physicians and advanced practice clinicians in the US spent approximately 50% more time on the EHR, twice the time on order entry, and almost 3 times on in-basket work; managed triple the number of messages; and used more documentation templates and copy-paste than their non-US colleagues.2 Perhaps most striking, only the farthest outliers for time on EHR in the non-US sample, at the 99th percentile, spent the same amount of time as a US clinician at the median.2

This new transparency will achieve 3 important goals. First will be a much-improved, if not ideal, representation of the EHR’s burden on providers. Second, the vendors will be seen as eager to participate in the solution to EHR-related burnout and not just the problem. Third, this will open up the possibility of cross-platform benchmarks and targets for which all health care organizations can aim.

Ideal provider efficiency metrics might also measure efficiency of common work flows (eg, ordering an antibiotic) and isolate time spent on purely administrative tasks.

Another way 1 vendor normalizes EHR data is by adjusting the time spent per patient based on the provider’s EHR adoption. For example, if a resident writes a note and forwards it to an attending physician, the attending will likely spend considerably less time reviewing and cosigning the note than the resident did creating it. In an effort to compare the resident’s efficiency to the attending’s, each provider is assigned an adoption percentage based on the number of notes they personally authored. Based on the percentage of notes authored, a multiplier then estimates the time spent per patient if the provider authored all of their notes.

everything a user does, such as look at a report or enter data into a flowsheet, is assigned to a “task.” The algorithms then take each task and assign them to larger categories (eg, Orders or Clinical Review). However, because many of these tasks are vaguely named, it is very difficult to validate that they have been assigned to the correct category.

In order to develop usable metrics of time spent using the EHR, vendors have developed algorithms to present the data in a meaningful way. This involves decisions on how to categorize tasks, assign time to a given task, when to stop the timer for a task, and how to normalize data for comparison between users.

Initial attempts to validate and interpret this data have proven difficult for a number of reasons, most of which involve the vendors’ proprietary algorithms which manipulate the raw data.

Measuring the EHR burden on providers is hard. Quantitative models such as time–motion analysis can be effective but are time-consuming, costly, and may be limited by bias and the inability to account well for multitasking. Qualitative models can measure perceived time in the EHR, but rely on surveys given to already-burnt out providers. A more accurate and convenient model would be to utilize data from EHR vendors’ access logs to compare the documentation burden between providers.

Because the EHR can track every user keystroke, click, and mouse mile, this data can be used to compare EHR efficiency of clinicians and target low efficiency users who might benefit from additional training or clinical decision support tools. EHRs, however, are complex and implemented differently in each institution. There are no industry-standard metrics to analyze and report provider time spent in the EHR, making it impossible to compare across vendor EHRs. Furthermore, in our experience, vendor provided dashboards utilize proprietary algorithms that cannot be validated by the institutions using them.

Most providers are frustrated with the amount of time they spend in the electronic health record (EHR), especially time spent after hours and on the weekends.2 Increased burnout among physicians has been linked to the rise of the EHR and the increasing administrative burden placed on providers.3

Options include face validity via end-user testing vs validation against an external standard, such as direct observation time-motion analysis. Manual time-motion observations are labor-intensive but currently represent the gold standard for validation.18,19,36,37 It is our hope that these core measures will be validated across different types of institutions, clinical specialties, and EHR vendors.

Not every aspect of clinical work is performed via the EHR. The time associated with phone calls, messages, family meetings, paperwork, verbal communication with colleagues, and even direct face time with patients are components of a physician’s workday that are not directly captured by EHR time stamp data.

accurate assessment of WOW requires integration of the physician’s clinic schedule with the EHR log data.

Unintended negative consequences

Generalization to inpatient and procedural settings

Reporting period

EHR measure normalization

EHR usemeasure validation

Work outside of the EHR

The mapping of EHR actions (ie, time on a type of EHR screen) to work (ie, the total time required to complete a task).

The exclusion of “shoulder time”(ie, prep time)immediately before or after clinic.

EHR use measures can likewise illuminate the impact of regulatory and compliance decisions upon clinician work.

Definition of work outside of work.

GENERALIZABILITY

NORMALIZATION

VALIDITY

IMPLEMENTATION

Definition ofEHR usetime.

The interval without user activity that triggers a time-out from active use will impact the resulting EHR use times. Currently, this interval may vary from 5 seconds, to 90 seconds, to 30 minutes. Determining time-out intervals that best represent user activity is challenging and may vary by setting or task, and one could even argue that they should not be included at all in some calculations.

CHALLENGES AND LIMITATIONS

Table 2.Sample use cases for EHR log data

EHR use measures can be used to assess the impact of new staffing models, such as advanced team-based care with in-room support.34 For example, a physician practicing with a strong, skilled team may be able to spend the majority of her time providing undivided attention to her patients, while her empowered staff enters orders, completes the billing invoice, drafts the preliminary visit note, and manages the team’s inbox. Another physician, practicing in a more “the doctor does it all” environment, performs the majority of data entry and inbox management on her own.

Total time on EHR (during and outside of clinic sessions) per 8 h of patient scheduled time. 

Table 1.Proposed core EHR use measures

total EHR time (EHR-Time); work outside of work (WOW), often referred to as “pajama time”; time on documentation (Note-Time); time on prescriptions (Script-Time); inbox time (IB-Time); teamwork for orders (TWORD); and an aspirational measure for the amount of undivided attention patients receive from their physicians during an encounter, undivided attention (ATTN).

In addition, while time alone does not capture all dimensions of work (eg, the content of work and appropriateness of tasks to different levels of training or certification), time-based metrics are relevant, interpretable, and form a foundation from which to expand upon in the future.

We worked with multiple stakeholders to select measures that are feasible and relevant to clinical and operational decision making. We identified time as an important unit of measure, as it is a commodity in limited supply for physicians and other health professionals.

A direct observation time-motion study in 2016 found physicians in the ambulatory setting spend half of the workday on the EHR, requiring nearly 2 hours of EHR and desk work for every 1 hour of direct clinical face time with patients.

Risk-enhancing factors include family history of premature ASCVD; persistently elevated LDL-C levels ≥160 mg/dL (≥4.1 mmol/L); metabolic syndrome; chronic kidney disease; history of preeclampsia or premature menopause (age <40 years); chronic inflammatory disorders (e.g., rheumatoid arthritis, psoriasis, or chronic HIV); high-risk ethnic groups (e.g., South Asian); persistent elevations of triglycerides ≥175 mg/dL (≥1.97 mmol/L); and, if measured in selected individuals, apolipoprotein B ≥130 mg/dL, high-sensitivity C-reactive protein ≥2.0 mg/L, ankle-brachial index (ABI) <0.9 and lipoprotein (a) ≥50 mg/dL or 125 nmol/L, especially at higher values of lipoprotein (a). Risk-enhancing factors may favor statin therapy in patients at 10-year risk of 5% to 7.5% (borderline risk).

The authors found that although the vaccines did offer some protection against infection and onward transmission, Delta dampened that effect. A person who was fully vaccinated and then had a ‘breakthrough’ Delta infection was almost twice as likely to pass on the virus as someone who was infected with Alpha. And that was on top of the higher risk of having a breakthrough infection caused by Delta than one caused by Alpha.Unfortunately, the vaccine’s beneficial effect on Delta transmission waned to almost negligible levels over time. In people infected 2 weeks after receiving the vaccine developed by the University of Oxford and AstraZeneca, both in the UK, the chance that an unvaccinated close contact would test positive was 57%, but 3 months later, that chance rose to 67%. The latter figure is on par with the likelihood that an unvaccinated person will spread the virus.A reduction was also observed in people vaccinated with the jab made by US company Pfizer and German firm BioNTech. The risk of spreading the Delta infection soon after vaccination with that jab was 42%, but increased to 58% with time.

An enrichment refers to a user interaction, behavior, or strategy that aims to maximize the utility of the information foraging. It can happen either between patches or within patches. Think of enrichments as an extra tool that users may use in order to forage more efficiently. The tool may be something that they already have in their pocket (such as a learned behavior) or could be built on the spot and tailored to the specific patch (in which case the user must spend time creating it). Behavior enrichments are the tools that users already have acquired and that help them extract information efficiently. These behaviors are adaptations that evolved over time and that proved to be successful in many situations in the past.

Looking up information on the web or on a webpage usually involves two types of user actions: Between-patch activities: Gathering information sources (i.e., patches) Within-patch activities: Inspecting each patch to extract information from it

What makes the scent of a webpage? When a person lands on that very page, the scent is given by the title, images, and the information that is easily visible above the fold.

Similarly, as a user searches for information on the web, she judges the webpages she encounters based on how well suited they are for her goal. Each source of information thus emits a “scent” — a signal that tells the forager how likely it is that it contains what she needs.

Specifically, people have no way of knowing in advance (1) how much information a patch contains; (2) how much time it will take them to extract that information.

because they attempt to maximize the rate of gain and get as much relevant information in as little time as possible.

when users have a certain information goal, they assess the information that they can extract from any candidate source of information relative to the cost involved in extracting that information and choose one or several candidate sources so that they maximize the ratio: Rate of gain = Information value / Cost associated with obtaining that information

If an AI model yields accurate predictions that help clinicians better treat their patients, then it may be useful even without a detailed explanation of how or why it works. It’s like the weather report, Shah says. “Do you, as a user, care how the weather is predicted, and what the causal explanation is, as long as you know a day ahead if it is going to rain and the forecast is correct?”

Using magnetic bead-based absorption assays, we found that SARS-CoV-2 infections elicited a large proportion of original antigenic sin-like antibodies that bound efficiently to common seasonal human coronaviruses but poorly to SARS-CoV-2. In converse, vaccination only modestly boosted antibodies reactive to common seasonal human coronaviruses and these antibodies bound efficiently to SARS-CoV-2. Our data indicate that SARS-CoV-2 mRNA vaccinations elicit fundamentally different antibody responses compared to SARS-CoV-2 infections.

Ming Tai-Seale (mtaiseale@ucsd.edu) is a professor in the Department of Family Medicine and Public Health, University of California San Diego; director of outcomes analysis and scholarship at UC San Diego Health; and director of research at UCSD Health Sciences International, in La Jolla.Ellis C. Dillon is an assistant scientist in the Research Institute, Palo Alto Medical Foundation, in California.Yan Yang is a research economist in the Research Institute, Palo Alto Medical Foundation.Robert Nordgren is CEO of the Palo Alto Foundation Medical Group.Ruth L. Steinberg is chair of the Physician Wellbeing Committee, Palo Alto Medical Foundation.Teresa Nauenberg is a physician in the internal medicine and concierge medicine departments at the Palo Alto Medical Foundation.Tim C. Lee is a physician in the pediatrics department, Palo Alto Medical Foundation.Amy Meehan is a research associate in the Research Institute, Palo Alto Medical Foundation.Jinnan Li is a quantitative analyst in the Research Institute, Palo Alto Medical Foundation.Albert Solomon Chan is chief of digital patient experience and an investigator at Sutter Health, in Palo Alto, and an adjunct professor at the Stanford Center for Biomedical Informatics Research, Stanford School of Medicine, in California.Dominick L. Frosch is director of the Research Institute, Palo Alto Medical Foundation.

It is necessary to recognize the different manifestations of burnout symptoms across physician genders. Female physicians have been documented to first suffer from emotional exhaustion, whereas male physicians first experience depersonalization.22 Female physicians are also more likely to experience burnout resulting from work-home conflict, whereas workload was a key predictor of burnout for male physicians.

Health care organizations could allow messages to reach physicians’ in-baskets only during work hours, conveying the message that physicians are so highly valued that the organization wants to protect their private time.

Keeping up with system-generated messages can be overwhelming, particularly for internists and family physicians. Some of those messages are generated by population health management algorithms that remind physicians to perform work that might have otherwise been overlooked. These were in addition to messages coming directly from patients and from other physicians or care team members. Therefore, both perceived and realized loss of autonomy over their work schedules could leave physicians feeling defeated,20 even though some of these system-generated messages have been shown to improve certain processes of care for patients with chronic illnesses.19

System-generated messages stood out as the largest source of messages for all specialties, especially for internal medicine (209) and family medicine (204), followed by pediatricians (102)

Almost half of all weekly in-basket messages came from EHR algorithms, and they were significantly associated with physicians having burnout symptoms and intending to reduce their clinical work hours.

Balancing Measures (looking at a system from different directions/dimensions) Are changes designed to improve one part of the system causing new problems in other parts of the system?

Process MeasuresAre the parts/steps in the system performing as planned? Are we on track in our efforts to improve the system?

Three Types of Measures Use a balanced set of measures for all improvement efforts: outcomes measures, process measures, and balancing measures.

Outcome Measures How does the system impact the values of patients, their health and wellbeing? What are impacts on other stakeholders such as payers, employees, or the community?

burnout may be defined by two domains, disengagement and exhaustion, or by three domains, the third being personal achievement.

affecting about 50% of physicians in the United States, in all stages of their medical career, in all practice settings, and in all specialties.1–3 Burned-out physicians have a twofold higher risk of leaving the institution, with turnover replacement and reduced productivity costing $4.6 billion annually in the United States.4 In addition to the financial impact, burned-out physicians have higher rates of drug and alcohol use, depression, and suicidal ideation in comparison to physicians without burnout.5–7

While I agree with many of the concepts & justifications given that drive an organization to form teams, however, I disagree with the notion that successfull teams can be "dynamic", or the notion of "teaming on the fly" as viable concepts. I think these ideas lack the psychological foundation of what makes a team and develops trust between the "players". Fundamental to the formation of a team is "identity". Whether it is the "Sharks" vs. the "Jets" in Westside Story or any other. There is the psychological need to belong to something. Then there is the aspect of trust. Each player needs to know their role and trust that the other will perform theirs. Trust is built on familiarity and a developed respect for each player to do their part and I might add self-sacrifice to help or pick-up the slack when your teammate falters. Failure to recognize these facts can be traced to many things. I would offer the comparrisson to modern medical teams that operate this way, however, these are the recreational equivalent of a pick-up game of basketball at the park. The participants know medicine and how to do their particular function, just as the players know how to dribble & shoot, but because they are not together all the time they don't know their tendencies. There is no trust factor that is devleoped. Their responsibility is only to their own objective, that is, do their job and hand it off to the next.

Teaming is the engine of organizational learning. By now, everyone knows that organizations need to learn how to thrive in a world of continuous change. But how organizations learn is not as well understood. As discussed later in this chapter, organizations are complex entities; many are globally distributed, most encompass multiple areas of expertise, and nearly all engage in a variety of activities. What does it mean for such a complex entity to "learn"? An organization cannot engage in a learning process in any meaningful sense—not in the way an individual can. Yet, when individuals learn, this does not always create change in the ways the organization delivers products and services to customers.

How do you create synergy when you lack the advantages offered by the frequent drilling and practice sessions of static performance teams like those in sports and music? The answer lies in teaming. Teaming is a verb. It is a dynamic activity, not a bounded, static entity. It is largely determined by the mindset and practices of teamwork, not by the design and structures of effective teams. Teaming is teamwork on the fly. It involves coordinating and collaborating without the benefit of stable team structures, because many operations like hospitals, power plants, and military installations require a level of staffing flexibility that makes stable team composition rare.

In the course of that work, anomalies necessarily arise — findings that differ from expectations. Kuhn had in mind episodes such as the accidental discoveries of X-rays in the late nineteenth century and nuclear fission in the early twentieth. Often, Kuhn argued, the anomalies are brushed aside or left as problems for future research. But once enough anomalies have accumulated, and all efforts to assimilate them to the paradigm have met with frustration, the field enters a state of crisis. Resolution comes only with a revolution, and the inauguration of a new paradigm that can address the anomalies.

To Kuhn, the concepts were incommensurable: no common measure could be found with which to relate them, because scientists, he argued, always interrogate nature through a given paradigm.

Perhaps the most radical thrust of Kuhn's analysis, then, was that science might not be progressing toward a truer representation of the world, but might simply be moving away from previous representations. Knowledge need not be cumulative: when paradigms change, whole sets of questions and answers get dropped as irrelevant, rather than incorporated into the new era of normal science. In the closing pages of his original edition, Kuhn adopted the metaphor of Darwinian natural selection: scientific knowledge surely changes over time, but does not necessarily march towards an ultimate goal.

More than most scholars of his era, Kuhn taught historians and philosophers to view science as practice rather than syllogism.

Without making assumptions or using causal inference techniques, prognostic models should not be used for decision making that affects the treatment choice [51]. When clinicians ask, “What will the outcome of this patient be?,” they are often actually interested in the causal question “What will the outcome be on this treatment versus on another?”

Predictive AnalysesUnlike inferential and causal analyses, predictive analyses do not seek structural knowledge about the world. Instead, they exploit correlations to predict outcomes or classify patient states at the individual level.

Negative control outcomes are a useful mechanism to assess susceptibility to such biases [45]. Briefly, the studies are rerun using an alternative outcome that is known to not be caused by the treatment or comparator. If the results show a significant effect, then it is likely that the results of the original study are also biased. For example, a prescription of metformin could never be causative of preprescription HbA1c levels. Therefore, if we are interested in metformin’s effect on postprescription HbA1c, we could use the preprescription value as a negative control.

There are several challenges in using EHR data. First, EHR data are retrospective and observational, so highly prone to confounding; second, there are a variety of causal inference methods to choose from; third, it is difficult to evaluate if confounding has been addressed well enough; and fourth, causal effects vary between patients.

Inferential and Causal AnalysesClinicians are often interested in the relationship between a treatment and an outcome. In an inferential analysis, it suffices to say that the outcome and treatment change together in a statistically significant way, but that does not imply that changing the treatment would change the outcome. To perform a causal analysis, we must attempt to reduce confounding while performing inference.

Descriptive and Exploratory AnalysesFor complex patient populations, it is helpful to describe the population to see if interpretable patterns emerge. Traditionally, this has been done by computing summary statistics of some clinically important features across predefined subgroups of the population.

Former Herman Miller CEO Max De Pree once said, “The first responsibility of a leader is to define reality. The last is to say thank you. In between the two, the leader must become a servant.”

managers who “express interest in and concern for team members’ success and personal well-being” outperform others in the quality and quantity of their work.

Intentionally build relationships. The brain network that oxytocin activates is evolutionarily old. This means that the trust and sociality that oxytocin enables are deeply embedded in our nature. Yet at work we often get the message that we should focus on completing tasks, not on making friends. Neuroscience experiments by my lab show that when people intentionally build social ties at work, their performance improves.

When companies trust employees to choose which projects they’ll work on, people focus their energies on what they care about most. As a result, organizations like the Morning Star Company—the largest producer of tomato products in the world—have highly productive colleagues who stay with the company year after year. At Morning Star (a company I’ve worked with), people don’t even have job titles; they self-organize into work groups. Gaming software company Valve gives employees desks on wheels and encourages them to join projects that seem “interesting” and “rewarding.” But they’re still held accountable. Clear expectations are set when employees join a new group, and 360-degree evaluations are done when projects wrap up, so that individual contributions can be measured.

vague or impossible goals cause people to give up before they even start. Leaders should check in frequently to assess progress and adjust goals that are too easy or out of reach.

Induce “challenge stress.” When a manager assigns a team a difficult but achievable job, the moderate stress of the task releases neurochemicals, including oxytocin and adrenocorticotropin, that intensify people’s focus and strengthen social connections.

I identified eight management behaviors that foster trust.

why trust varies across individuals and situations. For example, high stress is a potent oxytocin inhibitor. (Most people intuitively know this: When they are stressed out, they do not interact with others effectively.) We also discovered that oxytocin increases a person’s empathy, a useful trait for social creatures trying to work together.

Comparing participants who received a real dose with those who received a placebo, we found that giving people 24 IU of synthetic oxytocin more than doubled the amount of money they sent to a stranger. Using a variety of psychological tests, we showed that those receiving oxytocin remained cognitively intact. We also found that they did not take excessive risks in a gambling task, so the increase in trust was not due to neural disinhibition. Oxytocin appeared to do just one thing—reduce the fear of trusting a stranger.

We found that the more money people received (denoting greater trust on the part of senders), the more oxytocin their brains produced. And the amount of oxytocin recipients produced predicted how trustworthy—that is, how likely to share the money—they would be.

To measure oxytocin levels during the exchange, my colleagues and I developed a protocol to draw blood from people’s arms before and immediately after they made decisions to trust others (if they were senders) or to be trustworthy (if they were receivers).

I knew that in rodents a brain chemical called oxytocin had been shown to signal that another animal was safe to approach.

In my research I’ve found that building a culture of trust is what makes a meaningful difference. Employees in high-trust organizations are more productive, have more energy at work, collaborate better with their colleagues, and stay with their employers longer than people working at low-trust companies. They also suffer less chronic stress and are happier with their lives, and these factors fuel stronger performance.

The AI in Healthcare Specialization can serve as the foundation of anyone’s health AI education.

Jeremy Howard’s fast.ai course was my personal favorite and is the ideal resource for anyone with a strong technical background who knows even a little bit of coding

sidelines communication

Listen. Make eye contact. Touch. Stop typing.

results are often not available for several weeks, while treatment decisions may need to be made before the specific serologic profile is known.

dermatomyositis (DM) classically present with symmetric muscle weakness, elevated muscle enzymes, and characteristic cutaneous findings

One crucial difference, however, is the need for added emphasis on ventilation because the tiniest suspended particles can remain airborne for hours, and these constitute an important route of transmission.

Essentially, if you can inhale particles—regardless of their size or name—you are breathing in aerosols. Although this can happen at long range, it is more likely when close to someone, as the aerosols between two people are much more concentrated at short range

Our systematic review found that poor handover is associated with multiple potential hazards. No single tool arises as best to evaluate the handover process. There is little empirical evidence delineating what constitutes best handover practices.

there is a limited amount of good-quality research on handover. Failure to show effects may be that the included studies are of little quality and yield heterogeneous results.

principal teaching methods are role-playing and simulation, which are better received by learners than didactic sessions

Discussion

Only a few studies found positive effects of handover interventions on patient outcomes.

Lack of active listening, lack of attention or divided attention of the receiving healthcare professional(s), workload and lack of time were the leading causes of poor handover

Create specific moments to help the incoming party prepare for the handoff, thus shaping his or her mental models of the patients.

Without this question to the outgoing party, there may be an incomplete understanding about the patient. Sometimes, a question can even be an active formulation of an alternative hypothesis about the patient's fundamental or likely trajectory.

Encourage and teach the outgoing party to take the perspective of the one coming on [47].

This empirical evidence actually agrees with qualitative research that suggests that residents perceive standardized tools for handoff s as being possibly detrimental [46].

We did not evaluate the impact of the content overlap on sign-out qualit

code status (<1%)

No overlap: Written documentation content was not present at all in the verbal communication content (ie there was no match).

Clinical content framework

This encrypted, Microsoft Word-based sign-out document was maintained external to the institution’s Electronic Health Record (EHR) and was organized in a standardized problem-based format with the following information: patient identifying information [name, date of birth, medical record number (MRN), room number, allergies, code and contacts], history of presenting illness (HPI), active problems, medications, and tasks to-do. An example sign-out document is provided in the Supplementary Figure S1.

Resident sign-outs occurred at 5 pm daily, and involved the verbal exchange of information from the outgoing to the incoming resident.

Their comparative evaluation showed that the written documentation served as a cognitive aid for sign-out communication and reasoning.

no empirically validated content frameworks that can used to evaluate the overlap between written sign-out documentation and verbal communication.

In other words, only a few studies have evaluated both written documentation and verbal communication for comprehensively characterizing the nature of content and structure of resident sign-outs.

information discrepancies, declined rapidly over a 6-h period after sign-out, with the number of information discrepancies increasing over time.

verbal sign-out communication, and that of written and electronic sign-out documentation

The bundled intervention demonstrated increased patient handoff and health resource utilization compared with usual handoff practices.

handoff information following the widely adopted SIGNOUT? mnemonic (Sick or do not resuscitate, Identifying data, General hospital course, New events of the day, overall health status, Upcoming possibilities with plan, Tasks to complete, ?Questions)

The iHAND criteria showed a moderately significant correlation with requiring assessment overnight

type of patient to handoff, trainees were instructed to handoff all patients who had any of: (i) investigations pending, (H) currently located in a high acuity unit, (A) abnormal vital signs in the preceding 24 hours, (N) newly admitted in the last 24 hours, and (D) dying.

45-minute training and education session on the importance and evidence for patient handoff, standardization of type of patient and information to handoff as well designating a fixed time (17:30–18:00) and dedicated quiet location for face-to-face handoff

At large institutions with high volumes of inpatients, handoff on all patients is not feasible, thereby requiring daytime physicians to prioritize a smaller subset of patients to convey potential issues on.

Transfer of Professional Responsibility.

Figure 4.

A checklist of necessary information can help teach others new to the handoff about the process and serve as a monitoring tool in evaluating the content transferred.

“What are the main content pieces of a handoff in your discipline?”

communication of information (content) that can take place through different modalities, which can include a written or verbal component.

often include more information as the hospitalization progresses, but that this information may not be helpful.

Table 1. Information Abstracted From Written Sign‐out Entries

Lack of conflicting information

Rationale for decisions

Any reference to degree of illness

Any reference to baseline or current mental status

11 elements that should be present in a high‐quality written sign‐out and 2 (vague language and confusing/conflicting language) that should not be present (Table 1).

2 sites did not have EHR‐assisted sign‐out tools at the time of this study, and providers typed all information in Microsoft Excel or Word (Microsoft Corp., Redmond, WA)

Given that integration is the goal, many students of color who seek ‘safe’ race discussions in public rarely find them, having to settle for the reality that most pedagogical situations involving race are violent to them.

Our main criticism of safe space is that it is laced with a narcissism that designates safety for individuals in already dominant positions of power, which is not safe at all but perpetuates a systematic relation of violence.

critical race pedagogy is inherently risky, uncomfortable, and fundamentally unsafe (Lynn 1999Lynn, M. 1999. Toward a critical race pedagogy: A research note. Urban Education, 33(5): 606–26.  [Crossref], [Web of Science ®], [Google Scholar]), particularly for whites. This does not equate with creating a hostile situation but to acknowledges that pedagogies that tackle racial power will be most uncomfortable for those who benefit from that power.

“so what is it about this ethnicity that makes them that way?” And they [the lecturer] point to genetics. And I’m like, “Well, we’re 99.9% alike. So, is it genetics that’s making the change?” And then that’s when me and the lecturer are at a standstill. [Then the lecturer says] “It’s not genetics, but I don’t really know the reason. So, let’s move on.”

I raised my hand and answered the question. She [the instructor] shot in front of the whole class and said, “[I 3E], can we get someone else’s input. I don’t need your input. I need an educated answer; we don’t need your guess.”

I became very aware of how different I was from the general student body.

I think there is isolation because I feel excluded in conversations. I prefer to not be in that position, so I spend all my time by myself.

black people are better prepared than white people to cope with blatant prejudice but are particularly vulnerable to cognitive impairment resulting from exposure to ambiguous prejudice (a level of prejudice that white persons may not even register).

In some important professions, such as physics and engineering, Asian Americans are overrepresented and African Americans underrepresented. We presumably get better research because of this. This may or may not outweigh the inequity of unequal group representation. That is a social decision.

U.S. health care system currently suffers from a dearth of frontline clinical leaders precisely because our educational system does not consistently and explicitly prioritize leadership development.

Providers, educators, and administrators need to dispel the myth that clinical and managerial responsibilities are inherently at odds with one another.

how to manage relationships and negotiate with colleagues and patients

ACGME's Practice-based Learning and Improvement competency (which includes engaging in “constant self-evaluation”; participating in patient, family, student, and health care professional education; and leading quality improvement efforts) is addressed in leadership training through efforts to build self-understanding, the capacity for self-reflection, negotiation skills, and the abilities to learn from experience, create personal development goals, and manage interpersonal relationships.

First, leadership development must become an explicit goal of residency training.

Harvard Business School. MBA students explore their leadership motivations and capabilities through an iterative process that includes three critical parts: experience, reflection, and feedback.

CCL asserts that successful leadership development programs include three components: Assessments of trainees' leadership skills and development over time; content that Challenges participants to operate outside of their comfort zones—which is critical for skill development—and to take personal responsibility for their leadership development; and Support for learners through high-quality teaching, constructive feedback, and postcourse coaching (the “ACS Model”)

Moreover, many providers perceive an inherent tension between managing care and providing it. This wariness of managerial work is deeply rooted in the culture of medicine and medical education.

Most physicians value autonomy and often view practice interventions—including efforts to increase collaboration across providers—as a threat to their independence.

three different types of clinical leaders have been identified: institutional leaders (e.g., CEOs), service leaders (e.g., department chairs or research directors), and frontline leaders (e.g., those who work at the interface of patient care).

improving the leadership skills

we note that many of the lectures were also recorded so they would be available to students, both present and absent, for later viewing.

allowed participants to passively watch lecturers or their fellow students on the screen, as a viewer might watch a television.

We all hear it, but he has no idea.

seen at local and satellite sites from multiple angles and it is anxious making. In addition, I know I was being taped. Not to mention that there are people in the control room ensuring that technologically all goes okay. I felt like saying, “Does the camera add x number of pounds?” Everyone is watching and I felt super conscious.

placed a series of cameras throughout the classroom, a gooseneck microphone at each lecture podium, small dome-shaped microphones at student desks, and a collection of speakers in the ceiling.

Distributed medical education (DME)

architectural distortion, traction bronchiectasis, intra-thoracic lymph node enlargement, and pleural effusions