Ambulatory Clinician's Guide to Inpatient Service: An Innovative Rapid Onboarding Strategy for the COVID-19 Pandemic

Background and Significance  When hospitals are subject to prolonged surges in patients, such as during the coronavirus disease 2019 (COVID-19) pandemic, additional clinicians may be needed to care for the rapid increase of acutely ill patients. How might we quickly prepare a large number of ambulatory-based clinicians to care for hospitalized patients using the inpatient workflow of the electronic health record (EHR)? Objectives  The aim of the study is to create a successful training intervention which prepares ambulatory-based clinicians as they transition to inpatient services. Methods  We created a training guide with embedded videos that describes the workflow of an inpatient clinician. We delivered this intervention via an e-mail hyperlink, a static hyperlink inside of the EHR, and an on-demand hyperlink within the EHR. Results  In anticipation of the first peak of inpatients with COVID-19 in April 2020, the training manual was accessed 261 times by 167 unique users as clinicians anticipated being called into service. As our institution has not yet needed to deploy ambulatory-based clinicians for inpatient service, usage data of the training document is still pending. Conclusion  We intend that our novel implementation of a multimedia, highly accessible onboarding document with access from points inside and outside of the EHR will improve clinician performance and serve as a helpful example to other organizations during the COVID-19 pandemic and beyond.     

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

Background  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. Objective  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. Methods  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. Results  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. Conclusion  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.     

Disparities in Telemedicine Access: A Cross-Sectional Study of a Newly Established Infrastructure during the COVID-19 Pandemic

Background  The COVID-19 pandemic led to dramatic increases in telemedicine use to provide outpatient care without in-person contact risks. Telemedicine increases options for health care access, but a “digital divide” of disparate access may prevent certain populations from realizing the benefits of telemedicine. Objectives  The study aimed to understand telemedicine utilization patterns after a widespread deployment to identify potential disparities exacerbated by expanded telemedicine usage. Methods  We performed a cross-sectional retrospective analysis of adults who scheduled outpatient visits between June 1, 2020 and August 31, 2020 at a single-integrated academic health system encompassing a broad range of subspecialties and a large geographic region in the Upper Midwest, during a period of time after the initial surge of COVID-19 when most standard clinical services had resumed. At the beginning of this study period, approximately 72% of provider visits were telemedicine visits. The primary study outcome was whether a patient had one or more video-based visits, compared with audio-only (telephone) visits or in-person visits only. The secondary outcome was whether a patient had any telemedicine visits (video-based or audio-only), compared with in-person visits only. Results  A total of 197,076 individuals were eligible (average age = 46 years, 56% females). Increasing age, rural status, Asian or Black/African American race, Hispanic ethnicity, and self-pay/uninsured status were significantly negatively associated with having a video visit. Digital literacy, measured by patient portal activation status, was significantly positively associated with having a video visit, as were Medicaid or Medicare as payer and American Indian/Alaskan Native race. Conclusion  Our findings reinforce previous evidence that older age, rural status, lower socioeconomic status, Asian race, Black/African American race, and Hispanic/Latino ethnicity are associated with lower rates of video-based telemedicine use. Health systems and policies should seek to mitigate such barriers to telemedicine when possible, with efforts such as digital literacy outreach and equitable distribution of telemedicine infrastructure.     

A Framework for Systematic Assessment of Clinical Trial Population Representativeness Using Electronic Health Records Data

Background  Clinical trials are the gold standard for generating robust medical evidence, but clinical trial results often raise generalizability concerns, which can be attributed to the lack of population representativeness. The electronic health records (EHRs) data are useful for estimating the population representativeness of clinical trial study population. Objectives  This research aims to estimate the population representativeness of clinical trials systematically using EHR data during the early design stage. Methods  We present an end-to-end analytical framework for transforming free-text clinical trial eligibility criteria into executable database queries conformant with the Observational Medical Outcomes Partnership Common Data Model and for systematically quantifying the population representativeness for each clinical trial. Results  We calculated the population representativeness of 782 novel coronavirus disease 2019 (COVID-19) trials and 3,827 type 2 diabetes mellitus (T2DM) trials in the United States respectively using this framework. With the use of overly restrictive eligibility criteria, 85.7% of the COVID-19 trials and 30.1% of T2DM trials had poor population representativeness. Conclusion  This research demonstrates the potential of using the EHR data to assess the clinical trials population representativeness, providing data-driven metrics to inform the selection and optimization of eligibility criteria.     

Do You Know What Your Scribe Did Last Spring? The Impact of COVID-19 on Medical Scribe Workflow

Objective  To understand the impact of the shift to virtual medicine induced by coronavirus disease 2019 (COVID-19) has had on the workflow of medical scribes. Design  This is a prospective observational survey-based study. Setting  This study was conducted at academic medical center in the United States. Participants  Seventy-four scribes working in ambulatory practices within an academic medical center. Interventions  All medical scribes received a survey assessing their workflow since beginning of COVID-19 restrictions. Primary and Secondary Outcomes  To assess the current workflow of medical scribes since transition to virtual care. Secondary outcomes are to assess the equipment used and location of their new workflow. Results  Fifty-seven scribes completed the survey. Overall 42% of scribes have transitioned to remote scribing with 97% serving as remote scribes for remote visits. This workflow is conducted at home and with personal equipment. Of those not working as scribes, 46% serve in preclinic support, with a wide range of EHR-related activities being reported. The remaining scribes have been either redeployed or furloughed. Conclusion  The rapid transition to virtual care brought about by COVID-19 has resulted in a dramatic shift in scribe workflow with the adoption of a previously unreported workflow of remote scribing for virtual care. Additional work is now needed to ensure these new workflows are safe and effective and that scribes are trained to work in this new paradigm.     

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

Background  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. Objective  The objective of our study was to measure the association between CLOC metrics and validated measures of physician burnout and professional fulfillment. Methods  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. Results  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. Conclusion  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.     

Associations of Telehealth Care Delivery with Pediatric Health Care Provider Well-Being

Background  The rapid, large-scale deployment of new health technologies can introduce challenges to clinicians who are already under stress. The novel coronavirus disease 19 (COVID-19) pandemic transformed health care in the United States to include a telehealth model of care delivery. Clarifying paths through which telehealth technology use is associated with change in provider well-being and interest in sustaining virtual care delivery can inform planning and optimization efforts. Objective  This study aimed to characterize provider-reported changes in well-being and daily work associated with the pandemic-accelerated expansion of telehealth and assess the relationship of provider perceptions of telehealth effectiveness, efficiency, and work–life balance with desire for future telehealth. Methods  A cross-sectional survey study was conducted October through November 2020, 6 months after the outbreak of COVID-19 at three children''s hospitals. Factor analysis and structural equation modeling (SEM) were used to examine telehealth factors associated with reported change in well-being and desire for future telehealth. Results  A total of 947 nontrainee physicians, advanced practice providers, and psychologists were surveyed. Of them, 502 (53.0%) providers responded and 467 (49.3%) met inclusion criteria of telehealth use during the study period. Of these, 325 (69.6%) were female, 301 (65.6%) were physicians, and 220 (47.1%) were medical subspecialists. Providers were 4.77 times as likely (95% confidence interval [CI]: 3.29–7.06) to report improved versus worsened well-being associated with telehealth. Also, 95.5% of providers (95% CI: 93.2–97.2%) wish to continue performing telehealth postpandemic. Our model explains 66% of the variance in telehealth-attributed provider well-being and 59% of the variance for future telehealth preference and suggests telehealth resources significantly influence provider-perceived telehealth care effectiveness which in turn significantly influences provider well-being and desire to perform telehealth. Conclusion  Telehealth has potential to promote provider well-being; telehealth-related changes in provider well-being are associated with both provider-perceived effectiveness of telemedicine for patients and adequacy of telehealth resources.     

Impact of Changes in EHR Use during COVID-19 on Physician Trainee Mental Health

Objectives  This article investigates the association between changes in electronic health record (EHR) use during the coronavirus disease 2019 (COVID-19) pandemic on the rate of burnout, stress, posttraumatic stress disorder (PTSD), depression, and anxiety among physician trainees (residents and fellows). Methods  A total of 222 (of 1,375, 16.2%) physician trainees from an academic medical center responded to a Web-based survey. We compared the physician trainees who reported that their EHR use increased versus those whose EHR use stayed the same or decreased on outcomes related to depression, anxiety, stress, PTSD, and burnout using univariable and multivariable models. We examined whether self-reported exposure to COVID-19 patients moderated these relationships. Results  Physician trainees who reported increased use of EHR had higher burnout (adjusted mean, 1.48 [95% confidence interval [CI] 1.24, 1.71] vs. 1.05 [95% CI 0.93, 1.17]; p  = 0.001) and were more likely to exhibit symptoms of PTSD (adjusted mean = 15.09 [95% CI 9.12, 21.05] vs. 9.36 [95% CI 7.38, 11.28]; p  = 0.035). Physician trainees reporting increased EHR use outside of work were more likely to experience depression (adjusted mean, 8.37 [95% CI 5.68, 11.05] vs. 5.50 [95% CI 4.28, 6.72]; p  = 0.035). Among physician trainees with increased EHR use, those exposed to COVID-19 patients had significantly higher burnout (2.04, p  < 0.001) and depression scores (14.13, p  = 0.003). Conclusion  Increased EHR use was associated with higher burnout, depression, and PTSD outcomes among physician trainees. Although preliminary, these findings have implications for creating systemic changes to manage the wellness and well-being of trainees.     

Interaction Time with Electronic Health Records: A Systematic Review

Background  The amount of time that health care clinicians (physicians and nurses) spend interacting with the electronic health record is not well understood. Objective  This study aimed to evaluate the time that health care providers spend interacting with electronic health records (EHR). Methods  Data are retrieved from Ovid MEDLINE(R) and Epub Ahead of Print, In-Process and Other Non-Indexed Citations and Daily, (Ovid) Embase, CINAHL, and SCOPUS. Study Eligibility Criteria  Peer-reviewed studies that describe the use of EHR and include measurement of time either in hours, minutes, or in the percentage of a clinician''s workday. Papers were written in English and published between 1990 and 2021. Participants  All physicians and nurses involved in inpatient and outpatient settings. Study Appraisal and Synthesis Methods  A narrative synthesis of the results, providing summaries of interaction time with EHR. The studies were rated according to Quality Assessment Tool for Studies with Diverse Designs. Results  Out of 5,133 de-duplicated references identified through database searching, 18 met inclusion criteria. Most were time-motion studies (50%) that followed by logged-based analysis (44%). Most were conducted in the United States (94%) and examined a clinician workflow in the inpatient settings (83%). The average time was nearly 37% of time of their workday by physicians in both inpatient and outpatient settings and 22% of the workday by nurses in inpatient settings. The studies showed methodological heterogeneity. Conclusion  This systematic review evaluates the time that health care providers spend interacting with EHR. Interaction time with EHR varies depending on clinicians'' roles and clinical settings, computer systems, and users'' experience. The average time spent by physicians on EHR exceeded one-third of their workday. The finding is a possible indicator that the EHR has room for usability, functionality improvement, and workflow optimization.     

Building a Learning Health System: Creating an Analytical Workflow for Evidence Generation to Inform Institutional Clinical Care Guidelines

Background  One key aspect of a learning health system (LHS) is utilizing data generated during care delivery to inform clinical care. However, institutional guidelines that utilize observational data are rare and require months to create, making current processes impractical for more urgent scenarios such as those posed by the COVID-19 pandemic. There exists a need to rapidly analyze institutional data to drive guideline creation where evidence from randomized control trials are unavailable. Objectives  This article provides a background on the current state of observational data generation in institutional guideline creation and details our institution''s experience in creating a novel workflow to (1) demonstrate the value of such a workflow, (2) demonstrate a real-world example, and (3) discuss difficulties encountered and future directions. Methods  Utilizing a multidisciplinary team of database specialists, clinicians, and informaticists, we created a workflow for identifying and translating a clinical need into a queryable format in our clinical data warehouse, creating data summaries and feeding this information back into clinical guideline creation. Results  Clinical questions posed by the hospital medicine division were answered in a rapid time frame and informed creation of institutional guidelines for the care of patients with COVID-19. The cost of setting up a workflow, answering the questions, and producing data summaries required around 300 hours of effort and $300,000 USD. Conclusion  A key component of an LHS is the ability to learn from data generated during care delivery. There are rare examples in the literature and we demonstrate one such example along with proposed thoughts of ideal multidisciplinary team formation and deployment.     

Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial

Background  We previously developed and validated a predictive model to help clinicians identify hospitalized adults with coronavirus disease 2019 (COVID-19) who may be ready for discharge given their low risk of adverse events. Whether this algorithm can prompt more timely discharge for stable patients in practice is unknown. Objectives  The aim of the study is to estimate the effect of displaying risk scores on length of stay (LOS). Methods  We integrated model output into the electronic health record (EHR) at four hospitals in one health system by displaying a green/orange/red score indicating low/moderate/high-risk in a patient list column and a larger COVID-19 summary report visible for each patient. Display of the score was pseudo-randomized 1:1 into intervention and control arms using a patient identifier passed to the model execution code. Intervention effect was assessed by comparing LOS between intervention and control groups. Adverse safety outcomes of death, hospice, and re-presentation were tested separately and as a composite indicator. We tracked adoption and sustained use through daily counts of score displays. Results  Enrolling 1,010 patients from May 15, 2020 to December 7, 2020, the trial found no detectable difference in LOS. The intervention had no impact on safety indicators of death, hospice or re-presentation after discharge. The scores were displayed consistently throughout the study period but the study lacks a causally linked process measure of provider actions based on the score. Secondary analysis revealed complex dynamics in LOS temporally, by primary symptom, and hospital location. Conclusion  An AI-based COVID-19 risk score displayed passively to clinicians during routine care of hospitalized adults with COVID-19 was safe but had no detectable impact on LOS. Health technology challenges such as insufficient adoption, nonuniform use, and provider trust compounded with temporal factors of the COVID-19 pandemic may have contributed to the null result. Trial registration  ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT04570488","term_id":"NCT04570488"}}NCT04570488.     

Clinician and Health Care Leaders' Experiences with—and Perceptions of—COVID-19 Documentation Reduction Policies and Practices

Background  Substantial strategies to reduce clinical documentation were implemented by health care systems throughout the coronavirus disease-2019 (COVID-19) pandemic at national and local levels. This natural experiment provides an opportunity to study the impact of documentation reduction strategies on documentation burden among clinicians and other health professionals in the United States. Objectives  The aim of this study was to assess clinicians'' and other health care leaders'' experiences with and perceptions of COVID-19 documentation reduction strategies and identify which implemented strategies should be prioritized and remain permanent post-pandemic. Methods  We conducted a national survey of clinicians and health care leaders to understand COVID-19 documentation reduction strategies implemented during the pandemic using snowball sampling through professional networks, listservs, and social media. We developed and validated a 19-item survey leveraging existing post-COVID-19 policy and practice recommendations proposed by Sinsky and Linzer. Participants rated reduction strategies for impact on documentation burden on a scale of 0 to 100. Free-text responses were thematically analyzed. Results  Of the 351 surveys initiated, 193 (55%) were complete. Most participants were informaticians and/or clinicians and worked for a health system or in academia. A majority experienced telehealth expansion (81.9%) during the pandemic, which participants also rated as highly impactful (60.1–61.5) and preferred that it remain (90.5%). Implemented at lower proportions, documenting only pertinent positives to reduce note bloat (66.1 ± 28.3), c hanging compliance rules and performance metrics to eliminate those without evidence of net benefit (65.7 ± 26.3), and electronic health record (EHR) optimization sprints (64.3 ± 26.9) received the highest impact scores compared with other strategies presented; support for these strategies widely ranged (49.7–63.7%). Conclusion  The results of this survey suggest there are many perceived sources of and solutions for documentation burden. Within strategies, we found considerable support for telehealth, documenting pertinent positives, and changing compliance rules. We also found substantial variation in the experience of documentation burden among participants.     

Provider Preferences for Patient-Generated Health Data Displays in Pediatric Asthma: A Participatory Design Approach

Objective  There is a lack of evidence on how to best integrate patient-generated health data (PGHD) into electronic health record (EHR) systems in a way that supports provider needs, preferences, and workflows. The purpose of this study was to investigate provider preferences for the graphical display of pediatric asthma PGHD to support decisions and information needs in the outpatient setting. Methods  In December 2019, we conducted a formative evaluation of information display prototypes using an iterative, participatory design process. Using multiple types of PGHD, we created two case-based vignettes for pediatric asthma and designed accompanying displays to support treatment decisions. Semi-structured interviews and questionnaires with six participants were used to evaluate the display usability and determine provider preferences. Results  We identified provider preferences for display features, such as the use of color to indicate different levels of abnormality, the use of patterns to trend PGHD over time, and the display of environmental data. Preferences for display content included the amount of information and the relationship between data elements. Conclusion  Overall, provider preferences for PGHD include a desire for greater detail, additional sources, and visual integration with relevant EHR data. In the design of PGHD displays, it appears that the visual synthesis of multiple PGHD elements facilitates the interpretation of the PGHD. Clinicians likely need more information to make treatment decisions when PGHD displays are introduced into practice. Future work should include the development of interactive interface displays with full integration of PGHD into EHR systems.     

Implementing an Application Programming Interface for PROMIS Measures at Three Medical Centers

Background  There is an increasing body of literature advocating for the collection of patient-reported outcomes (PROs) in clinical care. Unfortunately, there are many barriers to integrating PRO measures, particularly computer adaptive tests (CATs), within electronic health records (EHRs), thereby limiting access to advances in PRO measures in clinical care settings. Objective  To address this obstacle, we created and evaluated a software integration of an Application Programming Interface (API) service for administering and scoring Patient-Reported Outcomes Measurement Information System (PROMIS) measures with the EHR system. Methods  We created a RESTful API and evaluated the technical feasibility and impact on clinical workflow at three academic medical centers. Results  Collaborative teams (i.e., clinical, information technology [IT] and administrative staff) performed these integration efforts addressing issues such as software integration as well as impact on clinical workflow. All centers considered their implementation successful based on the high rate of completed PROMIS assessments (between January 2016 and January 2021) and minimal workflow disruptions. Conclusion  These case studies demonstrate not only the feasibility but also the pathway for the integration of PROMIS CATs into the EHR and routine clinical care. All sites utilized diverse teams with support and commitment from institutional leadership, initial implementation in a single clinic, a process for monitoring and optimization, and use of custom software to minimize staff burden and error.     

Telemedicine Adoption during the COVID-19 Pandemic: Gaps and Inequalities

Background  The telemedicine industry has been experiencing fast growth in recent years. The outbreak of coronavirus disease 2019 (COVID-19) further accelerated the deployment and utilization of telemedicine services. An analysis of the socioeconomic characteristics of telemedicine users to understand potential socioeconomic gaps and disparities is critical for improving the adoption of telemedicine services among patients. Objectives  This study aims to measure the correlation of socioeconomic determinants with the use of telemedicine services in Milwaukee metropolitan area. Methods  Electronic health record review of patients using telemedicine services compared with those not using telemedicine services within an academic-community health system: patient demographics (e.g., age, gender, race, and ethnicity), insurance status, and socioeconomic determinants obtained through block-level census data in Milwaukee area. The telemedicine users were compared with all other patients using regression analysis. The telemedicine adoption rates were calculated across regional ZIP codes to analyze the geographic patterns of telemedicine adoption. Results  A total of 104,139 patients used telemedicine services during the study period. Patients who used video visits were younger (median age 48.12), more likely to be White (odds ratio [OR] 1.34; 95% confidence interval [CI], 1.31–1.37), and have private insurance (OR 1.43; CI, 1.41–1.46); patients who used telephone visits were older (median age 57.58), more likely to be Black (OR 1.31; CI 1.28–1.35), and have public insurance (OR 1.30; CI 1.27–1.32). In general, Latino and Asian populations were less likely to use telemedicine; women used more telemedicine services in general than men. In the multiple regression analysis of social determinant factors across 126 ZIP codes, college education (coefficient 1.41, p  = 0.01) had a strong correlation to video telemedicine adoption rate. Conclusion  Adoption of telemedicine services was significantly impacted by the social determinant factors of health, such as income, education level, race, and insurance type. The study reveals the potential inequities and disparities in telemedicine adoption.     

A Collaborative Partnership between the Multicenter Handoff Collaborative and an Electronic Health Record Vendor

Objectives  The operating room is a specialized, complex environment with many factors that can impede effective communication during transitions of care between anesthesia clinicians. We postulated that an efficient, accessible, standardized tool for intraoperative handoffs built into standard workflow would improve communication and handoff safety. Most institutions now use an electronic health record (EHR) system for patient care and have independently designed intraoperative handoff tools, but these home-grown tools are not scalable to other organizations and lack vendor-supported features. The goal of this project was to create a standardized, intraoperative handoff tool supported by EHR functionality. Methods  The Multicenter Handoff Collaborative, with support from the Anesthesia Patient Safety Foundation, created a working group of frontline anesthesia experts to collaborate with a development team from the EHR vendor (Epic Systems) to design a standardized intraoperative handoff tool. Over 2 years, the working group identified the critical elements for the tool and software usability, and the EHR team designed a standardized intraoperative handoff tool that is accessible to any institution using this EHR. Results  The first iteration of the intraoperative handoff tool was released in August 2019, with a second version in February 2020. The tool is standardized but customizable by individual institutions. Conclusion  We demonstrate that work on complex health care processes critical to patient safety, such as handoffs, can be performed on a national scale through cross-industry collaboration. Frontline experts can partner with health care industry vendors to design, build, and release a product on an accelerated timeline.     

Electronic Task Management System: A Pediatric Institution's Experience

Background  Electronic medical task management systems (ETMs) have been adopted in health care institutions to improve health care provider communication. ETMs allow for the requesting and resolution of nonurgent tasks between clinicians of all craft groups. Visibility, ability to provide close-loop feedback, and a digital trail of all decisions and responsible clinicians are key features of ETMs. An embedded ETM within an integrated electronic health record (EHR) was introduced to the Royal Children''s Hospital Melbourne on April 30, 2016. The ETM is used hospital-wide for nonurgent tasks 24 hours a day. It facilitates communication of nonurgent tasks between clinical staff, with an associated designated timeframe in which the task needs to be completed (2, 4, and 8 hours). Objective  This study aims to examine the usage of the ETM at our institution since its inception. Methods  ETM usage data from the first 3 years of use (April 2016 to April 2019) were extracted from the EHR. Data collected included age of patient, date and time of task request, ward, unit, type of task, urgency of task, requestor role, and time to completion. Results  A total of 136,481 tasks were placed via the ETM in the study period. There were approximately 125 tasks placed each day (24-hour period). The most common time of task placement was around 6:00 p.m. Task placement peaked at approximately 8 a.m., 2 p.m., and 9 p.m.—consistent with nursing shift change times. In total, 63.16% of tasks were placed outside business hours, indicating predominant usage for after-hours task communication. The ETM was most highly utilized by surgical units. The majority of tasks were ordered by nurses for medical staff to complete (97.01%). A significant proportion (98.79%) of tasks was marked as complete on the ETM, indicating closed-loop feedback after tasks were requested. Conclusion  An ETM function embedded in our EHR has been highly utilized in our institution since its introduction. It has multiple benefits for the clinician in the form of efficiencies in workflow and improvement in communication and also workflow management. By allowing collection, tracking, audit, and prioritization of tasks, it also provides a stream of actionable data for quality-improvement activities.     

Uptake of an Integrated Electronic Questionnaire System in Community Pediatric Clinics

Objective  The study aimed to evaluate an integrated electronic questionnaire system implementation in outpatient community pediatric practices on workflow, completion rates, and recorded scores. Methods  We evaluated the implementation and outcomes of an integrated electronic questionnaire system at 45 community pediatric practices that used standardized questionnaires to screen for autism, depression, and substance use and to measure asthma control. Electronic health record (EHR) data for all well child visits were extracted for the 3 months before and after implementation. We used statistical process control charts to evaluate questionnaire completion rates and Chi-square tests to evaluate screening completion and positive screening rates. The collection and entry of questionnaire information was observed and timed. Results  EHR data included 107,120 encounters across 45 practices that showed significant and sustained improvement in completion rates for all questionnaires. The rate of recorded concerning questionnaires decreased for asthma control (19.3 vs. 12.8%, p  < 0.001), stayed the same for autism (96.6 vs. 96.2%, p  = 0.38), decreased for depression (9.5 vs. 6.7%, p ≤ 0.001), and increased for any substance use (9.8 vs. 12.8%, p  < 0.001). Twelve practices were observed, and patient time and staff time managing questionnaires were decreased after implementation. Discussion  Electronic questionnaire administration saved staff time and patient time. We report overall improvement in questionnaire completion rates, with notable variation in improvement in completion across practices and in change in concerning recorded result rates across measures. Conclusion  Conversion of four standard paper questionnaires to an integrated electronic system reduces patient and staff time while increasing completion rates when well integrated into routine care.