Health Record Use Research Articles

Understanding enterprise data warehouses to support clinical and translational research: impact, sustainability, demand management, and accessibility.

Healthcare organizations, including Clinical and Translational Science Awards (CTSA) hubs funded by the National Institutes of Health, seek to enable secondary use of electronic health record (EHR) data through an enterprise data warehouse for research (EDW4R), but optimal approaches are unknown. In this qualitative study, our goal was to understand EDW4R impact, sustainability, demand management, and accessibility. We engaged a convenience sample of informatics leaders from CTSA hubs (n = 21) for semi-structured interviews and completed a directed content analysis of interview transcripts. EDW4R have created institutional capacity for single- and multi-center studies, democratized access to EHR data for investigators from multiple disciplines, and enabled the learning health system. Bibliometrics have been challenging due to investigator non-compliance, but one hub's requirement to link all study protocols with funding records enabled quantifying an EDW4R's multi-million dollar impact. Sustainability of EDW4R has relied on multiple funding sources with a general shift away from the CTSA grant toward institutional and industry support. To address EDW4R demand, institutions have expanded staff, used different governance approaches, and provided investigator self-service tools. EDW4R accessibility can benefit from improved tools incorporating user-centered design, increased data literacy among scientists, expansion of informaticians in the workforce, and growth of team science. As investigator demand for EDW4R has increased, approaches to tracking impact, ensuring sustainability, and improving accessibility of EDW4R resources have varied. This study adds to understanding of how informatics leaders seek to support investigators using EDW4R across the CTSA consortium and potentially elsewhere.

Telemedicine and In-Person Visit Modality Mix and Electronic Health Record Use in Primary Care

This cross-sectional study investigates the association between day-to-day changes in telemedicine share and clinician time spent on electronic health record (EHR) use.

Impact of Electronic Health Record Use on Cognitive Load and Burnout Among Clinicians: Narrative Review.

The cognitive load theory suggests that completing a task relies on the interplay between sensory input, working memory, and long-term memory. Cognitive overload occurs when the working memory's limited capacity is exceeded due to excessive information processing. In health care, clinicians face increasing cognitive load as the complexity of patient care has risen, leading to potential burnout. Electronic health records (EHRs) have become a common feature in modern health care, offering improved access to data and the ability to provide better patient care. They have been added to the electronic ecosystem alongside emails and other resources, such as guidelines and literature searches. Concerns have arisen in recent years that despite many benefits, the use of EHRs may lead to cognitive overload, which can impact the performance and well-being of clinicians. We aimed to review the impact of EHR use on cognitive load and how it correlates with physician burnout. Additionally, we wanted to identify potential strategies recommended in the literature that could be implemented to decrease the cognitive burden associated with the use of EHRs, with the goal of reducing clinician burnout. Using a comprehensive literature review on the topic, we have explored the link between EHR use, cognitive load, and burnout among health care professionals. We have also noted key factors that can help reduce EHR-related cognitive load, which may help reduce clinician burnout. The research findings suggest that inadequate efforts to present large amounts of clinical data to users in a manner that allows the user to control the cognitive burden in the EHR and the complexity of the user interfaces, thus adding more "work" to tasks, can lead to cognitive overload and burnout; this calls for strategies to mitigate these effects. Several factors, such as the presentation of information in the EHR, the specialty, the health care setting, and the time spent completing documentation and navigating systems, can contribute to this excess cognitive load and result in burnout. Potential strategies to mitigate this might include improving user interfaces, streamlining information, and reducing documentation burden requirements for clinicians. New technologies may facilitate these strategies. The review highlights the importance of addressing cognitive overload as one of the unintended consequences of EHR adoption and potential strategies for mitigation, identifying gaps in the current literature that require further exploration.

Measuring the Impact of Primary Care Team Composition on Patient Activation Utilizing Electronic Health Record Big Data Analytics.

Team-based care has been linked to key outcomes associated with the Quadruple Aim and a key driver of high-value patient-centered care. Use of the electronic health record (EHR) and machine learning have significant potential to overcome previous barriers to studying the impact of teams, including delays in accessing data to improve teamwork and optimize patient outcomes. This study utilized a large EHR dataset (n=316,542) from an urban health system to explore the relationship between team composition and patient activation, a key driver of patient engagement. Teams were operationalized using consensus definitions of teamwork from the literature. Patient activation was measured using the Patient Activation Measure (PAM). Results from multilevel regression analyses were compared to machine learning analyses using multinomial logistic regression to calculate propensity scores for the effect of team composition on PAM scores. Under the machine learning approach, a causal inference model with generalized overlap weighting was used to calculate the average treatment effect of teamwork. Seventeen different team types were observed in the data from the analyzed sample (n=12,448). Team sizes ranged from 2 to 5 members. After controlling for confounding variables in both analyses, more diverse, multidisciplinary teams (team size of 4 or more) were observed to have improved patient activation scores. This is the first study to explore the relationship between team composition and patient activation using the EHR and big data analytics. Implications for further research using EHR data and machine learning to study teams and other patient-centered care are promising and could be used to advance team science.

Understanding the role and impact of electronic health records in labor and delivery nursing practice: A scoping review protocol.

Electronic health records have a significant impact on nursing practice, particularly in specializations such as labor and delivery, or acute care maternity nursing practice. Although primary studies on the use of electronic health records in labor and delivery have been done, no reviews on this topic exist. Moreover, the topic of labor and delivery nurses' organizing work in the electronic health record-enabled context has not been addressed. To (a) synthesize research on electronic health record use in labor and delivery nursing and (b) map how labor and delivery nursing organizing work is transformed by the electronic health record (as described in the reviewed studies). The scoping review will be guided by a modified methodology based on selected recommendations from the Joanna Briggs Institute and the Preferred Reporting Items for Systematic reviews and Meta-Analyses Extension for Scoping Reviews. A comprehensive search will be conducted in the following databases: CINAHL Complete, MEDLINE, Academic Search Complete, Web of Science, Scopus and Dissertations and Theses Abstracts and Indexes. Included sources will be primary research, dissertations, or theses that address the use of electronic health records in labor and delivery nursing practice in countries with high levels of electronic health record adoption. Data extracted from included sources will be analyzed thematically. Further analysis will theorize labor and delivery nurses' organizing work in the context of electronic health record use by utilizing concepts from Davina Allen's Translational Mobilization Theory. Findings will be presented in tabular and descriptive formats. The findings of this review will help understand transformations of nursing practice in the electronic health record-enabled labor and delivery context and identify areas of future research. We will propose an extension of the Translational Mobilization Theory and theorize nurses' organizing work involving the use of the electronic health record.

The influence of electronic health record use on healthcare providers burnout

BackgroundElectronic health records (EHRs) are critical health information technology tools that ensure accuracy and improved management of patient records. However, the use of EHRs can lead to significant burden and burnout among healthcare providers, potentially affecting the quality of care they deliver. ObjectivesThe purpose of this study is to determine the extent of burnout among healthcare providers who use EHRs, with the specific objectives of assessing the level of EHR-related burnout in Saudi Arabian hospitals and identifying the key EHR-related factors contributing to this burnout. MethodsA descriptive quantitative cross-sectional study was conducted. A valid and reliable questionnaire was distributed to healthcare providers in Saudi Arabian hospitals to measure their burnout levels associated with EHR usage. ResultsThe findings indicate that the use of EHRs contributes to healthcare provider burnout, which may diminish the quality of care provided to patients. Several variables were significantly related to the healthcare providers' personal burnout, i.e., their living area, age, job, and year of experience, although only the healthcare provider's age influences their work-related burnout significantly. On the other hand, working hours per week and number of patients per week significantly influence the healthcare provider's EHR-related burnout. ConclusionThe study suggests that EHR usage is a significant factor in healthcare provider burnout. Addressing this issue requires enhanced training, workload reduction, and prompt resolution of EHR-related problems to improve provider well-being and maintain high-quality patient care.

Using electronic health records to enhance surveillance of diabetes in children, adolescents and young adults: a study protocol for the DiCAYA Network

IntroductionTraditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks...

Guidance for reporting analyses of metadata on electronic health record use.

Research on how people interact with electronic health records (EHRs) increasingly involves the analysis of metadata on EHR use. These metadata can be recorded unobtrusively and capture EHR use at a scale unattainable through direct observation or self-reports. However, there is substantial variation in how metadata on EHR use are recorded, analyzed and described, limiting understanding, replication, and synthesis across studies. In this perspective, we provide guidance to those working with EHR use metadata by describing 4 common types, how they are recorded, and how they can be aggregated into higher-level measures of EHR use. We also describe guidelines for reporting analyses of EHR use metadata-or measures of EHR use derived from them-to foster clarity, standardization, and reproducibility in this emerging and critical area of research.

The use of electronic health records in advanced practice nursing education: a scoping review

Electronic health records are integral to the advanced practice registered nurse role, yet access and training during academic preparation are profoundly limited. Lack of exposure to electronic health records prevents students from becoming fully prepared for the responsibilities of clinical practice and potentially impacts quality of care, patient safety, and communication among patients and providers. This scoping review of 20 articles on electronic health record use in advanced practice registered nursing student education shows significant gaps in current research. Nine articles were classified as research. The remaining 11 were non-research reports of teaching innovations describing the use of simulated electronic health records in graduate nursing education or the use of an electronic health record in interprofessional education activities. Most of the limited research did not use valid and reliable instruments or robust designs, employed disparate approaches and tools to study the phenomenon, and measured low-level outcomes such as student navigation and confidence in using electronic health records. The non-research literature draws attention to the deficits in educational resources, including unaffordable electronic health records for academic use. Although rigorous evidence is lacking, a common theme throughout the reviewed literature was the benefit of simulation to develop electronic health record skills.

Optimizing Electronic Health Record Use in the Busy Gastroenterology Practice

Optimizing Electronic Health Record Use in the Busy Gastroenterology Practice

The development of an explainable machine learning system for predicting brain atrophies from electronic health records

AbstractBackgroundThe number of elderly living with dementia is projected to dramatically increase, especially in low‐income and middle‐income countries (LMICs). While obtaining brain scans to detect atrophies and significant radiology findings related to dementia might be costly, the use of electronic health record (EHR) for elderly patients could facilitate identifying patients at a high risk based on routinely collected data. This works, evaluates the use of an interpretable machine learning‐based system that predicts brain atrophies and small vessel disease based on EHR data.MethodWe develop a machine learning predictive system to predict atrophies or small vessel disease from retrospective anonymized EHR data recorded for patients above the age of 50 years from a multispecialty outpatient medical center from Ramallah, Palestine. The patient labelling involved using natural language processing to identify cases in unstructured radiology reports for structural brain Magnetic Resonance Imaging (MRI). For input features, we extracted and preprocessed 30 features for the most commonly collected clinical features such as demographics and laboratory results. The dataset was split into training and test sets, where data preprocessing and augmentation, and hyperparameter tuning were applied before training multiple models including Xgboost, Support Vector Machines, Random Forest, and Logistic Regression. To better understand the relative impact each feature had on the model’s prediction, shapely feature importance analysis was conducted for the top performing model.ResultThe top preforming model was Random Forest, with a performance of Area Under the Precision‐Recall Curve (AUPRC) of 0.989, and 0.842 for Area Under Receiving Operating Curve (AUROC). The feature importance analysis revealed that age, sex, Vitamin D, Vitamin B12 and red blood cell distribution width were the features with highest impact on the model’s predictionConclusionPredicting atrophies from EHRs for elderly visiting outpatient clinics could assist in case‐finding for dementia patients and ultimately help identify patients that would benefit from an MRI. In future works, we aim to further investigate building low‐cost diagnostic tools based on a smaller feature set, which could be valuable for facilities from LMICs.

Abstract 18538: Results of a Self-Management Intervention to Improve Hypertension in Black Patients Using the Electronic Health Record Patient Portal

Introduction: Nearly half of American adults (47%) have hypertension (HTN), and non-Hispanic Black patients are disproportionately represented among those diagnosed (56% versus 48% for White, 46% for Asian, and 39% Hispanic adults). Models of care to reduce blood pressure for the Black patient population are not consistently implemented, in large part due to systemic and structural barriers to care. Hypothesis: The purpose of this study was to improve access to and use of digital education, skills for self-measured blood pressure (SMBP) monitoring, use of the electronic health record (EHR) patient portal, and blood pressure from baseline to 3 months in a cohort of Black Americans. Methods: A pre-post intervention design was used to evaluate the team-based, nurse-led intervention. Patients received coaching on HTN goals, screening for social determinants of health (SDOH), medication review, self-paced portal-based videos, and teach-back for BP cuff use. Post-implementation blood pressure (BP) and self-management (knowledge, cuff-use, patient portal use, and attendance at follow-up) were measured using the HELM tool, Chronic Care Model (CCM) and American Heart Association (AHA) HTN toolkit. 12-month follow-up is ongoing. Results: Black participants (n=80) averaged 59 (SD 10) years of age; most were female (n=58, 73%), employed (n=59, 75%), non-smokers (n=66, 84%), with average BMI 34.5 (SD8). From 0-3-months, views of portal-pushed videos increased to 69%, knowledge scores improved pre- (M = 67.9, SD = 16.7 to post (M = 75.2, SD = 17.4), and mean systolic BP was significantly reduced by 20.3mmHg (95%CI 16.11, 24.44). Average systolic BP pre was 152.13 (SD = 16.87) and post was 131.85 (SD = 13.13), t (79) = 9.71, p< .001. Sustainability at 12-months is ongoing. Conclusions: A team-based, nurse-led model improves patient engagement, adoption of portal-prescribed education, skills for SMBP, EHR-reported BP, and visit follow-up for Black patients with uncontrolled BP.

The state of workforce retention among US oncologists.

42 Background: With increasing incidence rate of human malignancy, it is critical to maintain an adequate oncologist workforce to meet the societal need for expected oncologic care. Methods: In January-February 2023, ASCO emailed a novel 36 item REDCap survey to 5892 U.S.-based ASCO physician members to evaluate career intentions. The survey included 2 questions from the Maslach Burnout Inventory (MBI). The survey was distributed through multiple ASCO channels in February-March 2023. Survey responses were compared to findings from a 2013 survey of 1345 oncologists by Shanafelt et al.1 Per convention, those with high levels of emotional exhaustion and/or depersonalization were categorized as having burnout. Results: 410 eligible responses were analyzed. Demographic characteristics of oncologists in active practice (ACs) (≥ 6 hours/week) and oncologists no longer in active practice (FCs) are summarized in the Table. Most ACs reported that their total work hours (57%) and hours spent on administrative work (68%) had increased since 2019 (pre-COVID). 49% reported an increase in patient care hours. Compared to ACs surveyed in 2013, a higher percentage of ACs surveyed in 2023 reported it was “likely” or “definite” they would leave their current practice within 2 years (21% vs. 17%, p=.049) or reduce their clinical work hours in the next 12 months (22% vs 16%; p=.009). High likelihood of leaving or reducing hours were associated with burnout (p=.002 and .003, respectively). When ACs were asked to identify up to 2 major work stressors, "Staffing levels” and “Use of the electronic health record” were the most common responses (47% of responders each) with “Payer policies and interactions” close behind (42%). Among retired FCs (42%, n=33), the median retirement age was 67 [IQR: 7]. A high proportion (42%, n=14) of these oncologists indicated they retired 2-4 years earlier than planned. Among FCs who had transitioned to non-clinical roles (56%, n=46), the median age to leave clinical practice was 58 [IQR: 21]. Among oncologists who had transitioned to non-clinical roles, the top reason for leaving clinical practice before age 50 was “Lack of satisfaction with clinical practice” (35%, n=6), while for those 50 or older it was “Desire for more work flexibility” (31%, n=9). Conclusions: The proportion of oncologists who intend to reduce clinical care hours or leave their current practice has risen over the past decade and is associated with professional burnout. Dissatisfaction with the practice environment has led some oncologists to leave clinical practice and/or retire earlier than planned. These trends have implications for the adequacy of the oncologist workforce to meet the needs of patients. (1) Shanafelt et al: J Clin Oncol 32(27), 2014. [Table: see text]

Reducing Preoperative Fasting Through Technology and Education in an Acute General Surgical Adult Cohort.

Despite widespread support for reduced fasting protocols prior to anesthesia, the traditional "fast from midnight" (FFMN) remains widely employed. This study implemented a pilot preoperative fasting reduction program for patients booked for acute surgery in the Department of General Surgery at a busy metropolitan tertiary hospital, including use of an electronic health record (EHR)-based solution, aiming to measure effect on fasting times and use of intravenous fluid (IVF). A pilot program was implemented in August 2021 in the Emergency General Surgery (EGS) unit at the Royal Melbourne Hospital, Australia. This included a new smart phrase within the EHR (EU2WU6: Eat until 2, drink water until 6) and an education campaign. Adult patients who underwent preoperative fasting between September 1 and December 31, 2021, were screened. Uptake of the protocol was recorded. Further, total fasting times (TFT) and IVF use were recorded. Potential impact with varying levels of protocol uptake was modeled. Uptake of EU2WU6 increased from 0% to 80%. TFT and total time on IVF (TT-IVF) were lower using EU2WU6 (TFT 7 hours vs. 13 hours, p < 0.001; TT-IVF 3 hours vs. 8 hours, p < 0.001). Proportion of patients requiring fluid overnight when using EU2WU6 was lower (18/45 vs. 34/50, p = 0.0062). Hospitalwide yearly savings, with 100% application of EU2WU6, were projected at 2,050 bags of IVF (at a cost savings of A$2,296), 10,251 minutes for physicians, and 20,502 minutes for nurses. The pilot preoperative fasting reduction program successfully reduced disparity between evidence and clinical practice.

Disparities in electronic health record portal access and use among patients with cancer.

Electronic health record-linked portals may improve health-care quality for patients with cancer. Barriers to portal access and use undermine interventions that rely on portals to reduce cancer care disparities. This study examined portal access and persistence of portal use and associations with patient and structural factors before the implementation of 3 portal-based interventions within the Improving the Management of symPtoms during And following Cancer Treatment (IMPACT) Consortium. Portal use data were extracted from electronic health records for the 12 months preceding intervention implementation. Sociodemographic factors, mode of accessing portals (web vs mobile), and number of clinical encounters before intervention implementation were also extracted. Rurality was derived using rural-urban commuting area codes. Broadband access was estimated using the 2015-2019 American Community Survey. Multiple logistic regression models tested the associations of these factors with portal access (ever accessed or never accessed) and persistence of portal use (accessed the portal ≤20 weeks vs ≥21 weeks in the 35-week study period). Of 28 942 eligible patients, 10 061 (35%) never accessed the portal. Male sex, membership in a racial and ethnic minority group, rural dwelling, not working, and limited broadband access were associated with lower odds of portal access. Younger age and more clinical encounters were associated with higher odds of portal access. Of those with portal access, 25% were persistent users. Using multiple modalities for portal access, being middle-aged, and having more clinical encounters were associated with persistent portal use. Patient and structural factors affect portal access and use and may exacerbate disparities in electronic health record-based cancer symptom surveillance and management.

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.

The use of electronic health record embedded MRC-ICU as a metric for critical care pharmacist workload.

A lack of pharmacist-specific risk-stratification scores in the electronic health record (EHR) may limit resource optimization. The medication regimen complexity-intensive care unit (MRC-ICU) score was implemented into our center's EHR for use by clinical pharmacists. The purpose of this evaluation was to evaluate MRC-ICU as a predictor of pharmacist workload and to assess its potential as an additional dimension to traditional workload measures. Data were abstracted from the EHR on adult ICU patients, including MRC-ICU scores and 2 traditional measures of pharmacist workload: numbers of medication orders verified and interventions logged. This was a single-center study of an EHR-integrated MRC-ICU tool. The primary outcome was the association of MRC-ICU with institutional metrics of pharmacist workload. Associations were assessed using the initial 24-h maximum MRC-ICU score's Pearson's correlation with overall admission workload and the day-to-day association using generalized linear mixed-effects modeling. A total of 1205 patients over 5083 patient-days were evaluated. Baseline MRC-ICU was correlated with both cumulative order volume (Spearman's rho 0.41, P < .001) and cumulative interventions placed (Spearman's rho 0.27, P < .001). A 1-point increase in maximum daily MRC-ICU was associated with a 31% increase in order volume (95% CI, 24%-38%) and 4% increase in interventions (95% CI, 2%-5%). The MRC-ICU is a validated score that has been previously correlated with important patient-centered outcomes. Here, MRC-ICU was modestly associated with 2 traditional objective measures of pharmacist workload, including orders verified and interventions placed, which is an important step for its use as a tool for resource utilization needs.

Identifying and Addressing Barriers to Implementing Core Electronic Health Record Use Metrics for Ambulatory Care: Virtual Consensus Conference Proceedings.

Precise, reliable, valid metrics that are cost-effective and require reasonable implementation time and effort are needed to drive electronic health record (EHR) improvements and decrease EHR burden. Differences exist between research and vendor definitions of metrics. PROCESS: We convened three stakeholder groups (health system informatics leaders, EHR vendor representatives, and researchers) in a virtual workshop series to achieve consensus on barriers, solutions, and next steps to implementing the core EHR use metrics in ambulatory care. CONCLUSION: Actionable solutions identified to address core categories of EHR metric implementation challenges include: (1) maintaining broad stakeholder engagement, (2) reaching agreement on standardized measure definitions across vendors, (3) integrating clinician perspectives, and (4) addressing cognitive and EHR burden. Building upon the momentum of this workshop's outputs offers promise for overcoming barriers to implementing EHR use metrics.

Assessing Electronic Health Record (EHR) Use during a Major EHR Transition: An Innovative Mixed Methods Approach

BackgroundElectronic health record (EHR) transitions are inherently disruptive to healthcare workers who must rapidly learn a new EHR and adapt to altered clinical workflows. Healthcare workers’ perceptions of EHR usability and their EHR use patterns following transitions are poorly understood. The Department of Veterans Affairs (VA) is currently replacing its homegrown EHR with a commercial Cerner EHR, presenting a unique opportunity to examine EHR use trends and usability perceptions.ObjectiveTo assess EHR usability and uptake up to 1-year post-transition at the first VA EHR transition site using a novel longitudinal, mixed methods approach.DesignA concurrent mixed methods strategy using EHR use metrics and qualitative interview data.Participants141 clinicians with data from select EHR use metrics in Cerner Lights On Network®. Interviews with 25 healthcare workers in various clinical and administrative roles.ApproachWe assessed changes in total EHR time, documentation time, and order time per patient post-transition. Interview transcripts (n = 90) were coded and analyzed for content specific to EHR usability.Key ResultsTotal EHR time, documentation time, and order time all decreased precipitously within the first four months after go-live and demonstrated gradual improvements over 12 months. Interview participants expressed ongoing concerns with the EHR’s usability and functionality up to a year after go-live such as tasks taking longer than the old system and inefficiencies related to inadequate training and inherent features of the new system. These sentiments did not seem to reflect the observed improvements in EHR use metrics.ConclusionsThe integration of quantitative and qualitative data yielded a complex picture of EHR usability. Participants described persistent challenges with EHR usability 1 year after go-live contrasting with observed improvements in EHR use metrics. Combining findings across methods can provide a clearer, contextualized understanding of EHR adoption and use patterns during EHR transitions.