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Background Physician fatigue increases the likelihood of medical errors. Eye-tracking technology offers an unobtrusive and objective way to measure fatigue but has only been implemented in controlled settings. Objective Our objective was to determine the feasibility of capturing physiological indicators of fatigue using eye-tracking technology in a real-world clinical setting. Methods A mixed-methods feasibility study was performed in a convenience sample of clinicians practicing in an urban, academic emergency department from November 11 to December 15, 2021. Outcomes included fatigue assessed at the beginning and end of each shift via eye-tracking (with low scores indicating greater fatigue) and self-report. Results Among 15 participants, self-reported fatigue and task load increased from the beginning to the end of their shift (fatigue visual analog scale [FVAS] 3.7–4.6, p = 0.04; physician task load [PTL] 97.7–154.3, p = 0.01). It was feasible to collect eye-tracking data at a fixed computer workstation with twice daily calibration and 61% capture of reliable data when the clinician was working at the study computer. Eye-tracking metrics did not change significantly from the beginning to the end of the shift. Eye metric fatigue score was associated with the change in PTL score (r 0.59, p = 0.02) but not FVAS. This association persisted after adjusting for age, gender, and role, with every 10-point increase in PTL, there was a 0.02-point increase in fatigue score (p = 0.04). Conclusion It is unclear whether the inability to detect fatigue via eye-tracking in routine clinical care was due to confounding factors, the technology, study design, sample size, or an absence of physiological fatigue. Further research and advances in functionality are needed to determine the eye-tracking technology's role in measuring clinician fatigue in routine care.

Pragmatic clinical trials (PCTs) focus on correlation between treatment and outcomes in real-world clinical practice, yet a guide highlighting key study considerations and design types for emergency medicine investigators pursuing this important study type is not available. Investigators conducting emergency department (ED)-based PCTs face multiple decisions within the planning phase to ensure robust and meaningful study findings. The PRagmatic Explanatory Continuum Indicator Summary 2 (PRECIS-2) tool allows trialists to consider both pragmatic and explanatory components across nine domains, shaping the trial design to the purpose intended by the investigators. Aside from the PRECIS-2 tool domains, ED-based investigators conducting PCTs should also consider randomization techniques, human subjects concerns, and integration of trial components within the electronic health record. The authors additionally highlight the advantages, disadvantages, and rationale for the use of four common randomized study design types to be considered in PCTs: parallel, crossover, factorial, and stepped-wedge. With increasing emphasis on the conduct of PCTs, emergency medicine investigators will benefit from a rigorous approach to clinical trial design.

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This cross-sectional study investigates rates of patients who left emergency departments without being seen from 2017 to 2021.

This cross-sectional study uses national benchmarking data to evaluate hospital occupancy and emergency department boarding during the COVID-19 pandemic.

Study objective People with opioid use disorder are vulnerable to disruptions in access to addiction treatment and social support during the COVID-19 pandemic. Our study objective was to understand changes in emergency department (ED) utilization following a nonfatal opioid overdose during COVID-19 compared to historical controls in 6 healthcare systems across the United States. Methods Opioid overdoses were retrospectively identified among adult visits to 25 EDs in Alabama, Colorado, Connecticut, North Carolina, Massachusetts, and Rhode Island from January 2018 to December 2020. Overdose visit counts and rates per 100 all-cause ED visits during the COVID-19 pandemic were compared with the levels predicted based on 2018 and 2019 visits using graphical analysis and an epidemiologic outbreak detection cumulative sum algorithm. Results Overdose visit counts increased by 10.5% (n=3486; 95% confidence interval [CI] 4.18% to 17.0%) in 2020 compared with the counts in 2018 and 2019 (n=3020 and n=3285, respectively), despite a 14% decline in all-cause ED visits. Opioid overdose rates increased by 28.5% (95% CI 23.3% to 34.0%) from 0.25 per 100 ED visits in 2018 to 2019 to 0.32 per 100 ED visits in 2020. Although all 6 studied health care systems experienced overdose ED visit rates more than the 95th percentile prediction in 6 or more weeks of 2020 (compared with 2.6 weeks as expected by chance), 2 health care systems experienced sustained outbreaks during the COVID-19 pandemic. Conclusion Despite decreases in ED visits for other medical emergencies, the numbers and rates of opioid overdose-related ED visits in 6 health care systems increased during 2020, suggesting a widespread increase in opioid-related complications during the COVID-19 pandemic. Expanded community- and hospital-based interventions are needed to support people with opioid use disorder and save lives during the COVID-19 pandemic.

ObjectiveTo determine the effect of a user centered clinical decision support tool versus usual care on rates of initiation of buprenorphine in the routine emergency care of individuals with opioid use disorder.DesignPragmatic cluster randomized controlled trial (EMBED).Setting18 emergency department clusters across five healthcare systems in five states representing the north east, south east, and western regions of the US, ranging from community hospitals to tertiary care centers, using either the Epic or Cerner electronic health record platform.Participants599 attending emergency physicians caring for 5047 adult patients presenting with opioid use disorder.InterventionA user centered, physician facing clinical decision support system seamlessly integrated into user workflows in the electronic health record to support initiating buprenorphine in the emergency department by helping clinicians to diagnose opioid use disorder, assess the severity of withdrawal, motivate patients to accept treatment, and complete electronic health record tasks by automating clinical and after visit documentation, order entry, prescribing, and referral.Main outcome measuresRate of initiation of buprenorphine (administration or prescription of buprenorphine) in the emergency department among patients with opioid use disorder. Secondary implementation outcomes were measured with the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework.Results1 413 693 visits to the emergency department (775 873 in the intervention arm and 637 820 in the usual care arm) from November 2019 to May 2021 were assessed for eligibility, resulting in 5047 patients with opioid use disorder (2787 intervention arm, 2260 usual care arm) under the care of 599 attending physicians (340 intervention arm, 259 usual care arm) for analysis. Buprenorphine was initiated in 347 (12.5%) patients in the intervention arm and in 271 (12.0%) patients in the usual care arm (adjusted generalized estimating equations odds ratio 1.22, 95% confidence interval 0.61 to 2.43, P=0.58). Buprenorphine was initiated at least once by 151 (44.4%) physicians in the intervention arm and by 88 (34.0%) in the usual care arm (1.83, 1.16 to 2.89, P=0.01).ConclusionsUser centered clinical decision support did not increase patient level rates of initiating buprenorphine in the emergency department. Although streamlining and automating electronic health record workflows can potentially increase adoption of complex, unfamiliar evidence based practices, more interventions are needed to look at other barriers to the treatment of addiction and increase the rate of initiating buprenorphine in the emergency department in patients with opioid use disorder.Trial registrationClinicalTrials.govNCT03658642.

The stepped wedge cluster randomized design has received increasing attention in pragmatic clinical trials and implementation science research. The key feature of the design is the unidirectional crossover of clusters from the control to intervention conditions on a staggered schedule, which induces confounding of the intervention effect by time. The stepped wedge design first appeared in the Gambia hepatitis study in the 1980s. However, the statistical model used for the design and analysis was not formally introduced until 2007 in an article by Hussey and Hughes. Since then, a variety of mixed-effects model extensions have been proposed for the design and analysis of these trials. In this article, we explore these extensions under a unified perspective. We provide a general model representation and regard various model extensions as alternative ways to characterize the secular trend, intervention effect, as well as sources of heterogeneity. We review the key model ingredients and clarify their implications for the design and analysis. The article serves as an entry point to the evolving statistical literatures on stepped wedge designs.

Objectives Adoption of emergency department (ED) initiation of buprenorphine (BUP) for opioid use disorder (OUD) into routine emergency care has been slow, partly due to clinicians’ unfamiliarity with this practice and perceptions that it is complicated and time‐consuming. To address these barriers and guide emergency clinicians through the process of BUP initiation, we implemented a user‐centered computerized clinical decision support system (CDS). This study was conducted to assess the feasibility of implementation and to evaluate the preliminary efficacy of the intervention to increase the rate of ED‐initiated BUP. Methods An interrupted time series study was conducted in an urban, academic ED from April 2018 to February 2019 (preimplementation phase), March 2019 to August 2019 (implementation phase), and September 2019 to December 2019 (maintenance phase) to study the effect of the intervention on adult ED patients identified by a validated electronic health record (EHR)‐based computable phenotype consisting of structured data consistent with potential cases of OUD who would benefit from BUP treatment. The intervention offers flexible CDS for identification of OUD, assessment of opioid withdrawal, and motivation of readiness to start treatment and automates EHR activities related to ED initiation of BUP (including documentation, orders, prescribing, and referral). The primary outcome was the rate of ED‐initiated BUP. Secondary outcomes were launch of the intervention, prescription for naloxone at ED discharge, and referral for ongoing addiction treatment. Results Of the 141,041 unique patients presenting to the ED over the preimplementation and implementation phases (i.e., the phases used in primary analysis), 906 (574 preimplementation and 332 implementation) met OUD phenotype and inclusion criteria. The rate of BUP initiation increased from 3.5% (20/574) in the preimplementation phase to 6.6% (22/332) in the implementation phase (p = 0.03). After the temporal trend of the number of physician's with X‐waiver training and other covariates were adjusted for, the relative risk of BUP initiation rate was 2.73 (95% confidence interval [CI] = 0.62 to 12.0, p = 0.18). Similarly, the number of unique attendings who initiated BUP increased modestly 7/53 (13.0%) to 13/57 (22.8%, p = 0.10) after offering just‐in‐time training during the implementation period. The rate of naloxone prescribed at discharge also increased (6.5% preimplementation and 11.5% implementation; p

Objective To describe and benchmark physician-perceived electronic health record (EHR) usability as defined by a standardized metric of technology usability and evaluate the association with professional burnout among physicians. Participants and Methods This cross-sectional survey of US physicians from all specialty disciplines was conducted between October 12, 2017, and March 15, 2018, using the American Medical Association Physician Masterfile. Among the 30,456 invited physicians, 5197 (17.1%) completed surveys. A random 25% (n=1250) of respondents in the primary survey received a subsurvey evaluating EHR usability, and 870 (69.6%) completed it. EHR usability was assessed using the System Usability Scale (SUS; range 0-100). SUS scores were normalized to percentile rankings across more than 1300 previous studies from other industries. Burnout was measured using the Maslach Burnout Inventory. Results Mean ± SD SUS score was 45.9±21.9. A score of 45.9 is in the bottom 9% of scores across previous studies and categorized in the "not acceptable" range or with a grade of F. On multivariate analysis adjusting for age, sex, medical specialty, practice setting, hours worked, and number of nights on call weekly, physician-rated EHR usability was independently associated with the odds of burnout with each 1 point more favorable SUS score associated with a 3% lower odds of burnout (odds ratio, 0.97; 95% CI, 0.97-0.98; P Conclusion The usability of current EHR systems received a grade of F by physician users when evaluated using a standardized metric of technology usability. A strong dose-response relationship between EHR usability and the odds of burnout was observed.

This Viewpoint discusses the need for public funding for research that supports health workforce well-being and addresses occupational burnout among health care practitioners.

This cross-sectional study compares patient electronic health record (EHR) inbox message volume in an ambulatory practice network in New England during the COVID-19 pandemic with prepandemic levels.

Key Points Question Can vendor-derived electronic health record (EHR) use data platforms be used to understand and explain physician turnover? Findings In this cohort study of 314 physicians in a large ambulatory care network, physician productivity and EHR use metrics were associated with physician departure. Counterintuitively, less time spent on the EHR (in particular inbox management) was associated with physician departure. Meaning These findings suggest that prospectively tracking these metrics along with standardizing metrics across vendor products could identify physicians at high risk of departure who would benefit from early, team-based, targeted interventions., This cohort study evaluates the association of physician productivity and electronic health record (EHR) use patterns with physician turnover., Importance Physician turnover takes a heavy toll on patients, physicians, and health care organizations. Survey research has established associations of electronic health record (EHR) use with professional burnout and reduction in professional effort, but these findings are subject to response fatigue and bias. Objective To evaluate the association of physician productivity and EHR use patterns, as determined by vendor-derived EHR use data platforms, with physician turnover. Design, Setting, and Participants This retrospective cohort study was conducted among nonteaching ambulatory physicians at a large ambulatory practice network based in New England. Data were collected from March 2018 to February 2020. Main Outcomes and Measures Physician departure from the practice network; 4 time-based core measures of EHR use, normalized to 8 hours of scheduled clinical time; teamwork, percentage of a physician’s orders that are placed by other members of the care team; and productivity measures of patient volume, intensity, and demand. Results Among 335 physicians assessed for eligibility, 314 unique physicians (89.2%) were included in the analysis (123 [39%] women; 100 [32%] aged 45-54 years), with 5663 physician-months of data. The turnover rate was 5.1%/year (32 of 314 physicians). Physicians completed a mean 2.6 appointments/hour (95% CI, 2.5-2.6 appointments/hour) and 206 appointments/month (95% CI, 197-215 appointments/month) with 5.5 hours (95% CI, 5.3-5.8 hours) of EHR time for every 8 hours of scheduled patient time. After controlling for gender, medical specialty, and time, the following variables were associated with turnover: inbox time (odds ratio [OR], 0.70; 95% CI, 0.61-0.82; P

Posterior strokes are frequently misdiagnosed as they present with non-specific complaints such as dizziness/vertigo. Emergency department (ED) practice often relies on CT/CTA to "exclude" infarct in such patients, providing false reassurance due to lower sensitivity of CT (42%) for stroke in the posterior circulation. We describe a pilot at our institution using a specialized MRI protocol with 95% sensitivity for posterior stroke, which may be used in place of CT/CTA or conventional MRI for stroke evaluation. Further development of this approach may help reduce the high rate of missed posterior stroke in patients presenting with dizziness.

Computerized clinical decision support (CDS) faces challenges to interoperability and scalability. Centralized, web-based solutions offer a mechanism to share the cost of CDS development, maintenance, and implementation across practices. Data standards have emerged to facilitate interoperability and rapid integration of such third-party CDS. This case report describes the challenges to implementation and scalability of an integrated, web-based CDS intervention for EMergency department-initiated BuprenorphinE for opioid use Disorder which will soon be evaluated in a trial across 20 sites in five healthcare systems. Due to limitations of current standards, security concerns, and the need for resource-intensive local customization, barriers persist related to centralized CDS at this scale. These challenges demonstrate the need and importance for future standards to support two-way messaging (read and write) between electronic health records and web applications, thus allowing for more robust sharing across health systems and decreasing redundant, resource-intensive CDS development at individual sites.

Objectives To analyze current practices in shared decision-making (SDM) in primary care and perform a needs assessment for the role of information technology (IT) interventions. Materials and Methods A mixed-methods study was conducted in three phases: (1) ethnographic observation of clinical encounters, (2) patient interviews, and (3) physician interviews. SDM was measured using the validated OPTION scale. Semistructured interviews followed an interview guide (developed by our multidisciplinary team) informed by the Traditional Decision Conflict Scale and Shared Decision Making Questionnaire. Field notes were independently coded and analyzed by two reviewers in Dedoose. Results Twenty-four patient encounters were observed in 3 diverse practices with an average OPTION score of 57.2 (0–100 scale; 95% confidence interval [CI], 51.8–62.6). Twenty-two patient and 8 physician interviews were conducted until thematic saturation was achieved. Cohen’s kappa, measuring coder agreement, was 0.42. Patient domains were: establishing trust, influence of others, flexibility, frustrations, values, and preferences. Physician domains included frustrations, technology (concerns, existing use, and desires), and decision making (current methods used, challenges, and patients’ understanding). Discussion Given low SDM observed, multiple opportunities for technology to enhance SDM exist based on specific OPTION items that received lower scores, including: (1) checking the patient’s preferred information format, (2) asking the patient's preferred level of involvement in decision making, and (3) providing an opportunity for deferring a decision. Based on data from interviews, patients and physicians value information exchange and are open to technologies that enhance communication of care options. Conclusion Future primary care IT platforms should prioritize the 3 quantitative gaps identified to improve physician–patient communication and relationships. Additionally, SDM tools should seek to standardize common workflow steps across decisions and focus on barriers to increasing adoption of effective SDM tools into routine primary care.

Background In order to streamline the emergency department (ED) referral process in a multi-network automated opioid treatment referral program, we performed a needs assessment of community providers for Medication for Opioid Use Disorder (MOUD) in the EMergency department-initiated BuprenorphinE for opioid use Disorder (EMBED) trial network. Methods A needs assessment was conducted in two phases: (1) key stakeholder meetings and (2) a survey of community sites offering MOUD. Stakeholder meetings were conducted with five key stakeholder groups: 1) ED clinicians and staff, 2) community sites offering MOUD, 3) the investigative team, 4) health system IT staff, and 5) medical ethics experts. Meetings continued until each stakeholder group stated that their priorities and needs were understood. Major categories of needs were extracted pragmatically based on recurrence across stakeholder groups. Informed by needs expressed by IT and MOUD site stakeholders, nineteen MOUD sites were surveyed to better characterize information needs of community sites offering MOUD when receiving an ED referral. Results Three major categories of needs for referral system were identified: 1) The system to be automated, flexible and allow multiple channels of referral, 2) Referral metrics are retrievable in a HIPAA compliant manner, 3) Patients are scheduled into community sites offering MOUD as urgently as possible. Of the MOUD sites surveyed, 68.4% (13/19) responded. Based on the responses, specific patient identifiers were required for most MOUD site referrals, and encrypted emails and EHR were the preferred methods of communication for the handoff. 53.8% (7/13) of the sites were able to accept patients within 3 days with only 1 site requiring >7 days. Conclusion These findings can inform IT solutions to address the discordant priorities of the ED (rapid and flexible referral process) and the community sites offering (referrals minimize variability and overbooking). To prevent drop-out in the referral cascade, our findings emphasize the need for increased availability and accessibility to MOUD on demand and protected communication channels between EDs and community providers of MOUD.

Despite considerable progress in tackling cardiovascular disease over the past 50 years, many gaps in the quality of care for cardiovascular disease remain. Multiple missed opportunities have been identified at every step in the prevention and treatment of cardiovascular disease, such as failure to make risk factor modifications, failure to diagnose cardiovascular disease, and failure to use proper evidence based treatments. With the digital transformation of medicine and advances in health information technology, clinical decision support (CDS) tools offer promise to enhance the efficiency and effectiveness of delivery of cardiovascular care. However, to date, the promise of CDS delivering scalable and sustained value for patient care in clinical practice has not been realized. This article reviews the evidence on key emerging questions around the development, implementation, and regulation of CDS with a focus on cardiovascular disease. It first reviews evidence on the effectiveness of CDS on healthcare process and clinical outcomes related to cardiovascular disease and design features associated with CDS effectiveness. It then reviews the barriers encountered during implementation of CDS in cardiovascular care, with a focus on unintended consequences and strategies to promote successful implementation. Finally, it reviews the legal and regulatory environment of CDS with specific examples for cardiovascular disease.

Background Electronic health record (EHR) usability and physician task load both contribute to physician professional burnout. The association between perceived EHR usability and workload has not previously been studied at a national level. Better understanding these interactions could give further information as to the drivers of extraneous task load. Objective This study aimed to determine the relationship between physician-perceived EHR usability and workload by specialty and evaluate for associations with professional burnout. Methods A secondary analysis of a cross-sectional survey of US physicians from all specialties was conducted from October 2017 to March 2018. Among the 1250 physicians invited to respond to the subsurvey analyzed here, 848 (67.8%) completed it. EHR usability was assessed with the System Usability Scale (SUS; range: 0-100). Provider task load (PTL) was assessed using the mental demand, physical demand, temporal demand, and effort required subscales of the National Aeronautics and Space Administration Task Load Index (range: 0-400). Burnout was measured using the Maslach Burnout Inventory. Results The mean scores were 46.1 (SD 22.1) for SUS and 262.5 (SD 71.7) for PTL. On multivariable analysis adjusting for age, gender, relationship status, medical specialty, practice setting, hours worked per week, and number of nights on call per week, physician-rated EHR usability was associated with PTL, with each 1-point increase in SUS score (indicating more favorable) associated with a 0.57-point decrease in PTL score (P Conclusions A strong association was observed between EHR usability and workload among US physicians, with more favorable usability associated with less workload. Both outcomes were associated with the odds of burnout, with task load acting as a mediator between EHR usability and burnout. Improving EHR usability while decreasing task load has the potential to allow practicing physicians more working memory for medical decision making and patient communication.

Despite basic federal requirements promoting a user-centered design approach to electronic health record (EHR) development and usability testing there have been usability and safety risks with EHR technology. Four EHR vendors were asked to provide written descriptions of their usability practices, and we reviewed these descriptions to identify areas where there has been advancement and areas for improvement. All 4 vendors described user-centered design processes and usability testing methods that demonstrate advancement from previous studies of vendor practices. Importantly, vendors are also beginning to address aspects of EHR implementation that play a critical role in shaping EHR usability. There are important areas for improvement in vendor practices including a greater focus on safety and on measurement and benchmarking. Vendors sharing their current usability practices demonstrates a step toward greater transparency which has typically been lacking.

This cross-sectional study examines trends in emergency department visits and visits that led to hospitalizations during a 4-month period leading up to and during the COVID-19 outbreak in the US., Key Points Question How did emergency department visits and hospitalizations change as the coronavirus disease 2019 (COVID-19) pandemic intensified in the US? Findings In this cross-sectional study of 24 emergency departments in 5 health care systems in Colorado, Connecticut, Massachusetts, New York, and North Carolina, decreases in emergency department visits ranged from 41.5% in Colorado to 63.5% in New York, with the most rapid rates of decrease in visits occurring in early March 2020. Rates of hospital admissions from the ED were stable until new COVID-19 case rates began to increase locally, at which point relative increases in hospital admission rates ranged from 22.0% to 149.0%. Meaning The findings suggest that clinicians and public health officials should emphasize to patients the importance of continuing to visit the emergency department for serious symptoms, illnesses, and injuries that cannot be managed in other clinical settings., Importance As coronavirus disease 2019 (COVID-19) spread throughout the US in the early months of 2020, acute care delivery changed to accommodate an influx of patients with a highly contagious infection about which little was known. Objective To examine trends in emergency department (ED) visits and visits that led to hospitalizations covering a 4-month period leading up to and during the COVID-19 outbreak in the US. Design, Setting, and Participants This retrospective, observational, cross-sectional study of 24 EDs in 5 large health care systems in Colorado (n = 4), Connecticut (n = 5), Massachusetts (n = 5), New York (n = 5), and North Carolina (n = 5) examined daily ED visit and hospital admission rates from January 1 to April 30, 2020, in relation to national and the 5 states’ COVID-19 case counts. Exposures Time (day) as a continuous variable. Main Outcomes and Measures Daily counts of ED visits, hospital admissions, and COVID-19 cases. Results A total of 24 EDs were studied. The annual ED volume before the COVID-19 pandemic ranged from 13 000 to 115 000 visits per year; the decrease in ED visits ranged from 41.5% in Colorado to 63.5% in New York. The weeks with the most rapid rates of decrease in visits were in March 2020, which corresponded with national public health messaging about COVID-19. Hospital admission rates from the ED were stable until new COVID-19 case rates began to increase locally; the largest relative increase in admission rates was 149.0% in New York, followed by 51.7% in Massachusetts, 36.2% in Connecticut, 29.4% in Colorado, and 22.0% in North Carolina. Conclusions and Relevance From January through April 2020, as the COVID-19 pandemic intensified in the US, temporal associations were observed with a decrease in ED visits and an increase in hospital admission rates in 5 health care systems in 5 states. These findings suggest that practitioners and public health officials should emphasize the importance of visiting the ED during the COVID-19 pandemic for serious symptoms, illnesses, and injuries that cannot be managed in other settings.

Decision aids are patient-focused tools that have the potential to reduce the overuse of head computed tomography (CT) scans. The objective of this study was to create a consensus among Canadian mild traumatic brain injury and emergency medicine experts on modifications required to adapt two American decision aids about head CT use for adult and paediatric mild traumatic brain injury to the Canadian context. We invited 21 Canadian stakeholders and the two authors of the American decision aids to a Nominal Group Technique consensus meeting to generate suggestions for adapting the decision aids. This method encourages idea generation and sharing between team members. Each idea was discussed and then prioritised using a voting system. We collected data using videotaping, writing material and online collaborative writing tools. The modifications proposed were analysed using a qualitative thematic content analysis. Twenty-one participants took part in the meeting, including researchers and clinician researchers (n = 9; 43%), patient partners (n = 3; 14%) and decision makers (n = 2; 10%). A total of 84 ideas were generated. Participants highlighted the need to clarify the purpose of the decision aids, the nature of the problem being addressed and the target population. The tools require sociocultural adaptations, better identification of their target population, better description of head CT utility, advantages and related risks, modification of the visual and written representation of the risk of brain injury and head CT use, and locally adapted, patient follow-up plans. This study based on a Nominal Group Technique identified several adaptations for two American decision aids about head CT use for mild traumatic brain injury to support their use in Canada’s different healthcare, social, cultural and legal context. These adaptations concerned the target users of the decision aids, the information presented, and how the benefits and risks were communicated in the decision aids. Future steps include prototyping the two adapted decision aids, conducting formative evaluations with actual emergency department patients and clinicians, and measuring the impact of the adapted tools on CT scan use. A mild traumatic brain injury (also called concussion) can happen when the brain moves around in the skull after an impact to the head. A concussion is not a brain bleed and you cannot see a concussion. Concussions do not show up on a computed tomography (CT) scan. Brain bleeds do. Computed tomography scans are specialised X-ray machines that can detect serious brain injuries. Unfortunately, CT scan use also exposes patients to radiation and a future increased risk of cancer. Shared decision making involves health professionals and patients making decisions together based on the best available evidence, health professionals’ experience, and patients’ values and preferences. Shared decision making improves appropriate diagnostic test use. Two decision aids created in the USA are available to facilitate shared decision making regarding the use of head CT scans for patients with concussion. These decision aids are not fully adapted for use in Canada because the healthcare, social and legal context is different. Our study brought together patients and experts in the field of concussion and shared decision making to analyse these decision aids and propose adaptations that would increase their acceptance in Canadian emergency departments. We used a technique called the Nominal Group Technique to create a consensus about the most important changes to make to both original decision aids. The main adaptations needed for the Canadian context concerned avoiding information about cost and removing any information that does not change clinical management. This project will help us adapt two decision aids for clinical use in Canada and support appropriate CT scan use for patients with concussion.

BACKGROUND Electronic health record (EHR) usability and physician task load both contribute to physician professional burnout. The association between perceived EHR usability and workload has not previously been studied at a national level. Better understanding these interactions could give further information as to the drivers of extraneous task load. OBJECTIVE This study aimed to determine the relationship between physician-perceived EHR usability and workload by specialty and evaluate for associations with professional burnout. METHODS A secondary analysis of a cross-sectional survey of US physicians from all specialties was conducted from October 2017 to March 2018. Among the 1250 physicians invited to respond to the subsurvey analyzed here, 848 (67.8%) completed it. EHR usability was assessed with the System Usability Scale (SUS; range: 0-100). Provider task load (PTL) was assessed using the mental demand, physical demand, temporal demand, and effort required subscales of the National Aeronautics and Space Administration Task Load Index (range: 0-400). Burnout was measured using the Maslach Burnout Inventory. RESULTS The mean scores were 46.1 (SD 22.1) for SUS and 262.5 (SD 71.7) for PTL. On multivariable analysis adjusting for age, gender, relationship status, medical specialty, practice setting, hours worked per week, and number of nights on call per week, physician-rated EHR usability was associated with PTL, with each 1-point increase in SUS score (indicating more favorable) associated with a 0.57-point decrease in PTL score (P CONCLUSIONS A strong association was observed between EHR usability and workload among US physicians, with more favorable usability associated with less workload. Both outcomes were associated with the odds of burnout, with task load acting as a mediator between EHR usability and burnout. Improving EHR usability while decreasing task load has the potential to allow practicing physicians more working memory for medical decision making and patient communication.

This cross-sectional survey assesses the association of perceived electronic health record usability with patient interaction and work-life integration among US physicians.

Until we have a meaningful alternative, lockdown is the only thing we can do to prevent further catastrophic spread of the virus, says Edward R Melnick. But John PA Ioannidis argues that any benefits of lockdown depend on its effectiveness and the covid-19 burden—and that the harms are multifarious

The final case fatality rate (CFR) from SARS-CoV-2, the virus that causes covid-19, will likely be lower than those initially reported.1 Previous reviews of H1N1 and SARS show the systematic inflation of early mortality estimates.23 Early estimates of H1N1’s mortality were susceptible to uncertainty about asymptomatic and subclinical infections, heterogeneity in approaches to diagnostic testing, and biases in confounding, selection, detection, reporting, …