Background: Electronic health records (EHRs) hold promise to improve productivity, quality, and outcomes; however, using EHRs can be cumbersome, disruptive to workflow, and off-putting to patients and clinicians. One proposed solution to this problem is the use of medical scribes. The purpose of this systematic review is to summarize the literature investigating the effect of medical scribes on health care productivity, quality, and outcomes. Implications for future research are discussed.Methods: A keyword search of the Cochrane Library, OvidSP Medline database, and Embase database from January 2000 through September 2014 was performed using the terms scribe or scribes in the title or abstract. To ensure no potentially eligible articles were missed, a second search was done using Google Scholar. English-language, peer-reviewed studies assessing the effect of medical scribes on health care productivity, quality, and outcomes were retained. Identified studies were assessed and the findings reported.Results: Five studies were identified. Three studies assessed scribe use in an emergency department, 1 in a cardiology clinic, and 1 in a urology clinic. Two of 3 studies reported scribes had no effect on patient satisfaction; 2 of 2 reported improved clinician satisfaction; 2 of 3 reported an increase in the number of patients; 2 of 2 reported an increase in the number of relative value units per hour; 1 of 1 reported increased revenue; 3 of 4 reported improved time-related efficiencies; and 1 of 1 reported improved patient-clinician interactions.Conclusions: Available evidence suggests medical scribes may improve clinician satisfaction, productivity, time-related efficiencies, revenue, and patient-clinician interactions. Because the number of studies is small, and because each study suffered important limitations, confidence in the reliability of the evidence is significantly constrained. Given the nascent state of the science, methodologically rigorous and sufficiently powered studies are greatly needed. (J Am Board Fam Med 2015;28:371-381.)

Objectives 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. Methods 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. Results 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.” Discussion 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. Conclusion 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.

Introduction: Our university hospital-based primary care practices transitioned a budding interest in telehealth to a largely telehealth-based approach in the face of the COVID-19 pandemic.Initial work: Implementation of telehealth began in 2017. Health system barriers, provider and patient reluctance, and inadequate reimbursement prevented widespread adoption at the time. COVID-19 served as the catalyst to accelerate telehealth efforts.Implementation: COVID-19 resulted in the need for patient care with "social distancing." In addition, due to the pandemic, the Centers for Medicare and Medicaid Services and other insurers began expanded reimbursement for telehealth. More than 2000 providers received virtual health training in less than 2 weeks. In March 2020, we provided 2376 virtual visits, and in April 5293, which was more than 75 times the number provided in February; 73% of all visits in April were virtual (up from 0.5% in October 2019). As COVID-19 cases receded in May, June, and July, patient demand for virtual visits decreased, but 28% of visits in July were still virtual.Lessons learned: Several key lessons are important for future efforts regarding clinical implementation: (1) prepare for innovation, (2) cultivate an innovation mindset, (3) standardize (but not too much), (4) technological innovation is necessary but not sufficient, and (5) communicate widely and often. ( J Am Board Fam Med 2021;34:S196-S202.

Objective We report the influence of Sprint electronic health record (EHR) training and optimization on clinician time spent in the EHR. Materials and Methods We 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. Results We 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. Discussion We 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. Conclusions We 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.

Objective The objective of the study was to highlight and analyze the outcomes of software configuration requests received from Sprint, a comprehensive, clinic-centered electronic health record (EHR) optimization program. Methods A retrospective review of 1,254 Sprint workbook requests identified (1) the responsible EHR team, (2) the clinical efficiency gained from the request, and (3) the EHR intervention conducted. Results Requests were received from 407 clinicians and 538 staff over 31 weeks of Sprint. Sixty-nine percent of the requests were completed during the Sprint. Of all requests, 25% required net new build, 73% required technical investigation and/or solutions, and 2% of the requests were escalated to the vendor. The clinical specialty groups requested a higher percentage of items that earned them clinical review (16 vs. 10%) and documentation (29 vs. 23%) efficiencies compared with their primary care colleagues who requested slightly more order modifications (22 vs. 20%). Clinical efficiencies most commonly associated with workbook requests included documentation (28%), ordering (20%), in basket (17%), and clinical review (15%). Sprint user requests evaluated by ambulatory, hardware, security, and training teams comprised 80% of reported items. Discussion Sprint requests were categorized as clean-up, break-fix, workflow investigation, or new build. On-site collaboration with clinical care teams permitted consensus-building, drove vetting, and iteration of EHR build, and led to goal-driven, usable workflows and EHR products. Conclusion This program evaluation demonstrates the process by which optimization can occur and the products that result when we adhere to optimization principles in health care organizations.