Physician Electronic Health Record Research Articles

Variable Impact of Medical Scribes on Physician Electronic Health Record Documentation Practices: A Quantitative Analysis Across a Large, Integrated Health-System.

Medical scribes have been utilized to reduce electronic health record (EHR) associated documentation burden. Although evidence suggests benefits to scribes, no large-scale studies have quantitatively evaluated scribe impact on physician documentation across clinical settings. This study aimed to evaluate the effect of scribes on physician EHR documentation behaviors and performance. This retrospective cohort study used EHR audit log data from a large academic health system to evaluate clinical documentation for all ambulatory encounters between January 2014 and December 2019 to evaluate the effect of scribes on physician documentation behaviors. Scribe services were provided on a first-come, first-served basis on physician request. Based on a physician's scribe use, encounters were grouped into 3 categories: never using a scribe, prescribe (before scribe use), or using a scribe. Outcomes included chart closure time, the proportion of delinquent charts, and charts closed after-hours. Three hundred ninety-five physicians (23% scribe users) across 29 medical subspecialties, encompassing 1,132,487 encounters, were included in the analysis. At baseline, scribe users had higher chart closure time, delinquent charts, and after-hours documentation than physicians who never used scribes. Among scribe users, the difference in outcome measures postscribe compared with baseline varied, and using a scribe rarely resulted in outcome measures approaching a range similar to the performance levels of nonusing physicians. In addition, there was variability in outcome measures across medical specialties and within similar subspecialties. Although scribes may improve documentation efficiency among some physicians, not all will improve EHR-related documentation practices. Different strategies may help to optimize documentation behaviors of physician-scribe dyads and maximize outcomes of scribe implementation.

Explaining Variability in Electronic Health Record Effort in Primary Care Ambulatory Encounters.

Electronic health record (EHR) user interface event logs are fast providing another perspective on the value and efficiency EHR technology brings to health care. Analysis of these detailed usage data has demonstrated their potential to identify EHR and clinical process design factors related to user efficiency, satisfaction, and burnout. This study aimed to analyze the event log data across 26 different health systems to determine the variability of use of a single vendor's EHR based on four event log metrics, at the individual, practice group, and health system levels. We obtained de-identified event log data recorded from June 1, 2018, to May 31, 2019, from 26 health systems' primary care physicians. We estimated the variability in total Active EHR Time, Documentation Time, Chart Review Time, and Ordering Time across health systems, practice groups, and individual physicians. In total, 5,444 physicians (Family Medicine: 3,042 and Internal Medicine: 2,422) provided care in a total of 2,285 different practices nested in 26 health systems. Health systems explain 1.29, 3.55, 3.45, and 3.30% of the total variability in Active Time, Documentation Time, Chart Review Time, and Ordering Time, respectively. Practice-level variability was estimated to be 7.96, 13.52, 8.39, and 5.57%, respectively, and individual physicians explained the largest proportion of the variability for those same outcomes 17.09, 27.49, 17.51, and 19.75%, respectively. The most variable physician EHR usage patterns occurs at the individual physician level and decreases as you move up to the practice and health system levels. This suggests that interventions to improve individual users' EHR usage efficiency may have the most potential impact compared with those directed at health system or practice levels.

The relationship between perceptions of electronic health record usability and clinical importance of social and environmental determinants of health on provider documentation.

Social and environmental determinants of health (SEDH) data in the electronic health record (EHR) can be inaccurate and incomplete. Providers are in a unique position to impact this issue as they both obtain and enter this data, however, the variability in screening and documentation practices currently limits the ability to mobilize SEDH data for secondary uses. This study explores whether providers' perceptions of clinical importance of SEDH or EHR usability influenced data entry by analyzing two relationships: (1) provider charting behavior and clinical consideration of SEDH and (2) provider charting behavior and ease of EHR use in charting. We performed a cross-sectional study using an 11-question electronic survey to assess self-reported practices related to clinical consideration of SEDH elements, EHR usability and SEDH documentation of all staff physicians, identified using administrative listserves, at Penn State Health Hershey Medical Center during September to October 2021. A total of 201 physicians responded to and completed the survey out of a possible 2,478 identified staff physicians (8.1% response rate). A five-point Likert scale from "never" to "always" assessed charting behavior and clinical consideration. Responses were dichotomized as consistent/inconsistent and vital/not vital respectively. EHR usability was assessed as "yes" or "no" responses. Fisher's exact tests assessed the relationship between charting behavior and clinical consideration and to compare charting practices between different SEDHs. Cumulative measures were constructed for consistent charting and ease of charting. A generalized linear mixed model (GLMM) compared SDH and EDH with respect to each cumulative measure and was quantified using odds ratios (OR) and 95% confidence intervals (CI). Our results show that provider documentation frequency of an SEDH is associated with perceived clinical utility as well as ease of charting and that providers were more likely to consistently chart on SDH versus EDH. Nuances in these relationships did exist with one notable example comparing the results of smoking (SDH) to infectious disease outbreaks (EDH). Despite similar percentages of physicians reporting that both smoking and infectious disease outbreaks are vital to care, differences in charting consistency and ease of charting between these two were seen. Taken as a whole, our results suggest that SEDH quality optimization efforts cannot consider physician perceptions and EHR usability as siloed entities and that EHR design should not be the only target for intervention. The associations found in this study provide a starting point to understand the complexity in how clinical utility and EHR usability influence charting consistency of each SEDH element, however, further research is needed to understand how these relationships intersect at various levels in the SEDH data optimization process.

The impact of automatic history-taking software on data quality in the cardiology outpatient clinic: Retrospective observational study.

Healthcare delivery now mandates shorter visits despite the need for more data entry, under-mining patient-provider interaction. Furthermore, enhancing access to the outcomes of prior tests and imaging conducted on the patient, along with accurately documenting medication history, will significantly elevate the quality of healthcare service delivery. To enhance the efficiency of clinic visits, we have devised a patient-provider portal that systematically gathers symptom and clinical data from patients through a computer algorithm known as Automated Assessment of Cardiovascular Examination (AACE). We intended to assess the quality of computer-generated Electronic Health Records (EHRs) with those documented by physicians. We conducted a cross-sectional study employing a paired-sample design, focusing on individuals seeking assessment for active cardiovascular symptoms at outpatient adult cardiovascular clinics. Participants initially completed the AACE, and subsequently, in the first protocol, patients were subjected to routine care without providing the AACE forms to examining physicians. In the second protocol, the AACE form was presented to the physician before the examination, and participants were subjected to routine care. We assessed the impact of AACE forms generated through computerized history-taking method on the examination, considering various clinical outcomes and satisfaction surveys. We included non-randomized eligible patients who visited seven general cardiology outpatient clinics between September 18, 2023, and October 27, 2023. These clinics were staffed by the same physicians who were unaware of the content and details of the study. A total of 762 patients (394 patients in protocol 1 and 368 patients in protocol 2) were included in the study. The mean overall impression score for computer-generated EHRs was higher versus physician EHRs (4.2 vs. 2.6; p < .001). Our study demonstrated that EHRs created by physicians' exhibit inaccuracies or deficiencies in various pieces of information. In the second protocol, in which the AACE form was presented to the physician before the examination, it was determined that the examination time was shorter, the number of tests requested, and the number of new drugs prescribed were less. We observed that the patient-provider portal, systematically collecting symptom and clinical data from patients through a computer algorithm known as AACE, yielded records that were of higher quality, more comprehensive, better organized, and more relevant compared to those documented by physicians.

Changes in Physician Electronic Health Record Use With the Expansion of Telemedicine

Understanding the drivers of electronic health record (EHR) burden, including EHR time and patient messaging, may directly inform strategies to address physician burnout. Given the COVID-19-induced expansion of telemedicine-now used for a substantial proportion of ambulatory encounters-its association with EHR burden should be evaluated. To measure the association of the telemedicine expansion with time spent working in the EHR and with patient messaging among ambulatory physicians before and after the onset of the COVID-19 pandemic. This longitudinal cohort study analyzed weekly EHR metadata of ambulatory physicians at UCSF Health, a large academic medical center. The same EHR measures were compared for 1 year before the COVID-19 pandemic (August 2018-September 2019) with the same period 1 year after its onset (August 2020-September 2021). Multivariable regression models evaluating the association between level of telemedicine use and EHR use were then assessed after the onset of the pandemic. The sample included all physician-weeks with at least 1 scheduled half-day clinic in the 11 largest ambulatory specialties at UCSF Health. Data analyses were performed from March 1, 2022, through July 1, 2023. Physicians' weekly modality mix of either entirely face-to-face visits, mixed modalities, or entirely telemedicine. The EHR time during and outside of patient scheduled hours (PSHs), time spent documenting (normalized per 8 PSHs), and electronic messages sent to and received from patients. The study sample included 1052 physicians (437 [41.5%] men and 615 [58.5%] women) during 115 weeks, which provided 35 697 physician-week observations. Comparing the period before to the period after pandemic onset showed that physician time spent working in the EHR during PSHs increased from 4.53 to 5.46 hours per 8 PSH (difference, 0.93; 95% CI, 0.87-0.98; P < 0.001); outside of PSHs, increased from 4.29 to 5.34 hours (difference, 1.04; 95% CI, 0.95-1.14; P < 0.001); and time documenting during and outside of PSHs increased from 6.35 to 8.18 hours (difference, 1.83; 95% CI, 1.72-1.94; P < 0.001). Mean weekly messages received from patients increased from 16.76 to 30.33, and messages sent to patients increased from 13.82 to 29.83. In multivariable models, weeks with a mix of face-to-face and telemedicine (β, 0.43; 95% CI, 0.31-0.55; P < .001) visits or entirely telemedicine (β, 0.91; 95% CI, 0.74-1.09; P < .001) had more EHR time during PSHs than all face-to-face weeks, with similar results for EHR time outside of PSHs. There was no association between telemedicine use and messages received from patients, whereas mixed modalities (β, -0.90; 95% CI, -1.73 to -0.08; P = .03) and all telemedicine (β, -4.06; 95% CI, -5.19 to -2.93; P < .001) were associated with fewer messages sent to patients compared with entirely face-to-face weeks. The findings of this longitudinal cohort study suggest that telemedicine is associated with greater physician time spent working in the EHR, both during and outside of scheduled hours, mostly documenting visits and not messaging patients. Health systems may need to adjust productivity expectations for physicians and develop strategies to address EHR documentation burden for physicians.

Quantifying EHR and Policy Factors Associated with the Gender Productivity Gap in Ambulatory, General Internal Medicine

BackgroundThe gender gap in physician compensation has persisted for decades. Little is known about how differences in use of the electronic health record (EHR) may contribute.ObjectiveTo characterize how time on clinical activities, time on the EHR, and clinical productivity vary by physician gender and to identify factors associated with physician productivity.Design, Setting, and ParticipantsThis longitudinal study included general internal medicine physicians employed by a large ambulatory practice network in the Northeastern United States from August 2018 to June 2021.Main MeasuresMonthly data on physician work relative value units (wRVUs), physician and practice characteristics, metrics of EHR use and note content, and temporal trend variables.Key ResultsThe analysis included 3227 physician-months of data for 108 physicians (44% women). Compared with men physicians, women physicians generated 23.8% fewer wRVUs per month, completed 22.1% fewer visits per month, spent 4.0 more minutes/visit and 8.72 more minutes on the EHR per hour worked (all p < 0.001), and typed or dictated 36.4% more note characters per note (p = 0.006). With multivariable adjustment for physician age, practice characteristics, EHR use, and temporal trends, physician gender was no longer associated with productivity (men 4.20 vs. women 3.88 wRVUs/hour, p = 0.31). Typing/dictating fewer characters per note, relying on greater teamwork to manage orders, and spending less time on documentation were associated with higher wRVUs/hour. The 2021 E/M code change was associated with higher wRVUs/hour for all physicians: 10% higher for men physicians and 18% higher for women physicians (p < 0.001 and p = 0.009, respectively).ConclusionsIncreased team support, briefer documentation, and the 2021 E/M code change were associated with higher physician productivity. The E/M code change may have preferentially benefited women physicians by incentivizing time-intensive activities such as medical decision-making, preventive care discussion, and patient counseling that women physicians have historically spent more time performing.

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.

Physician Electronic Health Record Use After Changes in US Centers for Medicare & Medicaid Services Documentation Requirements

This cohort study examines changes in physician electronic health record (EHR) documentation time before and after changes in Centers for Medicare &amp;amp;amp; Medicaid evaluation and management requirements.

Variation in Support for Documentation Among Primary Care Physicians by Gender.

There are known gender differences in both time spent on the electronic health record (EHR) and burnout. Previous studies have described potential benefits of staff support for documentation for physician experience and EHR time. It is not known, however, to what extent availability of staff support for documentation differs by gender in the context of primary care. METHODS: This was a cross-sectional study of primary care physicians (PCPs) using data from the 2018 and 2019 National Electronic Health Records Survey administrations. After descriptively analyzing the prevalence of staff support for documentation, we used multivariable logistic regression to identify the adjusted relationship of staff support for documentation with gender. RESULTS: Among the 813 physicians who endorsed having an EHR (92.5% of sample, representing 296,854 physicians), female PCPs were significantly less likely than male PCPs (25.1% vs 37.3%; P = .04) to report having staff support for documentation. This difference was most pronounced in practices with a single physician and practices with more than 50% of patients insured by Medicaid. Gender differences persisted in analyses adjusted for practice ownership and percent of patients insured by Medicaid. CONCLUSIONS: Given positive effects of documentation support and known gender differences in burnout and EHR use times, the differences identified have important implications for the physician workforce. Future research should focus on identifying underlying reasons and potential solutions for the gender differences described.

The Impact of the COVID-19 Pandemic on Physician Electronic Health Record Use and Burden at a Canadian Mental Health Hospital.

The COVID-19 Pandemic has significantly changed the delivery of care through new workflows and models of care. However, the impact of these changes on the usage of electronic health record (EHR) systems remains unclear. This mixed method study aims to understand how EHR usage patterns changed between the pandemic onset and the pre-pandemic period at a Canadian mental health hospital, using an analysis of EHR usage log data and a qualitative focus group. An increase in after-hours EHR usage and documentation time per patient was observed, as well as a decrease in order time. Virtual care (VC) use also had an impact on time spent per patient within the EHR and after-hours EHR usage. Qualitative results highlighted physician concerns related to VC workflows and documentation, which contributed to additional EHR burden. Future work should focus on different contexts and developing relevant interventions to address these issues.

Understanding physicians' work via text analytics on EHR inbox messages.

To develop a text analytics methodology to analyze in a refined manner the drivers of primary care physicians' (PCPs') electronic health record (EHR) inboxwork. This study used 1 year (2018) of EHR inbox messages obtained from the Epic system for 184 PCPs from 18 practices. An advanced text analytics latent Dirichlet allocation model was trained on physicians' inbox message texts to identify the different work themes managed by physicians and their relative share of workload across physicians and clinics. The text analytics model identified 30 different work themes rolled up into 2 categories of medical and administrative tasks. We found that 50.8% (range across physicians, 34.5%-61.9%) of the messages were concerned with medical issues and 34.1% (range, 23.0%-48.9%) focused on administrative matters. More specifically, 13.6% (range, 7.1%-22.6%) of the messages involved ambiguous diagnosis issues, 13.2% (range, 6.9%-18.8%) involved condition management issues, 6.7% (range, 1.9%-13.4%) involved identified symptoms issues, 9.5% (range, 5.2%-28.9%) involved paperwork issues, and 17.6% (range, 9.3%-27.1%) involved scheduling issues. Additionally, there was significant variability among physicians and practices. This study demonstrated that advanced text analytics provide a reliable data-driven methodology to understand the individual physician's EHR inbox management work with a significantly greater level of detail than previous approaches. This methodology can inform decision makers on appropriate workflow redesign to eliminate unnecessary workload on PCPs and to improve cost and quality of care, as well as staff work satisfaction.

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

This study aimed to understand the association between primary care physician (PCP) proficiency with the electronic health record (EHR) system and time spent interacting with the EHR. We examined the use of EHR proficiency tools among PCPs at one large academic health system using EHR-derived measures of clinician EHR proficiency and efficiency. Our main predictors were the use of EHR proficiency tools and our outcomes focused on 4 measures assessing time spent in the EHR: (1) total time spent interacting with the EHR, (2) time spent outside scheduled clinical hours, (3) time spent documenting, and (4) time spent on inbox management. We conducted multivariable quantile regression models with fixed effects for physician-level factors and time in order to identify factors that were independently associated with time spent in the EHR. Across 441 primary care physicians, we found mixed associations between certain EHR proficiency behaviors and time spent in the EHR. Across EHR activities studied, QuickActions, SmartPhrases, and documentation length were positively associated with increased time spent in the EHR. Models also showed a greater amount of help from team members in note writing was associated with less time spent in the EHR and documenting. Examining the prevalence of EHR proficiency behaviors may suggest targeted areas for initial and ongoing EHR training. Although documentation behaviors are key areas for training, team-based models for documentation and inbox management require further study. A nuanced association exists between physician EHR proficiency and time spent in the EHR.

Analysis of Electronic Health Record Use and Clinical Productivity and Their Association With Physician Turnover

Physician turnover takes a heavy toll on patients, physicians, and health care organizations. Survey research has established associations of electronic health record (EHR) use with professional burnout and reduction in professional effort, but these findings are subject to response fatigue and bias. To evaluate the association of physician productivity and EHR use patterns, as determined by vendor-derived EHR use data platforms, with physician turnover. This retrospective cohort study was conducted among nonteaching ambulatory physicians at a large ambulatory practice network based in New England. Data were collected from March 2018 to February 2020. Physician departure from the practice network; 4 time-based core measures of EHR use, normalized to 8 hours of scheduled clinical time; teamwork, percentage of a physician's orders that are placed by other members of the care team; and productivity measures of patient volume, intensity, and demand. Among 335 physicians assessed for eligibility, 314 unique physicians (89.2%) were included in the analysis (123 [39%] women; 100 [32%] aged 45-54 years), with 5663 physician-months of data. The turnover rate was 5.1%/year (32 of 314 physicians). Physicians completed a mean 2.6 appointments/hour (95% CI, 2.5-2.6 appointments/hour) and 206 appointments/month (95% CI, 197-215 appointments/month) with 5.5 hours (95% CI, 5.3-5.8 hours) of EHR time for every 8 hours of scheduled patient time. After controlling for gender, medical specialty, and time, the following variables were associated with turnover: inbox time (odds ratio [OR], 0.70; 95% CI, 0.61-0.82; P < .001), teamwork (OR, 0.68; 95% CI, 0.52-0.87; P = .003), demand (ie, proportion of available appointments filled: OR, 0.49; 95% CI, 0.35-0.70; P < .001), and age 45 to 54 years vs 25 to 34 years (OR, 0.19; 95% CI, 0.04-0.93; P = .04). In this study, physician productivity and EHR use metrics were associated with physician departure. Prospectively tracking these metrics could identify physicians at high risk of departure who would benefit from early, team-based, targeted interventions. The counterintuitive finding that less time spent on the EHR (in particular inbox management) was associated with physician departure warrants further investigation.

Impact of a medical scribe on clinical efficiency and quality in an academic general internal medicine practice

BackgroundScribes have been proposed as an intervention to decrease physician electronic health record (EHR) workload and improve clinical quality. We aimed to assess the impact of a scribe on clinical efficiency and quality in an academic internal medicine practice.MethodsSix faculty physicians worked with one scribe at an urban academic general internal medicine clinic April through June 2017. Patient visits during the 3 months prior to intervention (baseline, n = 789), unscribed visits during the intervention (concurrent control, n = 605), and scribed visits (n = 579) were included in the study. Clinical efficiency outcomes included time to close encounter, patient time in clinic, and number of visits per clinic session. Quality outcomes included EHR note quality, rates of medication and immunization review, population of patient instructions, reconciliation of outside information, and completion of preventative health recommendations.ResultsMedian time to close encounter (IQR) was lower for scribed visits [0.4 (4.8) days] compared to baseline and unscribed visits [1.2 (5.9) and 2.9 (5.4) days, both p < 0.001]. Scribed notes were more likely to have a clear history of present illness (HPI) [OR = 7.30 (2.35–22.7), p = 0.001] and sufficient HPI information [OR = 2.21 (1.13–4.35), p = 0.02] compared to unscribed notes. Physicians were more likely to review the medication list during scribed vs. baseline visits [OR = 1.70 (1.22–2.35), p = 0.002]. No differences were found in the number of visits per clinic session, patient time in clinic, completion of preventative health recommendations, or other outcomes.ConclusionsWorking with a scribe in an academic internal medicine practice was associated with more timely documentation.

Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis.

ObjectiveTo derive 7 proposed core electronic health record (EHR) use metrics across 2 healthcare systems with different EHR vendor product installations and examine factors associated with EHR time.Materials and MethodsA cross-sectional analysis of ambulatory physicians EHR use across the Yale-New Haven and MedStar Health systems was performed for August 2019 using 7 proposed core EHR use metrics normalized to 8 hours of patient scheduled time.ResultsFive out of 7 proposed metrics could be measured in a population of nonteaching, exclusively ambulatory physicians. Among 573 physicians (Yale-New Haven N = 290, MedStar N = 283) in the analysis, median EHR-Time8 was 5.23 hours. Gender, additional clinical hours scheduled, and certain medical specialties were associated with EHR-Time8 after adjusting for age and health system on multivariable analysis. For every 8 hours of scheduled patient time, the model predicted these differences in EHR time (P < .001, unless otherwise indicated): female physicians +0.58 hours; each additional clinical hour scheduled per month −0.01 hours; practicing cardiology −1.30 hours; medical subspecialties −0.89 hours (except gastroenterology, P = .002); neurology/psychiatry −2.60 hours; obstetrics/gynecology −1.88 hours; pediatrics −1.05 hours (P = .001); sports/physical medicine and rehabilitation −3.25 hours; and surgical specialties −3.65 hours.ConclusionsFor every 8 hours of scheduled patient time, ambulatory physicians spend more than 5 hours on the EHR. Physician gender, specialty, and number of clinical hours practicing are associated with differences in EHR time. While audit logs remain a powerful tool for understanding physician EHR use, additional transparency, granularity, and standardization of vendor-derived EHR use data definitions are still necessary to standardize EHR use measurement.

Novel Nonproprietary Measures of Ambulatory Electronic Health Record Use Associated with Physician Work Exhaustion.

Accumulating evidence indicates an association between physician electronic health record (EHR) use after work hours and occupational distress including burnout. These studies are based on either physician perception of time spent in EHR through surveys which may be prone to bias or by utilizing vendor-defined EHR use measures which often rely on proprietary algorithms that may not take into account variation in physician's schedules which may underestimate time spent on the EHR outside of scheduled clinic time. The Stanford team developed and refined a nonproprietary EHR use algorithm to track the number of hours a physician spends logged into the EHR and calculates the Clinician Logged-in Outside Clinic (CLOC) time, the number of hours spent by a physician on the EHR outside of allocated time for patient care. The objective of our study was to measure the association between CLOC metrics and validated measures of physician burnout and professional fulfillment. Physicians from adult outpatient Internal Medicine, Neurology, Dermatology, Hematology, Oncology, Rheumatology, and Endocrinology departments who logged more than 8 hours of scheduled clinic time per week and answered the annual wellness survey administered in Spring 2019 were included in the analysis. We observed a statistically significant positive correlation between CLOC ratio (defined as the ratio of CLOC time to allocated time for patient care) and work exhaustion (Pearson's r = 0.14; p = 0.04), but not interpersonal disengagement, burnout, or professional fulfillment. The CLOC metrics are potential objective EHR activity-based markers associated with physician work exhaustion. Our results suggest that the impact of time spent on EHR, while associated with exhaustion, does not appear to be a dominant factor driving the high rates of occupational burnout in physicians.

Physician perceptions of documentation methods in electronic health records.

This study sought to determine physician, specialty and practice factors influencing choice of method for electronic health record (EHR) documentation: direct typing (DT), electronic transcription (ET), human transcription (HT), and scribes. A survey assessing physician documentation practices was developed and distributed online. The primary outcome was the proportion of physicians using each method. Secondary outcomes were provider-rated accuracy, efficiency, and ease of navigation on a 1-5 Likert scale. Means were compared using linear mixed models with Bonferroni adjustment. The 818 respondents were mostly outpatient (46%) adult (79%) physicians, practiced for a mean 15.8 years, and used DT for EHR documentation (72%). Emergency physicians were more likely to use scribes (p < 0.0001). DT was rated less efficient than all other methods (p < 0.0001). ET was rated less accurate than DT (p < 0.001) and HT (p < 0.001). HT was rated less easy to navigate than DT (p = 0.002) and scribe (p < 0.001), and ET less than scribe (p = 0.002). Two hundred and forty-three respondents provided free-text comments that further described opinions. DT was the most commonly used EHR method but rated least efficient. Scribes were rated easy to navigate and efficient but infrequently used outside of emergency settings. Further innovation is needed to design systems responsive to all physician EHR needs.

Analysing EHR navigation patterns and digital workflows among physicians during ICU pre-rounds.

Background:Some physicians in intensive care units (ICUs) report that electronic health records (EHRs) can be cumbersome and disruptive to workflow. There are significant gaps in our understanding of the physician–EHR interaction.Objective:To better understand how clinicians use the EHR for chart review during ICU pre-rounds through the characterisation and description of screen navigation pathways and workflow patterns.Method:We conducted a live, direct observational study of six physician trainees performing electronic chart review during daily pre-rounds in the 30-bed medical ICU at a large academic medical centre in the Southeastern United States. A tailored checklist was used by observers for data collection.Results:We observed 52 distinct live patient chart review encounters, capturing a total of 2.7 hours of pre-rounding chart review activity by six individual physicians. Physicians reviewed an average of 8.7 patients (range = 5–12), spending a mean of 3:05 minutes per patient (range = 1:34–5:18). On average, physicians visited 6.3 (±3.1) total EHR screens per patient (range = 1–16). Four unique screens were viewed most commonly, accounting for over half (52.7%) of all screen visits: results review (17.9%), summary/overview (13.0%), flowsheet (12.7%), and the chart review tab (9.1%). Navigation pathways were highly variable, but several common screen transition patterns emerged across users. Average interrater reliability for the paired EHR observation was 80.0%.Conclusion:We observed the physician–EHR interaction during ICU pre-rounds to be brief and highly focused. Although we observed a high degree of “information sprawl” in physicians’ digital navigation, we also identified common launch points for electronic chart review, key high-traffic screens and common screen transition patterns.Implications:From the study findings, we suggest recommendations towards improved EHR design.

Impact of Patient Census and Admission Mortality on Pediatric Intensive Care Unit Attending Electronic Health Record Activity: A Preliminary Study.

Physicians may spend a significant amount of time using the electronic health record (EHR), but this is understudied in the pediatric intensive care unit (PICU). The objective of this study is to quantify PICU attending physician EHR usage and determine its association with patient census and mortality scores. During the year 2016, total EHR, chart review, and documentation times of 7 PICU physicians were collected retrospectively utilizing an EHR-embedded time tracking software package. We examined associations between documentation times and patient census and maximum admission mortality scores. Odds ratios (ORs) are reported per 1-unit increase in patient census and mortality scores. Overall, total daily EHR usage time (median time [hh:mm] [25th, 75th percentile]) was 2:10 (1:31, 3:08). For all hours (8 a.m.-8 a.m.), no strong association was noted between total EHR time, chart review, and documentation times and patient census, Pediatric Index of Mortality 2 (PIM2), or Pediatric Risk of Mortality 3 (PRISM3) scores. For regular hours (8 a.m.-7 p.m.), no strong association was noted between total EHR, chart review, and documentation times and patient census, PIM2, or PRISM3 scores. When patient census was higher, the odds of EHR after-hour usage (7 p.m.-8 a.m.) was higher (OR 1.262 [1.135, 1.403], p < 0.0001), but there were no increased odds with PIM2 (OR 1.090 [0.956, 1.242], p = 0.20) and PRISM3 (OR 1.010 [0.984, 1.036], p = 0.47) scores. A subset of physicians spent less time performing EHR-related tasks when patient census and admission mortality scores were elevated. We performed a novel evaluation of physician EHR workflow in our PICU. Our pediatric critical care physicians spend approximately 2 hours (out of an expected 10-hour shift) each service day using the EHR, but there was no strong or consistent association between EHR usage and patient census or mortality scores. Future larger scale studies are needed to ensure validity of these results.

A Daily Hospital Progress Note that Increases Physician Usability of the Electronic Health Record by Facilitating a Problem-Oriented Approach to the Patient and Reducing Physician Clerical Burden.

We suggest changes in the electronic health record (EHR) in hospitalized patients to increase EHR usability by optimizing the physician's ability to approach the patient in a problem-oriented fashion and by reducing physician data entry and chart navigation. The framework for these changes is a Physician's Daily Hospital Progress Note organized into 3 sections: Subjective, Objective, and a combined Assessment and Plan section, subdivided by problem titles. The EHR would consolidate information for each problem by: 1) juxtaposing to each problem title relevant medications, key durable results, and limitations; 2) entering in the running lists under Assessment and Plan the most relevant information for that day, including abbreviated versions of relevant reports; and 3) generating a flow sheet in a problem's progress note for any key results tracked daily. To reduce physician EHR navigation, the EHR would place in the Objective section abbreviated versions of notes of other physicians, nurses, and allied health professionals as well as recent orders. The physician would enter only the analysis and plan and new information not included in the EHR. The consolidation of information for each problem would facilitate physician communication at points of transition of care including generation of a problem-oriented discharge summary.