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.     

Transition to telemedicine and its impact on missed appointments in community-based clinics

Background and objectiveThe Coronavirus Aid, Relief, and Economic Security Act led to the rapid implementation of telemedicine across health care office settings. Whether this transition to telemedicine has any impact on missed appointments is yet to be determined. This study examined the relationship between telemedicine usage and missed appointments during the COVID-19 pandemic.MethodThis retrospective study used appointment-level data from 55 Federally Qualified Health Centre clinics in Texas between March and November 2020. To account for the nested data structure of repeated appointments within each patient, a mixed-effects multivariable logistic regression model was used to examine associations between telemedicine use and missed appointments, adjusting for patient sociodemographic characteristics, geographic classification, past medical history, and clinic characteristics. The independent variable was having a telemedicine appointment, defined as an audiovisual consultation started and finalized via a telemedicine platform. The outcome of interest was having a missed appointment (yes/no) after a scheduled and confirmed medical appointment. Results from this initial model were stratified by appointment type (in-person vs. telemedicine).ResultsThe analytic sample included 278,171 appointments for 85,413 unique patients. The overall missed appointment rate was 18%, and 25% of all appointments were telemedicine appointments. Compared to in-person visits, telemedicine visits were less likely to result in a missed appointment (OR = 0.87, p < .001). Compared to Whites, Asians were less likely to have a missed appointment (OR = 0.82, p < .001) while African Americans, Hispanics, and American Indians were all significantly more likely to have missed appointments (OR = 1.61, p < .001; OR = 1.19, p = .01; OR = 1.22, p < .01, respectively). Those accessing mental health services (OR = 1.57 for in-person and 0.78 for telemedicine) and living in metropolitan areas (OR = 1.15 for in-person and 0.82 for telemedicine) were more likely to miss in-person appointments but less likely to miss telemedicine appointments. Patients with frequent medical visits or those living with chronic diseases were more likely to miss in-person appointments but less likely to miss telemedicine appointments.ConclusionsTelemedicine is strongly associated with fewer missed appointments. Although our findings suggest a residual lag in minority populations, specific patient populations, including those with frequent prior visits or chronic conditions, those seeking mental health services, and those living in metropolitan areas were less likely to miss telemedicine appointments than in-person visits. These findings highlight how telemedicine can enable effective and accessible care by reducing missed healthcare appointments.

KEY MESSAGES

• Telemedicine was associated with 13% lower odds of missed appointments.
• Patients with frequent medical visits or those living with chronic diseases were less likely to miss telemedicine appointments but more likely to miss in-person appointments.
• Patients seeking mental health services were less likely to miss telemedicine appointments but more likely to miss in-person appointments.
• Similarly, those living in metropolitan areas were less likely to miss telemedicine appointments but more likely to miss in-person appointments.

     

The My Diabetes Care Patient Portal Intervention: Usability and Pre-Post Assessment

Background  My Diabetes Care (MDC) is a novel, multifaceted patient portal intervention designed to help patients better understand their diabetes health data and support self-management. MDC uses infographics to visualize and summarize patients'' diabetes health data, incorporates motivational strategies, and provides literacy level–appropriate educational resources. Objectives  We aimed to assess the usability, acceptability, perceptions, and potential impact of MDC. Methods  We recruited 69 participants from four clinics affiliated with Vanderbilt University Medical Center. Participants were given 1 month of access to MDC and completed pre- and post-questionnaires including validated measures of usability and patient activation, and questions about user experience. Results  Sixty participants completed the study. Participants'' mean age was 58, 55% were females, 68% were Caucasians, and 48% had limited health literacy (HL). Most participants (80%) visited MDC three or more times and 50% spent a total of ≥15 minutes on MDC. Participants'' median System Usability Scale (SUS) score was 78.8 [Q1, Q3: 72.5, 87.5] and significantly greater than the threshold value of 68 indicative of “above average” usability ( p  < 0.001). The median SUS score of patients with limited HL was similar to those with adequate HL (77.5 [72.5, 85.0] vs. 82.5 [72.5, 92.5]; p  = 0.41). Participants most commonly reported the literacy level–appropriate educational links and health data infographics as features that helped them better understand their diabetes health data (65%). All participants (100%) intended to continue to use MDC. Median Patient Activation Measure® scores increased postintervention (64.3 [55.6, 72.5] vs. 67.8 [60.6, 75.0]; p  = 0.01). Conclusion  Participants, including those with limited HL, rated the usability of MDC above average, anticipated continued use, and identified key features that improved their understanding of diabetes health data. Patient activation improved over the study period. Our findings suggest MDC may be a beneficial addition to existing patient portals.     

CB3-01: Comparison of Ethnicity and Race Categorization in Electronic Medical Records and by Self-report

Background/Aims Members of minority groups are more likely than non-minorities to have worse health outcomes. Electronic medical records (EMR) data are often used for research on health disparities, and can help identify patient risk factors, but accuracy of ethnicity and race data in the EMR is often questioned. Aims To compare HealthPartners Medical Group (HPMG) EMR data on ethnicity/race to self-reported classification. Methods We compared percent agreement of self-reported and EMR data on ethnicity/race among 1719 patients who expressed interest in a hypertension clinical trial, completed an eligibility phone screen, and consented to EMR review. Patients classified their ethnicity/race in two questions: Are you of Latino or Hispanic descent? (Yes, No, Don't know, Refused); How would you describe your race (Check all that apply) (American Indian/Alaskan Native, Asian, Black or African American, Native Hawaiian or Pacific Islander, White or Caucasian, Other, Don't know, Refused). EMR race categories allowed multiple selections among: White, Black, Asian, Hispanic, American Indian, Other, and No Answer. Results Race data was missing in 0.7% of phone screens and 1.2% of EMRs. Self-reported race was 79% white, 14% African American, 3% mixed, 2% other, 1% Asian, <1% Native American. In the EMR, race was recorded as 79% white, 14% African American, 3% mixed race, 1% Asian, <1% each for American Indian, and other. Overall agreement for race was 91.1%. EMR data agreed with self-report for 97% of those reporting white, 94% of those reporting African American, 83% Asian, 50% Native American, 9% mixed race and 6% other. Hispanic ethnicity was self-reported by 1.3% and coded for 2.4% in the EMR. EMR confirmed Hispanic ethnicity for 51% self-reporting Hispanic ethnicity. Discussion EMR race/ethnicity data was quite complete, and agreement of data sources was high overall and among whites, African Americans and Asians. Lower agreement was observed among Hispanic, Native American, and mixed race patients, subgroups that may be disproportionately affected by disparities. Some caution is needed in interpreting EMR-based results for those subgroups, and their proper classification in the EMR is warranted. Similar comparisons should be conducted in other settings and patient populations.     

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.     

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.     

eHealth Literacy of Medical and Health Science Students and Factors Affecting eHealth Literacy in an Ethiopian University: A Cross-Sectional Study

Background  eHealth literacy is individual''s ability to look for, understand, and evaluate health information from electronic sources. Integrating eHealth literacy to the health system could help lower health care costs and ensure health equity. Despite its importance, the eHealth literacy level in Ethiopia has not been studied on medical and health science students, who are important parties in the health system. Understanding their level of eHealth literacy augments practice of health care, efficiency in education, and use of eHealth technologies. Objective  This research study aims to determine eHealth literacy level and identify its associated factors among medical and health science students in University of Gondar (UoG). Methods  An institution-based cross-sectional study was conducted from March to May 2019 among undergraduate medical and health science students in the UoG. Stratified multistage sampling was used. The eHealth literacy scale was used to measure eHealth literacy. A binary logistic regression model was fitted to measure association between eHealth literacy and the independent variables. Results  A total of 801 students participated in this study with a 94.6% of response rate. The majority (60%) were male and previously lived-in urban areas (68%). The mean eHealth literacy score was 28.7 and 60% of the participants possessed high eHealth literacy. Using health-specific Web sites (adjusted odds ratio [AOR] = 2.84, 95% confidence interval [CI]: 1.86–4.33), having higher Internet efficacy (AOR = 2.26, 95% CI: 1.56–3.26), perceived usefulness of the Internet (AOR = 3.33, 95% CI: 1.95–5.69), medical app use (AOR = 1.70, 95% CI: 1.13–2.55), being female (AOR = 1.55, 95% CI: 1.08–2.22), and being health informatics student (AOR = 2.02, 95% CI: 1.149–3.148) affect a high eHealth literacy level. Conclusion  The level of eHealth literacy in this study was moderate. Using specific reputable health Web sites, using smartphone medical applications, and Internet efficacy determine eHealth literacy significantly.     

Sexual Orientation Demographic Data in a Clinical Cohort of Transgender Patients

Background  There are specific issues regarding sexual orientation (SO) collection and analysis among transgender and nonbinary patients. A limitation to meaningful SO and gender identity (GI) data collection is their consideration as a fixed trait or demographic data point. Methods  A de-identified patient database from a single electronic health record (EHR) that allows for searching any discrete data point in the EHR was used to query demographic data (sex assigned at birth and current GI) for transgender individuals from January 2011 to March 2020 at a large urban tertiary care academic health center. Results  A cohort of transgender individuals were identified by using EHR data from a two-step demographic question. Almost half of male identified (46.70%, n  = 85) and female identified (47.51%, n  = 86) individuals had “heterosexual/straight” input for SO. Overall, male and female identified (i.e., binary) GI aggregate categories had similar SO responses. Assigned male at birth (AMAB) nonbinary individuals ( n  = 6) had “homosexual/gay” SO data input. Assigned female at birth (AFAB) nonbinary individuals ( n  = 56) had almost half “something else” SO data input (41.67%, n  = 15). Individuals with “choose not to disclose” for GI ( n  = 249) almost all had “choose not to disclose” SO data (96.27%, n  = 232). Conclusion  Current SO categories do not fully capture transgender individuals'' identities and experiences, and limit the clinical and epidemiological utility of collecting this data in the current form. Anatomical assumptions based on SO should be seen as a potential shortcoming in over-reliance on SO as an indicator of screening needs and risk factors.     

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.     

Tracking Hospital Visitors/Chaperones during the COVID-19 Pandemic

Objective  The coronavirus disease (COVID-19) is an emerging infectious disease with strong infectious power and fatality rate. To protect national health, government agencies have regulations on hospital chaperoning and visiting. This article presents the development and implementation of a monitoring system for hospital visiting and chaperoning during the COVID-19 pandemic. The study aimed to create a hospital visiting and chaperoning monitor system that uses nation-wide data sources to more accurately screen hospital visitors and chaperones, assist contract tracing, and prevent transmission of severe acute respiratory syndrome coronavirus 2. Methods  This project was implemented in 57 ward units of an academic medical center. The system was connected to the National Health Insurance (NHI) system and Hospital Information System (HIS), and built on the data of everyone who accessed either the hospital or ward using an NHI smart card or national identification card. To shorten the time for manual identification, we also developed a new system of “app for appointment visits and chaperones” to make appointments online. Results  After the implementation of the system, data from visitors and chaperones in the nursing information system could be accessed. Given that all data were registered in the HIS visiting/chaperoning monitor system, an epidemic investigation could be performed whenever there was a confirmed case. Conclusion  Through the establishment of this system, people entering the ward can be accurately controlled, and all the contacts of potential cases can be traced.     

Leveraging American College of Obstetricians and Gynecologists Guidelines for Point-of-Care Decision Support in Obstetrics

Background  The American College of Obstetricians and Gynecologists (ACOG) provides numerous narrative documents containing formal recommendations and additional narrative guidance within the text. These guidelines are not intended to provide a complete “care pathway” for patient management, but these elements of guidance can be useful for clinical decision support (CDS) in obstetrical and gynecologic care and could be exposed within electronic health records (EHRs). Unfortunately, narrative guidelines do not easily translate into computable CDS guidance. Objective  This study aimed to describe a method of translating ACOG clinical guidance into clear, implementable items associated with specific obstetrical problems for integration into the EHR. Methods  To translate ACOG clinical guidance in Obstetrics into implementable CDS, we followed a set of steps including selection of documents, establishing a problem list, extraction and classification of recommendations, and assigning tasks to those recommendations. Results  Our search through ACOG clinical guidelines produced over 500 unique documents. After exclusions, and counting only sources relevant to obstetrics, we used 245 documents: 38 practice bulletins, 113 committee opinions, 16 endorsed publications, 1 practice advisory, 2 task force and work group reports, 2 patient education, 2 obstetric care consensus, 60 frequently asked questions (FAQ), 1 women''s health care guidelines, 1 Prolog series, and 9 others (non-ACOG). Recommendations were classified as actionable ( n  = 576), informational ( n  = 493), for in-house summary ( n  = 124), education/counseling ( n  = 170), policy/advocacy ( n  = 33), perioperative care ( n  = 4), delivery recommendations ( n  = 50), peripartum care ( n  = 13), and non-ACOG ( n  = 25). Conclusion  We described a methodology of translating ACOG narrative into a semi-structured format that can be more easily applied as CDS in the EHR. We believe this work can contribute to developing a library of information within ACOG that can be continually updated and disseminated to EHR systems for the most optimal decision support. We will continue documenting our process in developing executable code for decision support.     

Patient Race,Ethnicity, Language,and Pain Severity in Primary Care: A Retrospective Electronic Health Record Study

BackgroundPatient race, ethnicity, and culture including language are intertwined and may influence patient reporting of pain severity.PurposeTo describe documentation of patient's self-reported pain presence and severity by race, ethnicity, and language, specifically, Spanish, Hmong, Lao, or Khmer requiring an interpreter or English.Design and SampleRetrospective, electronic health record clinical data mining study of 79,195 patient visits with documented pain scores from one primary care clinic.MethodsHurdle regression was used to explore the effect of race, ethnicity, and language on the chances of having any pain (vs. no pain) and pain severity for visits with pain scores ≥1, controlling for age, sex, and documentation of a pain diagnosis. Mann-Whitney tests were used to explore the influence of English vs. non-English language on pain severity within a race or ethnicity category.ResultsPain scores were higher for limited English proficiency, compared with English-speaking, patients within the Asian race or Hispanic/Latino ethnicity category. Older age, female sex, pain diagnosis, Black or African American race, and Spanish or Lao language increased the chance of having any pain. These same factors, plus American Indian or Alaska Native race, contributed to higher pain severity. Asian race, in contrast, decreased the chance of reporting any pain and contributed to lesser pain severity.ConclusionsRace, in addition to a new area of focus, language, impacted both the chances of reporting any pain and pain severity. Additional research is needed on the impact of language barriers on pain severity reporting, documentation, and differences in pain outcomes and disparities.     

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.     

Preferred Functions of Personal Health Records in Rural Primary Health Clinics in Canada: Health Care Team Perspectives

Background  Personal health records (PHR) provide opportunities for improved patient engagement, collection of patient-generated data, and overcome health-system inefficiencies. While PHR use is increasing, uptake in rural populations is lower than in urban areas. Objectives  The study aimed to identify priorities for PHR functionality and gain insights into meaning, value, and use of patient-generated data for rural primary care providers. Methods  We performed PHR preimplementation focus groups with rural providers and their health care teams from five primary care clinics in a sparsely populated mountainous region of British Columbia, Canada to obtain their understanding of PHR functionality, needs, and perceived challenges. Results  Eight general practitioners (GP), five medical office assistants, two nurse practitioners (NP), and two registered nurses (14 females and 3 males) participated in focus groups held at their respective clinics. Providers (GPs, NPs, and RNs) had been practicing for a median of 9.5 (range = 1–38) years and had used an electronic medical record for 7.0 (1–20) years. Participants expressed interest in incorporating functionality around two-way communication and appointment scheduling, previsit data gathering, patient and provider data sharing, virtual care including visits using videoconferencing tools, and postvisit sharing of educational materials. Three further themes emerged from the focus groups: (1) the context in which the providers'' practice matters, (2) the need for providing patients and providers with choice (e.g., which data to share, who gets to initiate/respond in communications, and processes around virtual care visits), and (3) perceived risks of system use (e.g., increased complexity for older patients and workload barriers for the health care team). Conclusion  Rural primary care teams perceived PHR opportunities for increased patient engagement and access to patient-generated data, while worries about changes in workflow were the biggest perceived risk. Recommendations for PHR adoption in a rural primary health network include setting provider-patient expectations about response times, ability to share notes selectively, and automatically augmented note-taking from virtual-care visits.     

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.     

Impact of the COVID-19 pandemic on ophthalmologic outpatient care: experience from an Italian Tertiary Medical Center

PurposeTo evaluate the impact the COVID-19-related national lockdown has had on Ophthalmologic Outpatient Care in an Italian Tertiary Medical Centre.MethodsWe reviewed all the performances that were carried out as outpatient services at our department between 1 January 2020 and 30 November 2020. We compared data among four different periods: from 1 January 2020 to 17 March 2020 (“Pre-Lockdown”); from 18 March 2020 to 17 May 2020 (Lockdown); from 18 May 2020 to 2 November 2020 (Post-Lockdown) and from 3 November 2020 to 30 November 2020 (Regional Lockdown).ResultsThe overall number of performed routine outpatient visits per day (ROVs) was 11,871 (Mean ± SD = 35.76 ± 17.81), whereas booked appointments (BAs) were 21272 (Mean ± SD = 63.86 ± 9.27), meaning a decline in the number of ROVs by 44.01%. (Mean ± SD = 28.10 ± 12.11, p<.001). Post-Lockdown and Regional Lockdown clinical activities, dropped respectively by 31 and 25.14% (38.87 ± 3.88 vs. 56.34 ± 11.06, p<.001 and 6.04 ± 4.51 vs. 56.34 ± 11.06 p<.001). The number of BAs per day decreased during the pandemic, going from a mean of 77.81 ± 2.57 booked appointments per day before the lockdown, to a mean of 53.14 ± 4.94, 61.80 ± 4.62 and 72.07 ± 1.09 appointments per day respectively during the lockdown, the post-lockdown and the regional lockdown periods.ConclusionsDuring the various lockdown periods, at our institution the volume of outpatient ophthalmological visits drastically dropped. This testifies the dramatic impact the COVID-19 pandemic has had on the supply of ophthalmic care.     

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.     

Applicability of ancestral genotyping in pharmacogenomic research with hormonal contraception

To compare etonogestrel pharmacokinetic and pharmacodynamic outcomes by both self‐reported race/ethnicity and genetically determined ancestry among contraceptive implant users. We conducted a secondary analysis of our parent pharmacogenomic study of 350 implant users. We genotyped these reproductive‐aged (18–45 years) women for 88 ancestry‐informative single nucleotide polymorphisms. We then assigned each participant a proportion value for African (AFR), European (EUR), and Indigenous American (AMR) ancestry based on reference population data. We correlated genetic ancestry with self‐reported race/ethnicity and utilized genetic ancestry proportion values as variables for previously performed association analyses with serum etonogestrel concentrations and progestin‐related side effects (e.g., bothersome bleeding and subjective weight gain). We successfully estimated genetically determined ancestry for 332 participants. EUR, AFR, and AMR ancestry were each highly correlated with self‐reported White/non‐Hispanic race (r = 0.64, p = 4.14 × 10⁻⁴⁰), Black/African American race (r = 0.88, p = 1.36 × 10⁻¹⁰⁷), and Hispanic/Latina ethnicity (r = 0.68, p = 4.03 × 10⁻⁴⁷), respectively. Neither genetically determined ancestry nor self‐reported race/ethnicity were significantly associated with serum etonogestrel concentrations. AFR ancestry and self‐reported Black race had similar associations with reporting monthly periods (odds ratio [OR] 2.18, p = 0.09 vs. OR 2.22, p = 0.02) and having received treatment for bothersome bleeding (OR 5.19, p = 0.005 vs. OR 4.73, p = 2.0 × 10⁻⁴). In multivariable logistic regression for subjective weight gain, AMR ancestry dropped out of the model in preference for self‐reported Hispanic/Latina ethnicity. We found no new associations between genetically determined ancestry and contraceptive implant pharmacodynamics/pharmacokinetics. Self‐reported race/ethnicity were strong surrogates for genetically determined ancestry among this population of contraceptive implant users. Our data suggest that self‐reported race/ethnicity, capturing societal and cultural aspects, remain important to the investigation of progestin‐related side effects.

Study Highlights

• WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?

Individual women using the exact same contraceptive method demonstrate widely variable pharmacokinetics and side effect profiles. Self‐reported race/ethnicity has associations with progestin‐related side effects among etonogestrel contraceptive implant users. Self‐reported race/ethnicity and genetically determined ancestry may provide complementary information, but contraceptive research does not routinely evaluate for genetically determined ancestry.

• WHAT QUESTION DID THIS STUDY ADDRESS?

Is genetically determined ancestry associated with pharmacokinetic or pharmacodynamic (side effect) outcomes among contraceptive implant users?

• WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE?

Genetically determined ancestry was highly correlated with self‐reported race/ethnicity among this population of young contraceptive implant users. Genetically determined ancestry was not associated with etonogestrel pharmacokinetics and had very similar associations as self‐reported race/ethnicity with progestin‐related side effects. However, the associations with genetically determined ancestry were at higher risk of stemming from type 1 errors (i.e., higher p values) compared with the associations with self‐reported race/ethnicity.

• HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE?

In hormonal contraceptive research, self‐reported race/ethnicity remains an important variable as it may capture sociodemographic differences in the contraceptive experience unrelated to genetic differences.     

Some characteristics of hyperglycaemic crisis differ between patients with and without COVID-19 at a safety-net hospital in a cross-sectional study

ObjectiveTo compare patients with DKA, hyperglycaemic hyperosmolar syndrome (HHS), or mixed DKA-HHS and COVID-19 [COVID (+)] to COVID-19-negative (−) [COVID (−)] patients with DKA/HHS from a low-income, racially/ethnically diverse catchment area.MethodsA cross-sectional study was conducted with patients admitted to an urban academic medical center between 1 March and 30 July 2020. Eligible patients met lab criteria for either DKA or HHS. Mixed DKA-HHS was defined as meeting all criteria for either DKA or HHS with at least 1 criterion for the other diagnosis.ResultsA total of 82 participants were stratified by COVID-19 status and type of hyperglycaemic crisis [26 COVID (+) and 56 COVID (−)]. A majority were either Black or Hispanic. Compared with COVID (−) patients, COVID (+) patients were older, more Hispanic and more likely to have type 2 diabetes (T2D, 73% vs 48%, p < .01). COVID(+) patients had a higher mean pH (7.25 ± 0.10 vs 7.16 ± 0.16, p < .01) and lower anion gap (18.7 ± 5.7 vs 22.7 ± 6.9, p = .01) than COVID (−) patients. COVID (+) patients were given less intravenous fluids in the first 24 h (2.8 ± 1.9 vs 4.2 ± 2.4 L, p = .01) and were more likely to receive glucocorticoids (95% vs. 11%, p < .01). COVID (+) patients may have taken longer to resolve their hyperglycaemic crisis (53.3 ± 64.8 vs 28.8 ± 27.5 h, p = .09) and may have experienced more hypoglycaemia <3.9 mmol/L (35% vs 19%, p = .09). COVID (+) patients had a higher length of hospital stay (LOS, 14.8 ± 14.9 vs 6.5 ± 6.0 days, p = .01) and in-hospital mortality (27% vs 7%, p = .02).DiscussionCompared with COVID (−) patients, COVID (+) patients with DKA/HHS are more likely to have T2D. Despite less severe metabolic acidosis, COVID (+) patients may require more time to resolve the hyperglycaemic crisis and experience more hypoglycaemia while suffering greater LOS and risk of mortality. Larger studies are needed to examine whether differences in management between COVID (+) and (−) patients affect outcomes with DKA/HHS.