Electronic Health Record Usability Research Articles

Virtual Sprint Outpatient Electronic Health Record Training and Optimization Effect on Provider Burnout.

This study aimed to develop a virtual electronic health record (EHR) training and optimization program and evaluate the impact of the virtual model on provider and staff burnout and electronic health record (EHR) experience. UCHealth created and supported a multidisciplinary EHR optimization and training program, known as the Epic Sprint Program. The Sprint Team conducted dozens of onsite Sprint events over the course of several years prior to the pandemic but transitioned to a fully virtual program and successfully "sprinted" 21 outpatient clinics from May to December 2020. Core program components of group and 1:1 training, workflow analysis, and new or adjusted EHR build were unchanged from the onsite model. Pre- and post-Sprint surveys provided detailed, objective data about EHR usability, EHR proficiency, job satisfaction, and burnout. The EHR Net Promoter Score (NPS), a likelihood to recommend metric, increased by 39 points (-3 pre and 36 post; p < 0.001) for providers and 29 points (8 pre and 37 post; p = 0.001) for staff post-Sprint. Positive provider (NPS = +53) and staff (NPS = +47) NPS scores indicated a high likelihood to recommend the Sprint Program. Post-Sprint surveys also reflect an increase in providers (10%; p = 0.04) and staff (9%; 0.13) who indicated "no burnout" or "did not feel burned out." The UCHealth Sprint Team transitioned this comprehensive, enterprise level initiative from an onsite model to a fully virtual EHR training and optimization program during the first few months of the novel coronavirus disease (COVID-19) pandemic. Despite this change in program delivery, survey data clearly demonstrated improved EHR satisfaction, a high likelihood to recommend a sprint to a friend or colleague, and a trend toward burnout reduction in providers and staff. Changing an existing on-site EHR optimization program to a purely virtual format can be successful, and this study showed improved provider and staff EHR satisfaction with reduced burnout.

Design, Implementation, Utilization, and Sustainability of a Fast Healthcare Interoperability Resources-Based Inpatient Rounding List.

We designed and implemented an application programming interface (API)-based electronic health record (EHR)-integrated rounding list and evaluated acceptability, clinician satisfaction, information accuracy, and efficiency related to the application. We developed and integrated an application, employing iterative design techniques with user feedback. EHR and application user action logs, as well as hospital safety reports, were evaluated. Rounding preparation characteristics were obtained through surveys before and after application integration. To evaluate usability, inpatient providers, including residents, fellows, and attendings were surveyed 2 weeks prior to and 6 months after enterprise-wide EHR application integration. Our primary outcome was provider time savings measured by user action logs; secondary outcomes include provider satisfaction. The application was widely adopted by inpatient providers, with more than 69% of all inpatients queried by the application within 6 months of deployment. Application utilization was sustained throughout the study period with 79% (interquartile range [IQR]: 76, 82) of enterprise-wide unique patients accessed per weekday. EHR action logs showed application users spent -3.24 minutes per day (95% confidence interval [CI]: -6.8, 0.33), p = 0.07 within the EHR compared with nonusers. Median self-reported chart review time for attendings decreased from 30 minutes (IQR: 15, 60) to 20 minutes (IQR: 10, 45) after application integration (p = 0.04). Self-reported sign-out preparation time decreased by a median of 5 minutes (p < 0.01), and providers were better prepared for hand-offs (p = 0.02). There were no increased safety reports during the study period. This study demonstrates successful integration of a rounding application within a commercial EHR using APIs. We demonstrate increasing both provider-reported satisfaction and time savings. Rounding lists provided more accurate and timely information for rounds. Application usage was sustained across multiple specialties at 42 months. Other application designers should consider data density, optimization of provider workflows, and using real-time data transfer using novel tools when designing an application.

Not another box to check! Using the UTAUT to explore nurses' psychological adaptation to electronic health record usability

As the integration of electronic health records (EHRs) continues to expand throughout healthcare organizations worldwide, nurses are faced with the challenge to acclimate to a dynamic technology-based environment of patient care. As technology advances, EHR usability may influence nurses' clinical performance and require nurses to adapt to a wide range of situations associated with electronic documentation. While perceived benefits of EHRs include improvements in healthcare delivery and patient outcomes, there are also unintended consequences associated with EHR usability. The aim of this article is to explore dimensions of EHR usability that may influence nurses' psychological adaptation to the use of EHRs in daily practice. The unified theory of acceptance and use of technology (UTAUT) consists of four constructs theorized to have a direct influence on end-user behavior and acceptance of technology: performance expectancy, effort expectancy, social influence, and facilitating conditions. The UTAUT provides the framework to explore EHR usability as found in literature and describe the positive and negative psychological responses of nurses related to the use of EHRs in daily practice. Integration of EHRs into daily nursing practice can result in positive experiences or have a negative impact on nurses ability to perform their role as patient caregivers. While integration of EHRs into healthcare systems can facilitate improvements in patient outcomes, the delivery of patient care and nurses' daily practices can simultaneously be complicated by EHR usability issues. Although positive and negative experiences of nurses in relationship to EHR usability can be found in literature, there is limited evidence on nurses' psychological adaptation to use of EHRs. Further research on EHR usability is needed based on nursing perspectives and feedback to determine the psychological impact EHRs exert on nurses, discover effective methods for resolving issues, and promote positive trends associated with EHR usability.

Acute Care Surgeons Spend More Time than General Surgeons on the Electronic Health Record (EHR).

The paradigm of Acute Care Surgery (ACS) emerged in response to decreasing operative opportunities for trauma surgeons and increasing need for surgical coverage in disciplines to which the expertise of trauma surgeons naturally extends. While the continued evolution of this specialty remains largely beneficial, unintended consequences may have arisen along the way. One aspect of ACS that remains to be thoroughly investigated is the impact of the electronic health record (EHR). The purpose of this study is to objectively quantify EHR usage for ACS and compare it to other general surgery specialties. EHR user data were collected for fifteen ACS attendings and thirty-seven general surgery attendings from October 2014 to September 2019. Comparative analysis was conducted using two-tailed t-tests. Subgroup analysis was conducted for subspecialties included in the general surgery group. ACS attendings opened almost 3 times as many charts as general surgery attendings per month (180 vs 64 charts/month, P < .0001), and ultimately spent more time on the EHR as a result (10 vs 6.4 hours/month, P < .0001). Documentation was the most time consuming EHR task for both groups. Although ACS attendings spent less overall time per patient chart, the proportion of time spent on certain EHR tasks was similar to that of general surgery colleagues. The EHR imposes a disproportionate burden on ACS attendings compared to their general surgery counterparts, and additional study is warranted to improve usage. EHR usage burden has workforce implications for trainees considering a career in ACS.

Survey of Information Exchange and Advanced Use of Other Health Information Technology in Primary Care Settings: Capabilities In and Outside of the Safety Net.

Advanced use of health information technology (IT) functionalities can support more comprehensive, coordinated, and patient-centered primary care services. Safety net practices may benefit disproportionately from these investments, but it is unclear whether IT use in these settings has kept pace and what organizational factors are associated with varying use of these features. The aim was to estimate advanced use of health IT use in safety net versus nonsafety net primary care practices. We explore domains of patient engagement, population health management (decision support and registries), and electronic information exchange. We examine organizational characteristics that may differentially predict advanced use of IT across these settings, with a focus on health system ownership and/or membership in an independent practice network as key factors that may indicate available incentives and resources to support these efforts. We conduct cross-sectional analysis of a national survey of physician practices (n=1776). We use logistic regression to predict advanced IT use in each of our domains based on safety net status and other organizational characteristics. We then use interaction models to assess whether ownership or network membership moderate the relationship between safety net status and advanced use of health IT. Health IT use was common across primary care practices, but advanced use of health IT functionalities ranged only from 30% to 50% use. Safety net settings have kept pace with adoption of features for patient engagement and population management, yet lag in information exchange capabilities compared with nonsafety net practices (odds ratio=0.52 for federally qualified health centers, P<0.001; odds ratio=0.66 for other safety net, P=0.03). However, when safety net practices are members of a health system or practice network, health IT capabilities are comparable to nonsafety net sites. All outpatient settings would benefit from improved electronic health record usability and implementation support that facilitates advanced use of health IT. Safety net practices, particularly those without other sources of centralized support, need targeted resources to maintain equitable access to information exchange capabilities.

Is Electronic Health Record Safety a Paradox?

Is Electronic Health Record Safety a Paradox?

Hematology Patient Explorer - an Informatics Infrastructure and Web Application Empowering Clinicians and Researchers to Use Electronic Health Record Information to Identify Clinical Cohorts of Interest

Introduction: The widespread adoption of electronic health records (EHR) in the US (Adler-Milstein and Jha 2017) presents an opportunity to transform healthcare into rapidly learning health organizations and systems (Etheredge 2007; Abernethy et al. 2010) that use routinely collected clinical data in the course of care to generate evidence, address information disparities in patients underrepresented in clinical trials, such as those who are older, belong to ethnic minorities, or are in medically underserved areas, and continuously improve the quality of care delivered.(Rivera et al. 2019; Penberthy, Rivera, and Ward 2019) Unfortunately, this potential remains largely unrealized due to deficiencies in EHR interoperability (Holmgren, Patel, and Adler-Milstein 2017) and usability.(Dunn Lopez et al. 2021) EHR information remains largely unstructured due to the nature of the patient-clinician interaction and current user interfaces where structured data entry is burdensome.(Khairat et al. 2019) At the University of Utah Huntsman Cancer Institute division of Hematology, clinicians as well as clinical and translational researchers often need detailed information on patients seen at the cancer center to plan and conduct research and evaluate and improve the quality of care delivered. Previous efforts to address these needs relied on a clinical data science and health informatics staff working with clinicians to identify patient cohorts of interest. As part of an effort to improve the efficiency of this service, decrease the latency in information provision, and serve a larger number of clinicians and researchers, we designed and implemented a highly usable, scalable, health information technology solution that allows clinicians and researchers to identify, in near real time, cohorts of interest, based on patient and disease characteristics.Methods: Common information needs at the division were assessed by identifying key stakeholders, including division leadership, clinicians, researchers, and health informatics leadership and staff. A team was formed to include overlapping expertise in Hematology, clinical informatics and data science, and prior experience in extraction of clinical information from EHR data warehouses to generate evidence on patient practices and outcomes. Information sources and architectures were evaluated on their comprehensiveness, validity, extensibility, and ability to integrate multiple data sources. A modern web-based interface was designed to mirror the steps clinicians and clinical researchers frequently used to identify cohorts of interest, provide guidance for these users, and generate population level and patient level information. Usability testing included rounds of initial internal testing, followed by a round of closed beta testing.Results: A data lake architecture was implemented to ingest, harmonize and stage information from various data sources, including the Enterprise Data Warehouse, Tumor Registry, and other data silos. Data cleaning and harmonization was done using Python. A web application using ‘Dash’ was implemented with four steps split into four consecutive panes. The first two focused on cohort identification using diagnosis (first pane), and patient and disease characteristics (pane 2). Users first input keywords that allow them to identify diagnoses of interest based on ICDO-3 codes. Users can select multiple codes at this stage. In the next step, users can filter down their cohort based on patient and disease characteristics, such as sex, age, year of initial diagnosis, grade and stage of disease, and others. Once all desired refinements to the pilot cohort are made, users move on to the third tab, which displays customizable population level information, such as number of diagnoses by year, sex, or age. Finally, the fourth tab presents individual level data such as Patient Medical Record Numbers, age, or ICDO-3 diagnosis descriptions. Based on this output, users can return to the initial selection criteria and adjust them. Users are able to download or export selection criteria and query results for future work.Conclusion: We describe the process, roles, and informatics infrastructure and tools to implement a web interface that allows clinicians and researchers to leverage EHR information to identify cohorts of patients for research and quality improvement. Further research will focus on tool usability and scope. DisclosuresDeininger: Sangamo: Consultancy, Membership on an entity's Board of Directors or advisory committees; Fusion Pharma, Medscape, DisperSol: Consultancy; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Part of a Study Management Committee, Research Funding; SPARC, DisperSol, Leukemia & Lymphoma Society: Research Funding; Novartis: Consultancy, Research Funding; Incyte: Consultancy, Honoraria, Research Funding; Blueprint Medicines Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Part of a Study Management Committee, Research Funding.

Start using EHR, how satisfy are the doctors and nurses?

Electronic health record (EHR) system has many advantages. However, the implementation of it is challenging in a limited resources. Alongside with the challenge related to big change that clinicians have to adapt with. This causes hospital around the world changes the patient documentation, from paper based health record to EHR system. Evaluation about EHR system implementation is a crucial things. One of her evaluation implementation can be seen through measuring EHR user satisfaction. To determine physicians’ and nurses’ satisfaction in EHR implementation. This was a cross-sectional designed descriptive analytical research. There were 52 respondents consists of physicians and nurses who work in the out patient unit involved in the study. Data were collected using Electronic Health Record Nurse Satisfaction (EHRNS) developed by Sockolow et al. The mean of the effect of EHR in patient outcomes is equivalent to M = 3.9 ± 0.7 in nurses and M = 4.1 ± 0.8 in physicians. The effect of EHR usage on the patient's comfort is equivalent to M = 3.8 ± 0.5 in nurses and M = 3.7 ± 0.8 in doctors. EHR training is equivalent to M = 4.6 ± 0.6 in nurses and M = 4.3 ± 0.7 in doctors. There is no significance difference in satisfaction between nurses and doctors. Overall, nurses and physicians were satisfied with some functions in EHR system. However, there are some functions that didn’t satisfy the users and need to be improved.

Nurses and physicians’ perceptions on the Electronic Health Record implementation

Electronic Health Record (EHR) implementation is recommended to improve quality of patient care through information accessibility. Nurses and physicians as the EHR users play pivotal roles in the successful implementation of EHR. This study was aimed to understand clinicians’ perceptions on EHR implementation. This study was a descriptive quantitative with a cross sectional design. A questionnaire developed by Houser (2008) was translated and modified to inquire clinicians’ perception on EHR implementation. The data was analyzed to provide the description of clinicians’ perception. There were 152 clinicians who work at inpatient unit in an academic hospital involved in the study (137 nurses and 41 physicians). Most clinicians (87.6% physicians and 92.7% nurses) agreed that EHR bring ease and speed in sharing information, could improve their workflow, and healthcare quality. Lack of training could be the biggest barrier for nurses (60.6%). Problem in Internet connection perceived by physicians (51.2%) is the biggest barrier to implementation. Physicians have the same perception with nurses on the driving factor of EHR implementation, which are EHR capability in sharing information and improve healthcare services quality. There was a different perception on the barrier of EHR implementation between physicians and nurses.

Pilot Testing of Simulation in the Evaluation of a Novel, Rapidly Deployable Electronic Health Record for use in Disaster Intensive Care.

The SARS-CoV-2 pandemic has highlighted the need for rapid creation and management of ICU field hospitals with effective remote monitoring which is dependent on the rapid deployment and integration of an Electronic Health Record (EHR). We describe the use of simulation to evaluate a rapidly scalable hub-and-spoke model for EHR deployment and monitoring using asynchronous training. We adapted existing commercial EHR products to serve as the point of entry from a simulated hospital and a separate system for tele-ICU support and monitoring of the interfaced data. To train our users we created a modular video-based curriculum to facilitate asynchronous training. Effectiveness of the curriculum was assessed through completion of common ICU documentation tasks in a high-fidelity simulation. Additional endpoints include assessment of EHR navigation, user satisfaction (Net Promoter), system usability (System Usability Scale-SUS), and cognitive load (NASA-TLX). A total of 5 participants achieved a 100% task completion on all domains except ventilator data (91%). Systems demonstrated high degrees of satisfaction (Net Promoter = 65.2), acceptable usability (SUS = 66.5), and acceptable cognitive load (NASA-TLX = 41.5); with higher levels of cognitive load correlating with the number of screens employed. Clinical usability of a comprehensive and rapidly deployable EHR was acceptable in an intensive care simulation which was preceded by < 1 hour of video education about the EHR. This model should be considered in plans for integrated clinical response with remote and accessory facilities.

Time and Clerical Burden Posed by the Current Electronic Health Record for Orthopaedic Surgeons.

The electronic health record (EHR) has become an integral part of modern medical practice. The balance of benefit versus burden of a required EHR remains inconclusive, with many studies identifying increasing physician burnout and less face-to-face patient contact because of increasing documentation demands. Few studies have investigated EHR burden in orthopaedic surgery practice. This study aimed to characterize and compare EHR usage patterns and time allocation within EHR between orthopaedic surgeons, other surgeons, and medicine physicians at an academic medical center. EHR usage was digitally tracked within a large academic medical center. EHR usage data were compiled for all physicians seeing outpatients from April 2018 to June 2019. The tracking metrics included time spent answering messages, typing notes, reviewing laboratories and imaging, reading notes, and placing orders. Physicians were subdivided between orthopaedic surgeons, other surgeons, and nonsurgeon/medical specialties. Statistical comparisons using a two-sample t-test were done between orthopaedic surgeon EHR usage patterns and other surgeons, in addition to orthopaedic surgeons versus nonsurgeons. One thousand sixty physicians including 28 full-time orthopaedic surgeons, 134 other surgeons, and 898 nonsurgical medicine physicians met inclusion criteria. Orthopaedic surgeons saw on average 31 patients per office day compared with other surgeons at 18 patients per office day (P < 0.01) and nonsurgeons at 12 patients per office day (P < 0.01). Orthopaedic surgeons received more EHR messages while also being more efficient at answering EHR messages compared with other surgeons and nonsurgeons (P < 0.01). EHR tasks, including answering messages, placing orders, chart review, writing notes, and reviewing imaging, consumed 58% of an orthopaedic surgeon's scheduled office day with the largest contribution from required note writing. In academic orthopaedic practice, EHR use has surpassed face-to-face patient time, consuming 58% of orthopaedic surgeons' clinical days. With the previously shown correlation between EHR burden and physician burnout, targeted interventions to increase efficiency and off-load EHR burden are necessary to sustain a successful orthopaedic practice.

Predicting next-day discharge via electronic health record access logs.

Hospital capacity management depends on accurate real-time estimates of hospital-wide discharges. Estimation by a clinician requires an excessively large amount of effort and, even when attempted, accuracy in forecasting next-day patient-level discharge is poor. This study aims to support next-day discharge predictions with machine learning by incorporating electronic health record (EHR) audit log data, a resource that captures EHR users' granular interactions with patients' records by communicating various semantics and has been neglected in outcome predictions. This study focused on the EHR data for all adults admitted to Vanderbilt University Medical Center in 2019. We learned multiple advanced models to assess the value that EHR audit log data adds to the daily prediction of discharge likelihood within 24 h and to compare different representation strategies. We applied Shapley additive explanations to identify the most influential types of user-EHR interactions for discharge prediction. The data include 26 283 inpatient stays, 133 398 patient-day observations, and 819 types of user-EHR interactions. The model using the count of each type of interaction in the recent 24 h and other commonly used features, including demographics and admission diagnoses, achieved the highest area under the receiver operating characteristics (AUROC) curve of 0.921 (95% CI: 0.919-0.923). By contrast, the model lacking user-EHR interactions achieved a worse AUROC of 0.862 (0.860-0.865). In addition, 10 of the 20 (50%) most influential factors were user-EHR interaction features. EHR audit log data contain rich information such that it can improve hospital-wide discharge predictions.

Measuring Collaboration Through Concurrent Electronic Health Record Usage: Network Analysis Study.

BackgroundCollaboration is vital within health care institutions, and it allows for the effective use of collective health care worker (HCW) expertise. Human-computer interactions involving electronic health records (EHRs) have become pervasive and act as an avenue for quantifying these collaborations using statistical and network analysis methods.ObjectiveWe aimed to measure HCW collaboration and its characteristics by analyzing concurrent EHR usage.MethodsBy extracting concurrent EHR usage events from audit log data, we defined concurrent sessions. For each HCW, we established a metric called concurrent intensity, which was the proportion of EHR activities in concurrent sessions over all EHR activities. Statistical models were used to test the differences in the concurrent intensity between HCWs. For each patient visit, starting from admission to discharge, we measured concurrent EHR usage across all HCWs, which we called temporal patterns. Again, we applied statistical models to test the differences in temporal patterns of the admission, discharge, and intermediate days of hospital stay between weekdays and weekends. Network analysis was leveraged to measure collaborative relationships among HCWs. We surveyed experts to determine if they could distinguish collaborative relationships between high and low likelihood categories derived from concurrent EHR usage. Clustering was used to aggregate concurrent activities to describe concurrent sessions. We gathered 4 months of EHR audit log data from a large academic medical center’s neonatal intensive care unit (NICU) to validate the effectiveness of our framework.ResultsThere was a significant difference (P<.001) in the concurrent intensity (proportion of concurrent activities: ranging from mean 0.07, 95% CI 0.06-0.08, to mean 0.36, 95% CI 0.18-0.54; proportion of time spent on concurrent activities: ranging from mean 0.32, 95% CI 0.20-0.44, to mean 0.76, 95% CI 0.51-1.00) between the top 13 HCW specialties who had the largest amount of time spent in EHRs. Temporal patterns between weekday and weekend periods were significantly different on admission (number of concurrent intervals per hour: 11.60 vs 0.54; P<.001) and discharge days (4.72 vs 1.54; P<.001), but not during intermediate days of hospital stay. Neonatal nurses, fellows, frontline providers, neonatologists, consultants, respiratory therapists, and ancillary and support staff had collaborative relationships. NICU professionals could distinguish high likelihood collaborative relationships from low ones at significant rates (3.54, 95% CI 3.31-4.37 vs 2.64, 95% CI 2.46-3.29; P<.001). We identified 50 clusters of concurrent activities. Over 87% of concurrent sessions could be described by a single cluster, with the remaining 13% of sessions comprising multiple clusters.ConclusionsLeveraging concurrent EHR usage workflow through audit logs to analyze HCW collaboration may improve our understanding of collaborative patient care. HCW collaboration using EHRs could potentially influence the quality of patient care, discharge timeliness, and clinician workload, stress, or burnout.

Resident Physician Experience and Duration of Electronic Health Record Use.

Electronic health records (EHRs) demand a significant amount of physician time for documentation, orders, and communication during care delivery. Resident physicians already work long hours as they gain experience and develop both clinical and socio-technical skills. Measure how much time resident physicians spend in the EHR during clinic hours and after-hours, and how EHR usage changes as they gain experience over a 12-month period. Longitudinal descriptive study where participants were 622 resident physicians across postgraduate year cohorts (of 948 resident physicians at the institution, 65.6%) working in an ambulatory setting from July 2017 to June 2018. Time spent in the EHR per patient, patients records documented per day, and proportion of EHR time spent after-hours were the outcome, while the number of months of ambulatory care experience was the predictor. Resident physicians spent an average of 45.6 minutes in the EHR per patient, with 13.5% of that time spent after-hours. Over 12 months of ambulatory experience, resident physicians reduced their EHR time per patient and saw more patients per day, but the proportion of EHR time after-hours did not change. Resident physicians spend a significant amount of time working in the EHR, both during and after clinic hours. While residents improve efficiency in reducing EHR time per patient, they do not reduce the proportion of EHR time spent after-hours. Concerns over the impact of EHRs on physician well-being should include recognition of the burden of EHR usage on early-career physicians.

Measuring Electronic Health Record Use in the Pediatric ICU Using Audit-Logs and Screen Recordings.

Time spent in the electronic health record (EHR) has been identified as an important unit of measure for health care provider clinical activity. The lack of validation of audit-log based inpatient EHR time may have resulted in underuse of this data in studies focusing on inpatient patient outcomes, provider efficiency, provider satisfaction, etc. This has also led to a dearth of clinically relevant EHR usage metrics consistent with inpatient provider clinical activity. The aim of our study was to validate audit-log based EHR times using observed EHR-times extracted from screen recordings of EHR usage in the inpatient setting. This study was conducted in a 36-bed pediatric intensive care unit (PICU) at Lucile Packard Children's Hospital Stanford between June 11 and July 14, 2020. Attending physicians, fellow physicians, hospitalists, and advanced practice providers with ≥0.5 full-time equivalent (FTE) for the prior four consecutive weeks and at least one EHR session recording were included in the study. Citrix session recording player was used to retrospectively review EHR session recordings that were captured as the provider interacted with the EHR. EHR use patterns varied by provider type. Audit-log based total EHR time correlated strongly with both observed total EHR time (r = 0.98, p < 0.001) and observed active EHR time (r = 0.95, p < 0.001). Each minute of audit-log based total EHR time corresponded to 0.95 (0.87-1.02) minutes of observed total EHR time and 0.75 (0.67-0.83) minutes of observed active EHR time. Results were similar when stratified by provider role. Our study found inpatient audit-log based EHR time to correlate strongly with observed EHR time among pediatric critical care providers. These findings support the use of audit-log based EHR-time as a surrogate measure for inpatient provider EHR use, providing an opportunity for researchers and other stakeholders to leverage EHR audit-log data in measuring clinical activity and tracking outcomes of workflow improvement efforts longitudinally and across provider groups.

The influence of a Sprint optimization and training intervention on time spent in the electronic health record (EHR).

ObjectiveWe report the influence of Sprint electronic health record (EHR) training and optimization on clinician time spent in the EHR.Materials and MethodsWe studied the Sprint process in one academic internal medicine practice with 26 providers. Program offerings included individualized training sessions, and the ability to clean up, fix, or build new EHR tools during the 2-week intervention. EHR usage log data were available for 24 clinicians, and the average clinical full-time equivalent was 0.44. We used a quasi-experimental study design with an interrupted time series specification, with 8 months of pre- and 12 months of post-intervention data to evaluate clinician time spent in the EHR.ResultsWe discovered a greater than 6 h per day reduction in clinician time spent in the EHR at the clinic level. At the individual clinician level, we demonstrated a time savings of 20 min per clinician per day among those who attended at least 2 training sessions.DiscussionWe can promote EHR time savings for clinicians who engage in robust EHR training and optimization programs. To date, programs have shown a positive correlation between participation and subjective EHR satisfaction, efficiency, or time saved. The impact of EHR training and optimization on objective time savings remains elusive. By measuring time in the EHR, this study contributes to an ongoing conversation about the resources and programs needed to decrease clinician EHR time.ConclusionsWe have demonstrated that Sprint is associated with time savings for clinicians for up to 6 months. We suggest that an investment in EHR optimization and training can pay dividends in clinician time saved.

Establishing a multidisciplinary initiative for interoperable electronic health record innovations at an academic medical center.

ObjectiveTo establish an enterprise initiative for improving health and health care through interoperable electronic health record (EHR) innovations.Materials and MethodsWe developed a unifying mission and vision, established multidisciplinary governance, and formulated a strategic plan. Key elements of our strategy include establishing a world-class team; creating shared infrastructure to support individual innovations; developing and implementing innovations with high anticipated impact and a clear path to adoption; incorporating best practices such as the use of Fast Healthcare Interoperability Resources (FHIR) and related interoperability standards; and maximizing synergies across research and operations and with partner organizations.ResultsUniversity of Utah Health launched the ReImagine EHR initiative in 2016. Supportive infrastructure developed by the initiative include various FHIR-related tooling and a systematic evaluation framework. More than 10 EHR-integrated digital innovations have been implemented to support preventive care, shared decision-making, chronic disease management, and acute clinical care. Initial evaluations of these innovations have demonstrated positive impact on user satisfaction, provider efficiency, and compliance with evidence-based guidelines. Return on investment has included improvements in care; over $35 million in external grant funding; commercial opportunities; and increased ability to adapt to a changing healthcare landscape.DiscussionKey lessons learned include the value of investing in digital innovation initiatives leveraging FHIR; the importance of supportive infrastructure for accelerating innovation; and the critical role of user-centered design, implementation science, and evaluation.ConclusionEHR-integrated digital innovation initiatives can be key assets for enhancing the EHR user experience, improving patient care, and reducing provider burnout.

The Association Between Using a Mobile Version of an Electronic Health Record and the Well-Being of Nurses: Cross-sectional Survey Study

BackgroundMobile devices such as tablets and smartphones are increasingly being used in health care in many developed countries. Nurses form the largest group in health care that uses electronic health records (EHRs) and their mobile versions. Mobile devices are suggested to promote nurses’ workflow, constant updating of patient information, and improve the communication within the health care team. However, little is known about their effect on nurses’ well-being.ObjectiveThis study aimed to examine the association between using a mobile version of the EHR and nurses’ perceived time pressure, stress related to information systems, and self-rated stress. Moreover, we examined whether mobile device use modifies the associations of EHR usability (ease of use and technical quality), experience in using EHRs, and number of systems in daily use with these well-being indicators.MethodsThis was a cross-sectional population-based survey study among 3610 Finnish registered nurses gathered in 2020. The aforesaid associations were examined using analyses of covariance and logistic regression adjusted for age, gender, and employment sector (hospital, primary care, social service, and other).ResultsNurses who used the mobile version of their EHR had higher levels of time pressure (F1,3537=14.96, P<.001) and stress related to information systems (F1,3537=6.11, P=.01), compared with those who did not use mobile versions. Moreover, the interactions of mobile device use with experience in using EHRs (F1,3581=14.93, P<.001), ease of use (F1,3577=10.16, P=.001), and technical quality (F1,3577=6.45, P=.01) were significant for stress related to information systems. Inexperience in using EHRs, low levels of ease of use, and technical quality were associated with higher stress related to information systems and this association was more pronounced among those who used mobile devices. That is, the highest levels of stress related to information systems were perceived among those who used mobile devices as well as among inexperienced EHR users or those who perceived usability problems in their EHRs.ConclusionsAccording to our results, it seems that at present mobile device use is not beneficial for the nurses’ well-being. In addition, mobile device use seems to intensify the negative effects of usability issues related to EHRs. In particular, inexperienced users of EHRs seem to be at a disadvantage when using mobile devices. Thus, we suggest that EHRs and their mobile versions should be improved such that they would be easier to use and would better support the nurses’ workflow (eg, improvements to problems related to small display, user interface, and data entry). Moreover, additional training on EHRs, their mobile versions, and workflow related to these should be provided to nurses.

Integrating Web Services/Applications to Improve Pediatric Functionalities in Electronic Health Records.

The past decade has seen a substantial increase in the use of electronic health records (EHRs) by health care providers caring for children. However, gaps in pediatric-specific functionalities continue to exist in some EHR systems, including population-specific growth curves, immunization clinical decision support, weight-based medication dosing with rounding, calculation of pediatric hypertension percentiles, age-specific developmental assessment, newborn bilirubin nomograms, anticipatory guidance reminders, and other functionalities described elsewhere. Implementing pediatric functionalities into EHRs is critical to the provision of safe pediatric care. As an alternative to direct implementation in EHRs, EHR vendor agnostic Web applications, Web services, and application programming interfaces offer an opportunity to provide pediatric functionalities and eliminate the need for each vendor to develop these functionalities. Successful implementation of Web services and related technologies requires responsible attention from both EHR vendors and developers of Web services, Web applications, and application programming interfaces to the use of data terminology standards, adherence to privacy and security requirements, rigorous testing, change management processes, and robust system support and maintenance. Education of health care providers about opportunities to improve pediatric functionalities in EHRs by using these services can facilitate discussions in EHR user groups in which vendors can be lobbied to implement them. This policy statement emphasizes the need to address pediatric-specific functionalities in EHRs by providing insight and recommendations into the development, maintenance, integration, and support of these novel solutions.

The future of medical scribes documenting in the electronic health record: results of an expert consensus conference

BackgroundWith the use of electronic health records (EHRs) increasing and causing unintended negative consequences, the medical scribe profession has burgeoned, but it has yet to be regulated. The purpose of this study was to describe scribe workflow as well as identify the threats and opportunities for the future of the scribe industry.MethodsThe first phase of the study used ethnographic methods consisting of interviews and observations by a multi-disciplinary team of researchers at five United States sites. In April 2019, a two-day conference of experts representing different stakeholder perspectives was held to discuss the results from site visits and to predict the future of medical scribing. An interpretive content analysis approach was used to discover threats and opportunities for the future of medical scribes.ResultsThreats facing the medical scribe industry were related to changes in the documentation model, EHR usability, different payment structures, the need to acquire disparate data during clinical encounters, and workforce-related changes relevant to the scribing model. Simultaneously, opportunities for medical scribing in the future included extension of their role to include workflow analysis, acting as EHR-related subject-matter-experts, and becoming integrated more effectively into the clinical care delivery team. Experts thought that if EHR usability increases, the need for medical scribes might decrease. Additionally, the scribe role could be expanded to allow scribes to document more or take on more informatics-related tasks. The experts also anticipated an increased use of alternative models of scribing, like tele-scribing.ConclusionThreats and opportunities for medical scribing were identified. Many experts thought that if the scribe role could be expanded to allow scribes to document more or take on more informatics activities, it would be beneficial. With COVID-19 continuing to change workflows, it is critical that medical scribes receive standardized training as tele-scribing continues to grow in popularity and new roles for scribes as medical team members are identified.