Text Messaging Real-Time COVID-19 Clinical Guidance to Hospital Employees

Background  During the initial days of the coronavirus disease 2019 (COVID-19) pandemic, hospital-wide practices rapidly evolved, and hospital employees became a critical population for receiving consistent and timely communication about these changes. Objectives  We aimed to rapidly implement enterprise text messaging as a crisis communication intervention to deliver key COVID-related safety and practice information directly to hospital employees. Methods  Utilizing a secure text-messaging platform already routinely used in direct patient care, we sent 140-character messages containing targeted pandemic-related updates to on-duty hospital employees three times per week for 13 weeks. This innovation was evaluated through the analysis of aggregate “read” receipts from each message. Effectiveness was assessed by rates of occupational exposures to COVID-19 and by two cross-sectional attitudinal surveys administered to all text-message recipients. Results  On average, each enterprise text message was sent to 1,997 on-duty employees. Analysis of “read” receipts revealed that on average, 60% of messages were consistently read within 24 hours of delivery, 34% were read in 2 hours, and 16% were read in 10 minutes. Readership peaked and fell in the first week of messaging but remained consistent throughout the remainder of the intervention. A survey administered after 2 weeks revealed that 163 (79%) users found enterprise texts “valuable,” 152 (73%) users would recommend these texts to their colleagues, and 114 (55%) users preferred texts to email. A second survey at 9 weeks revealed that 109 (80%) users continued to find texts “valuable.” Enterprise messaging, in conjunction with the system''s larger communication strategy, was associated with a decrease in median daily occupational exposure events (nine events per day premessaging versus one event per day during messaging). Conclusion  Enterprise text messages sent to hospital-employee smartphones are an efficient and effective strategy for urgent communications. Hospitals may wish to leverage this technology during times of routine operations and crisis management.     

Moving Faster than the COVID-19 Pandemic: The Rapid,Digital Transformation of a Public Health System

Background  Queensland, Australia has been successful in containing the COVID-19 pandemic. Underpinning that response has been a highly effective virus containment strategy which relies on identification, isolation, and contact tracing of cases. The dramatic emergence of the COVID-19 pandemic rendered traditional paper-based systems for managing contact tracing no longer fit for purpose. A rapid digital transformation of the public health contact tracing system occurred to support this effort. Objectives  The objectives of the digital transformation were to shift legacy systems (paper or standalone electronic systems) to a digitally enabled public health system, where data are centered around the consumer rather than isolated databases. The objective of this paper is to outline this case study and detail the lessons learnt to inform and give confidence to others contemplating digitization of public health systems in response to the COVID-19 pandemic. Methods  This case study is set in Queensland, Australia. Universal health care is available. A multidisciplinary team was established consisting of clinical informaticians, developers, data strategists, and health information managers. An agile “pair-programming” approach was undertaken to application development and extensive change efforts were made to maximize adoption of the new digital workflows. Data governance and flows were changed to support rapid management of the pandemic. Results  The digital coronavirus application (DCOVA) is a web-based application that securely captures information about people required to quarantine and creates a multiagency secure database to support a successful containment strategy. Conclusion  Most of the literature surrounding digital transformation allows time for significant consultation, which was simply not possible under crisis conditions. Our observation is that staff was willing to adopt new digital systems because the reason for change (the COVID-19 pandemic) was clearly pressing. This case study highlights just how critical a unified purpose, is to successful, rapid digital transformation.     

Improving COVID-19 Research of University Hospitals in Germany: Formative Usability Evaluation of the CODEX Feasibility Portal

Background  Within the German “Network University Medicine,” a portal is to be developed to enable researchers to query on novel coronavirus disease 2019 (COVID-19) data from university hospitals for assessing the feasibility of a clinical study. Objectives  The usability of a prototype for federated feasibility queries was evaluated to identify design strengths and weaknesses and derive improvement recommendations for further development. Methods  In the course of a remote usability test with the thinking-aloud method and posttask interviews, 15 clinical researchers evaluated the usability of a prototype of the Feasibility Portal. The identified usability problems were rated according to severity, and improvement recommendations were derived. Results  The design of the prototype was rated as simple, intuitive, and as usable with little effort. The usability test reported a total of 26 problems, 8 of these were rated as “critical.” Usability problems and revision recommendations focus primarily on improving the visual distinguishability of selected inclusion and exclusion criteria, enabling a flexible approach to criteria linking, and enhancing the free-text search. Conclusion  Improvement proposals were developed for these user problems which will guide further development and the adaptation of the portal to user needs. This is an important prerequisite for correct and efficient use in everyday clinical work in the future. Results can provide developers of similar systems with a good starting point for interface conceptualizations. The methodological approach/the developed test guideline can serve as a template for similar evaluations.     

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.     

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.     

Health Intelligence Atlas: A Core Tool for Public Health Intelligence

Background  The dramatic increase in complexity and volume of health data has challenged traditional health systems to deliver useful information to their users. The novel coronavirus disease 2019 (COVID-19) pandemic has further exacerbated this problem and demonstrated the critical need for the 21st century approach. This approach needs to ingest relevant, diverse data sources, analyze them, and generate appropriate health intelligence products that enable users to take more effective and efficient actions for their specific challenges. Objectives  This article characterizes the Health Intelligence Atlas (HI-Atlas) development and implementation to produce Public Health Intelligence (PHI) that supports identifying and prioritizing high-risk communities by public health authorities. The HI-Atlas moves from post hoc observations to a proactive model-based approach for preplanning COVID-19 vaccine preparedness, distribution, and assessing the effectiveness of those plans. Results  Details are presented on how the HI-Atlas merged traditional surveillance data with social intelligence multidimensional data streams to produce the next level of health intelligence. Two-model use cases in a large county demonstrate how the HI-Atlas produced relevant PHI to inform public health decision makers to (1) support identification and prioritization of vulnerable communities at risk for COVID-19 spread and vaccine hesitancy, and (2) support the implementation of a generic model for planning equitable COVID-19 vaccine preparedness and distribution. Conclusion  The scalable models of data sources, analyses, and smart hybrid data layer visualizations implemented in the HI-Atlas are the Health Intelligence tools designed to support real-time proactive planning and monitoring for COVID-19 vaccine preparedness and distribution in counties and states.     

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.     

Rapid Implementation of a Complex,Multimodal Technology Response to COVID-19 at an Integrated Community-Based Health Care System

Background  The rapid spread of severe acute respiratory syndrome coronavirus-2 or SARS-CoV-2 necessitated a scaled treatment response to the novel coronavirus disease 2019 (COVID-19). Objective  This study aimed to characterize the design and rapid implementation of a complex, multimodal, technology response to COVID-19 led by the Intermountain Healthcare''s (Intermountain''s) Care Transformation Information Systems (CTIS) organization to build pandemic surge capacity. Methods  Intermountain has active community-spread cases of COVID-19 that are increasing. We used the Centers for Disease Control and Prevention Pandemic Intervals Framework (the Framework) to characterize CTIS leadership''s multimodal technology response to COVID-19 at Intermountain. We provide results on implementation feasibility and sustainability of health information technology (HIT) interventions as of June 30, 2020, characterize lessons learned and identify persistent barriers to sustained deployment. Results  We characterize the CTIS organization''s multimodal technology response to COVID-19 in five relevant areas of the Framework enabling (1) incident management, (2) surveillance, (3) laboratory testing, (4) community mitigation, and (5) medical care and countermeasures. We are seeing increased use of traditionally slow-to-adopt technologies that create additional surge capacity while sustaining patient safety and care quality. CTIS leadership recognized early that a multimodal technology intervention could enable additional surge capacity for health care delivery systems with a broad geographic and service scope. A statewide central tracking system to coordinate capacity planning and management response is needed. Order interoperability between health care systems remains a barrier to an integrated response. Conclusion  The rate of future pandemics is estimated to increase. The pandemic response of health care systems, like Intermountain, offers a blueprint for the leadership role that HIT organizations can play in mainstream care delivery, enabling a nimbler, virtual health care delivery system that is more responsive to current and future needs.     

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.     

The Effect of WeChat on Parental Care Burden,Anxiety, and Depression in Children after CHD Surgery during COVID-19 Pandemic

Objectives  This study aimed to explore the effect of applying WeChat in the follow-up and health education of children after congenital heart disease (CHD) surgery during the coronavirus disease 2019 (COVID-19) epidemic. Methods  Data from 135 children were retrospectively analyzed. The care burden, anxiety, depression, and satisfaction of the parents of patients at home were analyzed and compared. Results  One month after discharge, the Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), Zarit Burden Interview (ZBI), and Patient Satisfaction Questionnaire-18 scores of the WeChat follow-up group were significantly better than those of the outpatient follow-up group ( p  < 0.05). Compared with the discharge time, the SAS, SDS, and ZBI scores were significantly improved in the WeChat follow-up group but not in the outpatient follow-up group ( p  < 0.05). Conclusion  During the COVID-19 epidemic, the application of WeChat to the follow-up management of children after CHD surgery can effectively reduce care burden and relieve anxiety and depression in parents at home. It can also improve the satisfaction of parents with medical treatment.     

COVID-19 Mass Vaccination Resource Calculator

Background  Despite the recent emergency use authorization of two vaccines for the prevention of the 2019 novel coronavirus (COVID-19) disease, vaccination rates are lower than expected. Vaccination efforts may be hampered by supply, delivery, storage, patient prioritization, administration infrastructure or logistics problems. To address the last issue, our institution is sharing publically a calculator to optimize the management of staffing and facility resources in an outpatient mass vaccination effort. Objective  By sharing our calculator locally and through this paper, we aim to help health organizations administering vaccines optimize resource allocation while maximizing efficiency. Methods  Our calculator determines the maximum number of vaccinations that can be administered per hour, the number of check-in staff (clerks) needed, the number of vaccination staff (nurses) needed, and the required room capacity needed for the vaccination and the mandatory 15-minute observation period after inoculation. Results  We provide a functional version of the calculator, allowing users to replicate the calculation for their own vaccine events. Conclusion  An efficient and organized vaccination program is critical to halting the spread of COVID-19. By sharing this calculator, it is our hope that other organizations may use it to facilitate rapid and efficient vaccination.     

U.S. COVID-19 State Government Public Dashboards: An Expert Review

Background  In the United States, all 50 state governments deployed publicly viewable dashboards regarding the novel coronavirus disease 2019 (COVID-19) to track and respond to the pandemic. States dashboards, however, reflect idiosyncratic design practices based on their content, function, and visual design and platform. There has been little guidance for what state dashboards should look like or contain, leading to significant variation. Objectives  The primary objective of our study was to catalog how information, system function, and user interface were deployed across the COVID-19 state dashboards. Our secondary objective was to group and characterize the dashboards based on the information we collected using clustering analysis. Methods  For preliminary data collection, we developed a framework to first analyze two dashboards as a group and reach agreement on coding. We subsequently doubled coded the remaining 48 dashboards using the framework and reviewed the coding to reach total consensus. Results  All state dashboards included maps and graphs, most frequently line charts, bar charts, and histograms. The most represented metrics were total deaths, total cases, new cases, laboratory tests, and hospitalization. Decisions on how metrics were aggregated and stratified greatly varied across dashboards. Overall, the dashboards were very interactive with 96% having at least some functionality including tooltips, zooming, or exporting capabilities. For visual design and platform, we noted that the software was dominated by a few major organizations. Our cluster analysis yielded a six-cluster solution, and each cluster provided additional insights about how groups of states engaged in specific practices in dashboard design. Conclusion  Our study indicates that states engaged in dashboard practices that generally aligned with many of the goals set forth by the Centers for Disease Control and Prevention, Essential Public Health Services. We highlight areas where states fall short of these expectations and provide specific design recommendations to address these gaps.     

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.     

Opportunities and Challenges of Telehealth in Disease Management during COVID-19 Pandemic: A Scoping Review

Objective  The novel coronavirus disease 2019 (COVID-19) pandemic is an unexpected universal problem that has changed health care access across the world. Telehealth is an effective solution for health care delivery during disasters and public health emergencies. This study was conducted to summarize the opportunities and challenges of using telehealth in health care delivery during the COVID-19 pandemic. Methods  A structured search was performed in the Web of Science, PubMed, Science Direct, and Scopus databases, as well as the Google Scholar search engine, for studies published until November 4, 2020. The reviewers analyzed 112 studies and identified opportunities and challenges. This review followed the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) protocols. Quality appraisal was done according to the Mixed Methods Appraisal Tool (MMAT) version 2018. Thematic analysis was applied for data analysis. Results  A total of 112 unique opportunities of telehealth application during the pandemic were categorized into 4 key themes, such as (1) clinical, (2) organizational, (3) technical, and (4) social, which were further divided into 11 initial themes and 26 unique concepts. Furthermore, 106 unique challenges were categorized into 6 key themes, such as (1) legal, (2) clinical, (3) organizational, (40 technical, (5) socioeconomic, and (6) data quality, which were divided into 16 initial themes and 37 unique concepts altogether. The clinical opportunities and legal challenges were the most frequent opportunities and challenges, respectively. Conclusion  The COVID-19 pandemic significantly accelerated the use of telehealth. This study could offer useful information to policymakers about the opportunities and challenges of implementing telehealth for providing accessible, safe, and efficient health care delivery to the patient population during and after COVID-19. Furthermore, it can assist policymakers to make informed decisions on implementing telehealth in response to the COVID-19 pandemic by addressing the obstacles ahead.     

传染病和死亡网络直报系统与医院信息系统连接初探

目的通过试点解决目前传染病和死亡网络直报系统与医院信息系统（医院HIS系统）之间的连通,实现传染病报告卡和死亡报告卡的直接抽取和数据的上报,同时建立相应的管理规范和认证程序。方法3家试点医院在项目实施期间,完成医院HIS系统的接口及流程改造,在数据交换接口中,使用Web Service的方式来进行数据交换。通过系统后台数据库日志,监控上传数据质量。结果3家试点医院在项目实施期间,成功实现传染病和死亡病例的自动上报。结论本次试点项目中的网络直报系统与医院HIS系统连接技术可以为未来在全国范围内实现系统间的连接提供参考。 本项目为传染病疫情和死亡病例的报告质量的改善可以提供技术保障。     

A qualitative investigation of hospital visitors’ experiences using the analytic lens of liminality: Informing nursing practice and policy

This research aimed to inform nursing practice and policy by identifying satisfying and problematic experiences of hospital visitors during the hospitalisation episode of a significant other. An extensive contextual review revealed that healthcare systems in advanced economies face multiple pressures and that in England, the government leaves the determination of hospital visiting rules to individual trusts. The analytic lens of liminality provides rich interpretations of visitors’ accounts and demonstrates the importance to visitors of structure (hospital rules and systems) and communitas (social bonding among liminal personae). Supportive hospital structures reduce the challenges of liminality and increase satisfaction. The data further suggest an extension to current understandings of liminality. Strong structure and successful communitas permit a safe exit from liminality after the hospitalisation episode for visitors with a close emotional bond with the patient.     

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.