (n ¼ 13), 13,22,27,43,53,54,56,57,64,66,69,72,73 followed by multiple/other/unspecified (n ¼ 12), 14,28,29,52,63,67,68,[75][76][77][78][79] Cerner (n ¼ 6), [58][59][60]65,71,74 Allscripts (n ¼ 2), 61,62 and Eclipsys (n ¼ 2). 55,70 Articles were published between 2010 and 2020 with 2018 (n ¼ 8) 13 13,27,43,54,55,57,59,60,63,64,66,72,74,75,77 experimental/quasiexperimental (n ¼ 8), 14,22,29,53,56,58,78,79 and cross-sectional studies (n ¼ 4). ...
... 55,70 Articles were published between 2010 and 2020 with 2018 (n ¼ 8) 13 13,27,43,54,55,57,59,60,63,64,66,72,74,75,77 experimental/quasiexperimental (n ¼ 8), 14,22,29,53,56,58,78,79 and cross-sectional studies (n ¼ 4). 69,71,73,76 Eight studies evaluated an intervention, 14,22,52,53,56,58,75,78 including scribes (n ¼ 3), 14,52,53 documentation redesign (n ¼ 3), 58,75,78 or EHR training programs (n ¼ 2) 22,56 ; the remaining were descriptive studies on EHR activities and usage (n ¼ 27)-2 of which involved the implementation of new EHR systems. 29 A diversity of analytical methods was employed. ...
... Time spent documenting was assessed in all studies and was measured using 3 key data collection strategies: EHR usage logs (n ¼ 28), 13,14,22,27,43,[53][54][55][56][57][58][59][60][63][64][65][66][67]69,[71][72][73][74][75][76][77][78][79] activity capture applications (n ¼ 8), [27][28][29]52,61,62,68,80 and video recordings (n ¼ 1). 58 Few studies triangulated these data through multiple data collection strategies (n ¼ 2). ...
Background:
Objective:
Electronic health records (EHRs) are linked with documentation burden resulting in clinician burnout. While clear classifications and validated measures of burnout exist, documentation burden remains ill-defined and inconsistently measured. We aim to conduct a scoping review focused on identifying approaches to documentation burden measurement and their characteristics.
Materials and methods:
Based on Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Extension for Scoping Reviews (ScR) guidelines, we conducted a scoping review assessing MEDLINE, Embase, Web of Science, and CINAHL from inception to April 2020 for studies investigating documentation burden among physicians and nurses in ambulatory or inpatient settings. Two reviewers evaluated each potentially relevant study for inclusion/exclusion criteria.
Results:
Of the 3482 articles retrieved, 35 studies met inclusion criteria. We identified 15 measurement characteristics, including 7 effort constructs: EHR usage and workload, clinical documentation/review, EHR work after hours and remotely, administrative tasks, cognitively cumbersome work, fragmentation of workflow, and patient interaction. We uncovered 4 time constructs: average time, proportion of time, timeliness of completion, activity rate, and 11 units of analysis. Only 45.0% of studies assessed the impact of EHRs on clinicians and/or patients and 40.0% mentioned clinician burnout.
Discussion:
Standard and validated measures of documentation burden are lacking. While time and effort were the core concepts measured, there appears to be no consensus on the best approach nor degree of rigor to study documentation burden.
Conclusion:
Further research is needed to reliably operationalize the concept of documentation burden, explore best practices for measurement, and standardize its use.
... Evaluating provider interactions with the EHR has primarily been conducted to understand burnout, and has revealed important insight into providers' EHR documentation patterns. [17][18][19][20] Initially, these interactions utilized methods such as time motion studies, keystrokes, and mouse miles to identify the specific elements of the EHR, which most impact providers and their patients. 21 More recently, it has been proposed that the same metrics that are already stored and used to audit the EHR can be repurposed and utilized to objectively assess the clinical experience. ...
... Our third area of interest was provider burnout, which has been correlated with time spent in the EHR outside of work. 20,23,26 The exact methodology for measuring time outside of usual working hours has differed between studies, so we decided to include three different metrics: (1) time spent outside 7 AM-7 PM; (2) time spent on unscheduled days (average number of minutes spent in the system on days with no scheduled patients, only including unscheduled days wherein system activity was detected); and (3) pajama time (average number of minutes spent in charting activities outside of 7 AM-5:30 PM on weekdays and outside scheduled hours on weekends, not including any time spent in the system during scheduled hours). ...
Telemedicine has been widely implemented during the coronavirus disease 2019 (COVID-19) pandemic; however, its impact on those providing care remains largely understudied. Provider documentation data collected by the electronic health record (EHR) represents an underutilized tool for assessing the provider experience. Through Epic Signal, we collected data regarding the actions logged in the EHR by health care providers of the Montefiore Health System (Bronx, NY) before and after the implementation of telemedicine during the pandemic. Focusing on five metrics (appointments per day, visits closed same day, time spent outside 7 AM-7 PM, time spent on unscheduled days, and pajama time), we performed a preliminary analysis of providers across the institution, by specialty, and according to demographic characteristics such as gender and years since graduation. We observed that after telemedicine implementation, a greater proportion of providers had fewer appointments per day, closed more notes same day, and spent less time in the EHR outside of normal working hours for each of the time-related metrics. We additionally found that providers who graduated longer ago as well as female providers spent more time documenting in the EHR after hours. This brief analysis highlights the potential of using EHR data to inform decisions based on provider well-being, specifically in the setting of telemedicine implementation.
... It is estimated that on average, clinicians spend 6 hours per day documenting care in the EHR, much of this occurs during a clinician's personal time. 7,8 Over a 30-year career, working 200 days per year, this represents 36,000 hours or 4 years of a clinician's life spent using an EHR. It is not surprising that technology remains the leading cause of clinician burnout. ...
... Importantly, telehealth implementation has been linked to less provider time spent in the electronic health records (EHR) outside of normal working hours [26]. Given that provider burnout has been correlated with time spent in the EHR outside of work, [30][31][32] this finding suggests that telehealth approaches could also help improve physician satisfaction and reduce burnout. ...
Background
Understanding perceptions of telehealth implementation from patients and providers can improve the utility and sustainability of these programs, particularly in under-resourced rural settings. The purpose of this study was to evaluate both patient and provider perceptions of telehealth visits in a large rural healthcare system during the COVID-19 pandemic. To promote sustainability of telehealth approaches, we also assessed whether the percentage of missed appointments differed between in-person and telehealth visits.
Methods
Using anonymous surveys, we evaluated patient preferences and satisfaction with telehealth visits from November 2020 -March 2021 and assessed perceptions of telehealth efficiency and value among rural providers from September–October 2020. We examined whether telehealth perceptions differed according to patients’ age, educational attainment, insurance status, and distance to clinical site and providers’ age and length of time practicing medicine using ANOVA test. We also examined whether the percentage of missed appointments differed between in-person and telehealth visits at a family practice clinic within the rural healthcare system from April to September 2020 using a Chi-square test.
Results
Over 73% of rural patients had favorable perceptions of telehealth visits, and satisfaction was generally higher among younger patients. Patients reported difficulty with scheduling follow-up appointments, lack of personal contact and technology challenges as common barriers. Over 80% of the 219 providers responding to the survey reported that telehealth added value to their practice, while 36.6% agreed that telehealth visits are more efficient than in-person visits. Perception of telehealth value and efficiency did not differ by provider age (p = 0.67 and p = 0.67, respectively) or time in practice (p = 0.53 and p = 0.44, respectively). Technology challenges for the patient (91.3%) and provider (45.1%) were commonly reported. The percentage of missed appointments was slightly higher for telehealth visits compared to in-person visits, but the difference was not statistically significant (8.7% vs. 8.0%; p = 0.39).
Conclusions
Telehealth perceptions were generally favorable among rural patients and providers, although satisfaction was lower among older patients and providers. Our findings suggest that telehealth approaches may add value and efficiency to rural clinical practice. However, technology issues for both patients and providers and gaps in care coordination need to be addressed to promote sustainability of telehealth approaches in rural practice.
... We also did not find differences based on FTE, contrary to previous findings [16] that more work relative value units generated by physicians (another measure of workload) were associated with more EHR time after work hours. Most studies use basic measures to characterize EHR usage, such as the duration of time [14,15,55]. In one study, researchers used more complex measures to characterize mobile EHR usage, such as the number of log-ins and features used and usage paths (ie, the frequency and complexity of consecutive actions) [56]. ...
Background:
Increased work through electronic health record (EHR) messaging is frequently cited as a factor of physician burnout. However, studies to date have relied on anecdotal or self-reported measures, which limit the ability to match EHR use patterns with continuous stress patterns throughout the day.
Objective:
The aim of this study is to collect EHR use and physiologic stress data through unobtrusive means that provide objective and continuous measures, cluster distinct patterns of EHR inbox work, identify physicians' daily physiologic stress patterns, and evaluate the association between EHR inbox work patterns and physician physiologic stress.
Methods:
Physicians were recruited from 5 medical centers. Participants (N=47) were given wrist-worn devices (Garmin Vivosmart 3) with heart rate sensors to wear for 7 days. The devices measured physiological stress throughout the day based on heart rate variability (HRV). Perceived stress was also measured with self-reports through experience sampling and a one-time survey. From the EHR system logs, the time attributed to different activities was quantified. By using a clustering algorithm, distinct inbox work patterns were identified and their associated stress measures were compared. The effects of EHR use on physician stress were examined using a generalized linear mixed effects model.
Results:
Physicians spent an average of 1.08 hours doing EHR inbox work out of an average total EHR time of 3.5 hours. Patient messages accounted for most of the inbox work time (mean 37%, SD 11%). A total of 3 patterns of inbox work emerged: inbox work mostly outside work hours, inbox work mostly during work hours, and inbox work extending after hours that were mostly contiguous to work hours. Across these 3 groups, physiologic stress patterns showed 3 periods in which stress increased: in the first hour of work, early in the afternoon, and in the evening. Physicians in group 1 had the longest average stress duration during work hours (80 out of 243 min of valid HRV data; P=.02), as measured by physiological sensors. Inbox work duration, the rate of EHR window switching (moving from one screen to another), the proportion of inbox work done outside of work hours, inbox work batching, and the day of the week were each independently associated with daily stress duration (marginal R2=15%). Individual-level random effects were significant and explained most of the variation in stress (conditional R2=98%).
Conclusions:
This study is among the first to demonstrate associations between electronic inbox work and physiological stress. We identified 3 potentially modifiable factors associated with stress: EHR window switching, inbox work duration, and inbox work outside work hours. Organizations seeking to reduce physician stress may consider system-based changes to reduce EHR window switching or inbox work duration or the incorporation of inbox management time into work hours.
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.
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.
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.
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.
Objectives
Outpatient rehabilitation (rehab) physical, occupational, and speech therapists use electronic health records (EHR), yet their documentation experiences, including any documentation burden, are not well researched. Therapists are a growing portion of the U.S. healthcare workforce, whose need is critical to the health of an aging population. We aimed to describe outpatient rehab therapists’ documentation experiences and identify strategies for mitigating any documentation burden.
Materials and Methods
We used qualitative descriptive methodology to conduct 4 focus groups with outpatient rehab therapists at Hospital for Special Surgery, a multi-site orthopedic institution. Transcripts were inductively coded to identify themes and actionable strategies for improving the therapists’ documentation experiences. Therapists provided feedback and prioritization of proposed strategies.
Results
A total of 13 therapists were interviewed. Five themes and 10 subthemes characterize the therapists’ documentation experience by a feeling that documentation inhibits clinical care and work/life balance, a perceived lack of support and efficiencies, the desire to document to communicate clinical care, and a design vision for improving the EHR. Top prioritized strategies for improvement included use of timesaving templates, expanding dictation, decluttering the EHR interface, and support for free texting over discrete data capture.
Discussion
Outpatient rehab therapists experience documentation burden similar to that documented of physicians and nurses. Manual data entry imposes burden on therapists’ time and clinical care.
Conclusion
A multi-faceted approach is needed for improving therapists’ experiences including EHR redesign, technology supporting dictation and narrative to discrete data capture, and support from leadership and regulators.
Background: Electronic health record systems have given rise to a tremendous transformation in the US
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.
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.
Objectives:
1) To determine the impact of COVID-19 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.
Materials and methods:
We analyzed eleven 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 (pre-pandemic / 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 to 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 7AM-7PM, and Time in Notes decreased significantly compared to 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 AM-7 PM compared to male residents, fellows, and attendings (p<0.01) compared to the pre-telehealth period. Attending physicians had a greater patient volume, spent more time and were more efficient in the EHR compared to trainees (p<0.01) in both the post-telehealth and follow-up periods as compared to 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 via 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 to male physicians; and 2) attending physicians had higher patient volumes and also higher efficiency in the EHR compared to resident physicians.
As important as individual solutions and team-based solutions are, there is a critical third level of potential solutions that can and should be implemented, namely, system-level solutions. Some of these broader solutions can be implemented fairly directly by leaders in local healthcare systems, including individual practices and hospitals. One especially important “local systems” solution is workflow analysis and workflow simplification. As valuable as improving workflow is, it is a challenge to persuade leaders to engage in such a change process, and it is a challenge to persuade those who would benefit from workflow simplification to actually change their behavior. The pandemic is providing a major “reset” opportunity, the chance to rethink how we do things in general and, more particularly, in healthcare.
Patients have demonstrated a growing interest in using wearable devices, particularly smartwatches, to monitor and improve their cardiovascular wellness. Wearable devices are now one of the fastest growing sectors of the technology industry, and big technology companies, such as Apple (Apple Watch), Google (Fitbit), and Samsung (Galaxy), have engineered smartwatch features that are capable of monitoring biometrics, such as heart rhythm, heart rate, blood pressure, and sleep. These devices hold significant potential to impact the relation between cardiologists and their patients, but concerns exist about device trustworthiness to detect pertinent data points and deliver alerts with accuracy. How these devices’ features will interplay with cardiologists’ workflow has also yet to be defined and requires thoughtful implementation. Furthermore, the success of smartwatches as medical devices is dependent on patients’ continuous use. Keeping patients engaged with their devices through leveraging behavioral factors may lead to achieving and optimizing healthcare goals. Socioeconomic disparities and privacy concerns are other barriers in the path forward. Cardiovascular professional societies are uniquely poised to help impact how these devices are eventually accepted and used in everyday practice. In conclusion, engagement and collaboration with big tech companies will help guide how this market grows.
Background:
Clinician burnout is a prevalent issue in healthcare, with detrimental implications in healthcare quality and medical costs due to errors. The inefficient use of health information technologies (HIT) is attributed to having a role in burnout.
Objective:
This paper seeks to review the literature with the following two goals: (1) characterize and extract HIT trends in burnout studies over time, and (2) examine the evidence and synthesize themes of HIT's roles in burnout studies.
Methods:
A scoping literature review was performed by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines with two rounds of searches in PubMed, IEEE Xplore, ACM, and Google Scholar. The retrieved papers and their references were screened for eligibility by using developed inclusion and exclusion criteria. Data were extracted from included papers and summarized either statistically or qualitatively to demonstrate patterns.
Results:
After narrowing down the initial 945 papers, 36 papers were included. All papers were published between 2013 and 2020; nearly half of them focused on primary care (n = 16; 44.4%). The most commonly studied variable was electronic health record (EHR) practices (e.g., number of clicks). The most common study population was physicians. HIT played multiple roles in burnout studies: it can contribute to burnout; it can be used to measure burnout; or it can intervene and mitigate burnout levels.
Conclusion:
This scoping review presents trends in HIT-centered burnout studies and synthesizes three roles for HIT in contributing to, measuring, and mitigating burnout. Four recommendations were generated accordingly for future burnout studies: (1) validate and standardize HIT burnout measures; (2) focus on EHR-based solutions to mitigate clinician burnout; (3) expand burnout studies to other specialties and types of healthcare providers, and (4) utilize mobile and tracking technology to study time efficiency.
Purpose
The use of the Electronic Health Record (EHR) has led to physician dissatisfaction, physician burnout, and delays in documentation and billing. Medical scribes can mitigate these unintended consequences by reducing documentation workload and increasing efficiency.
Objective
To study the effects of medical scribes on time to completion of notes and clinician experience, with a focus on time spent charting during clinic and after-hours. We hypothesized that medical scribes in an outpatient pediatric setting would decrease clinician time spent charting, time to finalize encounter notes, and clinician's perceived documentation time.
Method
This 15-month single-center observational study was carried out with 3 study periods: pre-scribe, with-scribe, and scribe-withheld. Time spent in EHR was extracted by our EHR vendor. Participants completed surveys regarding time spent documenting. Six clinicians (5 physicians, 1 nurse practitioner) participated in this study to trial the implementation of medical scribes.
Results
EHR time data was collected for 4329 patient visits (2232 pre-scribe, 1888 with-scribe, 209 scribe-withheld periods). Comparing pre-scribe versus with-scribe periods, documentation time per patient decreased by 3-minutes 28-seconds per patient (pre-scribe IQR: 6, with-scribe IQR: 3, p=0.028); note timeliness decreased from 0.96 days to 0.26 days (pre-scribe IQR: 0.22, with-scribe IQR: 0.11, p=0.028); and clinicians’ estimates of time spent in the EHR decreased by 1.2 hours per clinic session (pre-scribe IQR: 0.5, with-scribe IQR: 0.5, p=0.031).
Conclusions
Medical scribes in an outpatient pediatric setting result in: 1) decreased time spent charting, 2) reduced time to final sign clinic notes, and 3) decrease in clinician's perceived time spent documenting.
Objective
Electronic health records (EHRs) are an integral part of the medical system and are used in all aspects of care. Despite multiple advantages of an EHR, concerns exist over the amount of time that residents spend on computers rather than in direct patient care. This study aims to quantify the time a general surgery resident spends on the EHR during their training.
Design/Participants
Active usage time data from our institution's EHR were extracted for 34 unique general surgery residents from October 2014 to June 2019. Career time on the EHR was calculated and a “work month” was defined as a 4-week period of 80 hours per week.
Setting
Carolinas Medical Center, Charlotte, NC.
Results
Total career EHR usage for a general surgery resident was 2512 continuous hours, corresponding to 31.4 work weeks or 7.9 work months. In total, 7133 charts were opened with an average of 20.5 minutes on the EHR per patient chart. Career time spent on specific tasks included: chart review 10.6 work weeks, documentation 10.4 work weeks, and order entry 5.4 work weeks. The total number of orders entered were 57,739 and total number of documents created were 9222. EHR time in all aspects, patient charts opened, documents created, and number of orders entered decreased as postgraduate year increased.
Conclusions
This is the first study quantifying the total time a general surgery resident spends on the EHR during their clinical training. Total EHR time equated to nearly 8 work months. General surgery residents spend considerable time on the EHR and this underscores the importance of implementing methods to improve EHR efficiency and maximize time for clinical training.
Importance
Speech recognition (SR) is increasingly used directly by clinicians for electronic health record (EHR) documentation. Its usability and effect on quality and efficiency versus other documentation methods remain unclear.
Objective
To study usability and quality of documentation with SR versus typing.
Design
In this controlled observational study, each subject participated in two of five simulated outpatient scenarios. Sessions were recorded with Morae® usability software. Two notes were documented into the EHR per encounter (one dictated, one typed) in randomized order. Participants were interviewed about each method’s perceived advantages and disadvantages. Demographics and documentation habits were collected via survey. Data collection occurred between January 8 and February 8, 2019, and data analysis was conducted from February through September of 2019.
Setting
Brigham and Women’s Hospital, Boston, Massachusetts, USA.
Participants
Ten physicians who had used SR for at least six months.
Main Outcomes and Measures
Documentation time, word count, vocabulary size, number of errors, number of corrections and quality (clarity, completeness, concision, information sufficiency and prioritization).
Results
Dictated notes were longer than typed notes (320.6 vs. 180.8 words; p = 0.004) with more unique words (170.9 vs. 120.4; p = 0.01). Documentation time was similar between methods, with dictated notes taking slightly less time to complete than typed notes. Typed notes had more uncorrected errors per note than dictated notes (2.9 vs. 1.5), although most were minor misspellings. Dictated notes had a higher mean quality score (7.7 vs. 6.6; p = 0.04), were more complete and included more sufficient information.
Conclusions and Relevance
Participants felt that SR saves them time, increases their efficiency and allows them to quickly document more relevant details. Quality analysis supports the perception that SR allows for more detailed notes, but whether dictation is objectively faster than typing remains unclear, and participants described some scenarios where typing is still preferred. Dictation can be effective for creating comprehensive documentation, especially when physicians like and feel comfortable using SR. Research is needed to further improve integration of SR with EHR systems and assess its impact on clinical practice, workflows, provider and patient experience, and costs.
Background and objectives:
Electronic health records (EHRs) have had mixed effects on the workflow of ambulatory primary care. In this study, we update previous research on the time required to care for patients in primary care clinics with EHRs.
Methods:
We directly observed family physician (FP) attendings, residents, and their ambulatory patients in 982 visits in clinics affiliated with 10 residencies of the Residency Research Network of Texas. The FPs were purposely chosen to reflect a diversity of patient care styles. We measured total visit time, previsit chart time, face-to-face time, non-face time, out-of-hours EHR work time, and total EHR work time.
Results:
The mean (SD) visit length was 35.8 (16.6) minutes, not counting resident precepting time. The mean time components included 2.9 (3.8) minutes working in the EHR prior to entering the room, 16.5 (9.2) minutes of face-to-face time not working in the EHR, 2.0 (2.1) minutes working in the EHR in the room (which occurred in 73.4% of the visits), 7.5 (7.5) minutes of non-face time (mostly EHR time), and 6.9 (7.6) minutes of EHR work outside of normal clinic operational hours (which occurred in 64.6% of the visits). The total time and total EHR time varied only slightly between faculty physicians, third-year and second-year residents. Multivariable linear regression analysis revealed many factors associated with total visit time including patient, physician, and clinic infrastructure factors.
Conclusions:
Primary care physicians spent more time working in the EHR than they spent in face-to-face time with patients in clinic visits.
Background:
Little is known about how physician time is allocated in ambulatory care.
Objective:
To describe how physician time is spent in ambulatory practice.
Design:
Quantitative direct observational time and motion study (during office hours) and self-reported diary (after hours).
Setting:
U.S. ambulatory care in 4 specialties in 4 states (Illinois, New Hampshire, Virginia, and Washington).
Participants:
57 U.S. physicians in family medicine, internal medicine, cardiology, and orthopedics who were observed for 430 hours, 21 of whom also completed after-hours diaries.
Measurements:
Proportions of time spent on 4 activities (direct clinical face time, electronic health record [EHR] and desk work, administrative tasks, and other tasks) and self-reported after-hours work.
Results:
During the office day, physicians spent 27.0% of their total time on direct clinical face time with patients and 49.2% of their time on EHR and desk work. While in the examination room with patients, physicians spent 52.9% of the time on direct clinical face time and 37.0% on EHR and desk work. The 21 physicians who completed after-hours diaries reported 1 to 2 hours of after-hours work each night, devoted mostly to EHR tasks.
Limitations:
Data were gathered in self-selected, high-performing practices and may not be generalizable to other settings. The descriptive study design did not support formal statistical comparisons by physician and practice characteristics.
Conclusion:
For every hour physicians provide direct clinical face time to patients, nearly 2 additional hours is spent on EHR and desk work within the clinic day. Outside office hours, physicians spend another 1 to 2 hours of personal time each night doing additional computer and other clerical work.
Primary funding source:
American Medical Association.
Background and objectives:
The increased demand on providers from health care systems combined with the complex and difficult practice of medicine contributes to provider stress and burnout. In order to develop effective, sustainable interventions for provider burnout, it is important to understand the lived experiences of providers and their perceptions of its causative factors. We describe focus group findings that explore provider perceptions and offer suggestions for future actions.
Methods:
We convened six focus groups in five clinics involving 44 participants and used a common set of questions for each group. Real-time follow-up questions varied as needed to clarify or explore specific themes. We asked for descriptions of providers' daily work, their ability to complete that work, and the frustrations associated with accomplishing their tasks. In addition, providers were asked about transparency of decision making and their perceptions of control in the workplace.
Results:
Three major themes evolved from these focus groups: the perceived impact of the work environment, work tasks, and "e-stress."
Conclusions:
Our findings suggest three competing tensions contribute to provider burnout, none of which were attributable to patient volume or complexity. These tensions were described as originating from clinician experience of management practices and new requirements in the work environment, tension between direct patient care and non-direct patient care work tasks, and "e-stress" caused by the digital presence in providers' work lives.
Background Since the late 1980s, resident physicians have spent increasing amounts of time on electronic health record (EHR) data entry and retrieval. Objective longitudinal data measuring time spent on the EHR are lacking.
Objective We sought to quantify the time actually spent using the EHR by all first-year internal medicine residents in a single program (N = 41).
Methods Active EHR usage data were collected from the audit logs for May, July, and October 2014 and January 2015. Per recommendations from our EHR vendor (Cerner Corporation), active EHR usage time was defined as more than 15 keystrokes, or 3 mouse clicks, or 1700 ‘‘mouse miles’’ per minute. Active EHR usage time was tallied for each patient chart viewed each day and termed an electronic patient record encounter (EPRE).
Results In 4 months, 41 interns accumulated 18 322 hours of active EHR usage in more than 33 733 EPREs. Each intern spent on average 112 hours per month on 206 EPREs. Interns spent more time in July compared to January (41 minutes versus 30 minutes per EPRE, P < .001). Time spent on the EHR in January echoed that of the previous May (30 minutes versus 29 minutes, P = .40).
Conclusions First-year residents spent a significant amount of time actively using the EHR, achieving maximal proficiency on or before January of the academic year. Decreased time spent on the EHR may reflect greater familiarity with the EHR, growing EHR efficiencies, or other factors.
Purpose:
Primary care physicians spend nearly 2 hours on electronic health record (EHR) tasks per hour of direct patient care. Demand for non-face-to-face care, such as communication through a patient portal and administrative tasks, is increasing and contributing to burnout. The goal of this study was to assess time allocated by primary care physicians within the EHR as indicated by EHR user-event log data, both during clinic hours (defined as 8:00 am to 6:00 pm Monday through Friday) and outside clinic hours.
Methods:
We conducted a retrospective cohort study of 142 family medicine physicians in a single system in southern Wisconsin. All Epic (Epic Systems Corporation) EHR interactions were captured from "event logging" records over a 3-year period for both direct patient care and non-face-to-face activities, and were validated by direct observation. EHR events were assigned to 1 of 15 EHR task categories and allocated to either during or after clinic hours.
Results:
Clinicians spent 355 minutes (5.9 hours) of an 11.4-hour workday in the EHR per weekday per 1.0 clinical full-time equivalent: 269 minutes (4.5 hours) during clinic hours and 86 minutes (1.4 hours) after clinic hours. Clerical and administrative tasks including documentation, order entry, billing and coding, and system security accounted for nearly one-half of the total EHR time (157 minutes, 44.2%). Inbox management accounted for another 85 minutes (23.7%).
Conclusions:
Primary care physicians spend more than one-half of their workday, nearly 6 hours, interacting with the EHR during and after clinic hours. EHR event logs can identify areas of EHR-related work that could be delegated, thus reducing workload, improving professional satisfaction, and decreasing burnout. Direct time-motion observations validated EHR-event log data as a reliable source of information regarding clinician time allocation.
Background :
Physician burnout is a problem that often is attributed to the use of the electronic health record (EHR).
Objective :
To estimate the prevalence of burnout and work-life balance satisfaction in primary care residents and teaching physicians, and to examine the relationship between these outcomes, EHR use, and other practice and individual factors.
Methods :
Residents and faculty in 19 primary care programs were anonymously surveyed about burnout, work-life balance satisfaction, and EHR use. Additional items included practice size, specialty, EHR characteristics, and demographics. A logistic regression model identified independent factors associated with burnout and work-life balance satisfaction.
Results :
In total, 585 of 866 surveys (68%) were completed, and 216 (37%) respondents indicated 1 or more symptoms of burnout, with 162 (75%) attributing burnout to the EHR. A total of 310 of 585 (53%) reported dissatisfaction with work-life balance, and 497 (85%) indicated that use of the EHR affected their work-life balance. Respondents who spent more than 6 hours weekly after hours in EHR work were 2.9 times (95% confidence interval [CI] 1.9-4.4) more likely to report burnout and 3.9 times (95% CI 1.9-8.2) more likely to attribute burnout to the EHR. They were 0.33 times (95% CI 0.22-0.49) as likely to report work-life balance satisfaction, and 3.7 times (95% CI 2.1-6.7) more likely to attribute their work-life balance satisfaction to the EHR.
Conclusions :
More after-hours time spent on the EHR was associated with burnout and less work-life satisfaction in primary care residents and faculty.
Background :
Rates of physician burnout have increased in recent years, and high burnout levels are reported by physicians in training.
Objective :
This review of the research on resident well-being seeks to identify factors associated with well-being, summarize well-being promotion interventions, and provide a framework for future research efforts.
Methods :
Keywords were used to search PubMed, PsycINFO, and MEDLINE. Studies included were conducted between 1989 and 2014. The search yielded 82 articles, 26 which met inclusion criteria, and were assessed using the Medical Education Research Study Quality Instrument.
Results :
Articles measured resident well-being and associated factors, predictors, effects, barriers, as well as interventions to improve well-being. Factors identified in psychological well-being research-autonomy, building of competence, and strong social relatedness-are associated with resident well-being. Sleep and time away from work are associated with greater resident well-being. Perseverance is predictive of well-being, and greater well-being is associated with increased empathy. Interventions focused on health and coping skills appear to improve well-being, although the 3 studies that examined interventions were limited by small samples and single site administration.
Conclusions :
An important step in evolving research in this area entails the development of a clear definition of resident well-being and a scale for measuring the construct. The majority (n = 17, 65%) of existing studies are cross-sectional analyses of factors associated with well-being. The literature summarized in this review suggests future research should focus on factors identified in cross-sectional studies, including sleep, coping mechanisms, resident autonomy, building competence, and enhanced social relatedness.
Objective:
To evaluate associations between the electronic environment, clerical burden, and burnout in US physicians.
Participants and methods:
Physicians across all specialties in the United States were surveyed between August and October 2014. Physicians provided information regarding use of electronic health records (EHRs), computerized physician order entry (CPOE), and electronic patient portals. Burnout was measured using validated metrics.
Results:
Of 6375 responding physicians in active practice, 5389 (84.5%) reported that they used EHRs. Of 5892 physicians who indicated that CPOE was relevant to their specialty, 4858 (82.5%) reported using CPOE. Physicians who used EHRs and CPOE had lower satisfaction with the amount of time spent on clerical tasks and higher rates of burnout on univariate analysis. On multivariable analysis, physicians who used EHRs (odds ratio [OR]=0.67; 95% CI, 0.57-0.79; P<.001) or CPOE (OR=0.72; 95% CI, 0.62-0.84; P<.001) were less likely to be satisfied with the amount of time spent on clerical tasks after adjusting for age, sex, specialty, practice setting, and hours worked per week. Use of CPOE was also associated with a higher risk of burnout after adjusting for these same factors (OR=1.29; 95% CI, 1.12-1.48; P<.001). Use of EHRs was not associated with burnout in adjusted models controlling for CPOE and other factors.
Conclusion:
In this large national study, physicians' satisfaction with their EHRs and CPOE was generally low. Physicians who used EHRs and CPOE were less satisfied with the amount of time spent on clerical tasks and were at higher risk for professional burnout.
Little has been written about physician stress that may be associated with electronic medical records (EMR).
We assessed relationships between the number of EMR functions, primary care work conditions, and physician satisfaction, stress and burnout.
379 primary care physicians and 92 managers at 92 clinics from New York City and the upper Midwest participating in the 2001-5 Minimizing Error, Maximizing Outcome (MEMO) Study. A latent class analysis identified clusters of physicians within clinics with low, medium and high EMR functions.
We assessed physician-reported stress, burnout, satisfaction, and intent to leave the practice, and predictors including time pressure during visits. We used a two-level regression model to estimate the mean response for each physician cluster to each outcome, adjusting for physician age, sex, specialty, work hours and years using the EMR. Effect sizes (ES) of these relationships were considered small (0.14), moderate (0.39), and large (0.61).
Compared to the low EMR cluster, physicians in the moderate EMR cluster reported more stress (ES 0.35, p=0.03) and lower satisfaction (ES -0.45, p=0.006). Physicians in the high EMR cluster indicated lower satisfaction than low EMR cluster physicians (ES -0.39, p=0.01). Time pressure was associated with significantly more burnout, dissatisfaction and intent to leave only within the high EMR cluster.
Stress may rise for physicians with a moderate number of EMR functions. Time pressure was associated with poor physician outcomes mainly in the high EMR cluster. Work redesign may address these stressors.
Background:
Despite extensive data about physician burnout, to our knowledge, no national study has evaluated rates of burnout among US physicians, explored differences by specialty, or compared physicians with US workers in other fields.
Methods:
We conducted a national study of burnout in a large sample of US physicians from all specialty disciplines using the American Medical Association Physician Masterfile and surveyed a probability-based sample of the general US population for comparison. Burnout was measured using validated instruments. Satisfaction with work-life balance was explored.
Results:
Of 27 276 physicians who received an invitation to participate, 7288 (26.7%) completed surveys. When assessed using the Maslach Burnout Inventory, 45.8% of physicians reported at least 1 symptom of burnout. Substantial differences in burnout were observed by specialty, with the highest rates among physicians at the front line of care access (family medicine, general internal medicine, and emergency medicine). Compared with a probability-based sample of 3442 working US adults, physicians were more likely to have symptoms of burnout (37.9% vs 27.8%) and to be dissatisfied with work-life balance (40.2% vs 23.2%) (P < .001 for both). Highest level of education completed also related to burnout in a pooled multivariate analysis adjusted for age, sex, relationship status, and hours worked per week. Compared with high school graduates, individuals with an MD or DO degree were at increased risk for burnout (odds ratio [OR], 1.36; P < .001), whereas individuals with a bachelor's degree (OR, 0.80; P = .048), master's degree (OR, 0.71; P = .01), or professional or doctoral degree other than an MD or DO degree (OR, 0.64; P = .04) were at lower risk for burnout.
Conclusions:
Burnout is more common among physicians than among other US workers. Physicians in specialties at the front line of care access seem to be at greatest risk.
Physician Well-Being: The Reciprocity of Practice Efficiency, Culture of Wellness, and Personal Resilience
- B Bohman
- L Dyrbye
- C Sinsky
- M Linzer
- K Olson
- S Babbott
- M Murphy
- P Devries
- M Hamidi
- M Trockel
Bohman B, Dyrbye L, Sinsky C, Linzer M,
Olson K, Babbott S, Murphy M, deVries P,
Hamidi M, Trockel M. Physician Well-Being:
The Reciprocity of Practice Efficiency, Culture
of Wellness, and Personal Resilience. NEJM
Catalyst http://catalyst.nejm.org/physicianwell-being-efficiency-wellness-resilience/. Accessed April 22, 2019.