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SUMMARY & CONCLUSIONSThe spread of COVID-19 has transformed our world over, propelling individuals and organizations to adapt quickly. Often, changing directions mid-step as new information becomes available. This has subsequently evolved the concept of new knowledge learning to quantum levels.The nursing workforce is the largest profession within healthcare systems and is central to the response and prevention efforts of COVID-19. Registered Nurses (RN) are the front-line caregivers for the sickest of COVID-19 patients in the intensive care arena. Therefore, it is imperative nursing operations monitor, adapt, and function in times of constraint while exhibiting essential principles of resilience to survive under surge conditions. These principles are: Top-level Commitment, Just Culture, Learning Culture, Awareness, Preparedness, Flexibility, and Opacity. The focus of this paper is to present a case study with lessons learned on COVID-19 nursing operational initiatives within the context of the principles of resilience.The principals of resilience were demonstrated during the initial response to the pandemic through multiple operational initiatives. The Incident Command structure directed decisions and action items through an even sharper lens for driving outcomes. This was impacted by a sense of urgency in responding to social media influences, overt staff fear of the disease and potential impact to self and their families, and the evolution of incoming scientific information on disease management.Staff quickly adapted to the education while sustaining an ability to provide direct care to patients. There were 932 hospital admissions with 895 successful COVID-19 hospital discharges from March - May 2020. The remaining 114 admissions were resulting in-hospital COVID-19 related deaths. During the escalation of the COVID-19 crisis, 2845 ChristianaCare employees were tested for COVID. Five hundred and one tests came back positive for the disease. One hundred and fifty three positive tests were nursing staff that worked on the dedicated COVID-19 patient care units. Interestingly, the hypothesis in the beginning of the crisis was that the COVID patient care staff were at more risk for exposure and acquired infections. These statistics infer that the directed attention of RNs from COVID-19 units on education resulted in purposeful application too proper Personal Protective Equipment (PPE) and hand hygiene practices, along with a preparedness for working in the stressful environment. This coupled with purposeful leadership presence and responsiveness to staff feedback, resulted in better system resilience among COVID-19-unit staff versus non-COVID-19 unit staff. Opportunities have emerged to inform recovery plans in the future to include opportunities for providing acute care in the population health setting with supportive technology.

Background: Patients with cardiovascular disease (CVD) are especially vulnerable to respiratory infections caused by the coronavirus. The underlying effect of cardiovascular comorbidities on patients with COVID-19, however, remains to be sufficiently understood. Methods: Hospitalized COVID-19 patients from a state-wide large health care system with completed historical clinical conditions during March - June of 2020 were included in this study. The impact of CVD on the mortality, resources utility including the uses of intensive care unit (ICU) and ventilator, length of stay (LOS) and financial burden of COVID-19 inpatients were examined. Logistic analysis was applied to analyze the relationship between CVD and mortality, and non-parametric methods were used to evaluate the impact of CVD on resources utility. Random forest method was used to rank the importance of risk factors. Results: Among 811 hospitalized COVID-19 patients, 228 (28.11%) were placed in ICU, 105 (12.95%) spent on ventilators, and there were 94 deaths (11.59%). The mean LOS was 11.93 ± 11.26 (SD, standard deviation), mean time a patient in an ICU was 2.41 ± 5.49 days, and mean ventilator time was 1.29 ± 4.62 days. The mean charge of a patient was $55242 ± 71742) with inter-quarter range of $44124. Age, gender, and race were the top 3 factors of mortality and utilities. Patients who present with heart failure vs. those who do not, have increased mortality (21.47% vs 8.97%; odds ratio [OR], 2.00 (95% CI: 1.25-3.21; P=0.004), longer LOS (12.97 ±10.09 vs. 11.61±11.46), p=0.18), higher ICU usage ( 3.32 ± 6.04 vs. 2.14 ±5.26, p=0.02) and ICU requiring ventilator (1.86 ± 4.90 vs. 1.15 ± 4.56, p=0.09), and significant higher charge ($ 66175 ± 68773 vs $ 50736 ±64142, mean difference $15439± 65193 with 95% CI: $4537-26340, p=0.01). Similar results were shown for patients with coronary artery disease or arrhythmia. Patients with hypertension vs those who do not, have increased mortality (14.81% vs. 4.92%; OR=3.22 (95% CI: 1.76-5.90, p=0.01), but the impact was not significant after adjusted by age, race and gender. Conclusions: Among COVID-19 hospitalized patients with established cardiovascular disease, there was a worse survival and adverse utility outcomes in hospital resources and financial charges.

We identify the value and usage of a cognitive artifact used by hospital nurses. By analyzing the value and usage of workaround artifacts, unmet needs using intended systems can be uncovered. A descriptive study employed direct observations of registered nurses at two hospitals using a paper workaround (“brains”) and the Electronic Health Record. Field notes and photographs were taken; the format, size, layout, permanence, and content of the artifact were analyzed. Thirty-nine observations, spanning 156 hr, were conducted with 20 nurses across four clinical units. A total of 322 photographs of paper-based artifacts for 161 patients were collected. All participants used and updated “brains” during report, and throughout the shift, most were self-generated. These artifacts contained patient identifiers in a header with room number, last name, age, code status, and physician; clinical data were recorded in the body with historical chronic issues, detailed assessment information, and planned activities for the shift. Updates continuously made during the shift highlighted important information, updated values, and tracked the completion of activities. The primary functional uses of “brains” are to support nurses’ needs for clinical immediacy through personally generated snapshot overviews for clinical summaries and updates to the status of planned activities.

Human factors engineering is an underutilized approach in the design, evaluation, and implementation of health information technology. Heuristic evaluation of the usability of an interface is a ‘low-hanging fruit’ for identifying a set of relatively simple modifications to a software program that can make software easier to use. In this paper, we describe recommendations to improve the usability of a software package used to view digitized images of tissues by pathologists. Several recommendations were immediately implemented, and others are planned for future releases. The changes are anticipated to be more compatible with user expectations from interacting with similar elements in other packages, and thus easier to learn and use.

The overarching objective of this research is to reduce the burden of documentation in electronic health records by registered nurses in hospitals. Registered nurses have consistently reported that e-documentation is a concern with the introduction of electronic health records. As a result, many nurses use handwritten notes in order to avoid using electronic health records to access information about patients. At the top of these notes are patient identifiers. By identifying aspects of good and suboptimal headers, we can begin to form a model of how to effectively support identifying patients during assessments and care activities. The primary finding is that nurses use room number as the primary patient identifier in the hospital setting, not the patient’s last name. In addition, the last name, gender, and age are sufficiently important identifiers that they are frequently recorded at the top of handwritten notes. Clearly distinguishable field labels and values are helpful in quickly scanning the identifier for identifying information. A web based annotator was designed as a first step towards machine learning approaches to recognize handwritten or printed data on paper sheets in future research.

Attending physicians need to supervise resident physician sign-outs in order to ensure patient safety. In one survey study, 59% of resident physicians reported at least one case of harm to one of their patients due to communication issues during sign-outs in their last rotation. In prior research, we identified ‘best practices’ for sign-outs used by attending physicians. For the outgoing physician, communication strategies improve the informativeness, structure, and coverage of the information. For the incoming physician, communication strategies focus on minimizing interruptions, active listening, and assertively questioning the accuracy of contentious decisions. These may include diagnoses, treatment plans, and prognoses. Real-time monitoring of four teams of resident physicians conducting sign-outs simultaneously is extremely difficult for attending physicians without computerized decision support. In this study, we examined the impact of providing automated highlights of sign-out transcripts on the ability to judge the quality of the sign-out. A between-subject design was employed to compare performance with a system displaying four transcripts of sign-outs simultaneously vs. one with the automated highlights on the transcripts. Study participants were 16 fourth-year medical students. Hypothesized benefits of the computerized support on performance and efficiency were not detected. One explanation is that the participants did not understand or agree with the best practice communication strategies, which were used in the design of the highlighted information. Nevertheless, study participants without the computerized support were more likely to judge the supervisory task as not able to be performed safely (p

Numerous training interventions on patient handoffs have been initiated in the last few years, in part to meet new residency program accreditation requirements. Most of these programs focus on increasing the structure, comprehensiveness, and accuracy of the information conveyed by the outgoing clinician in either verbal or written format. Our team has developed online training that can augment these programs with how to foster resilient communication that increases overall system resilience, and thus reduces unintended patient harm. It is anticipated that improving communication competencies with resilient strategies during real-time verbal exchanges conducted at the shift change will increase the likelihood of detecting and addressing erroneous diagnostic assessments, prognoses, and inappropriate elements of treatment plans.

Die casting is a widely used high-technology manufacturing process which is both capital and energy intensive. While there are several economic and environmental advantages to die casting, the high energy consumption required to cast products warrants attention. Operational and design decisions within a die casting process can have a significant impact on the total energy use and equivalent carbon dioxide emissions. An absorbing-state Markov chain model of the die casting process represents the possible flows of material and measures the resource consumption of the most energy-intensive steps. The model supports decision-makers considering possible design, investment, and operational decisions, such as the purchase of new equipment. Data elements necessary to implement the model are specified, as are the necessary reference data for analyzing the emissions related to energy consumption. The use of the model is illustrated with a historical case study from a specific product design decision. Prescriptive uses of the model based on this case study are also analyzed, although the model supports a variety of analyses.

Handover communication improvement initiatives typically employ a "one size fits all" approach. A human factors perspective has the potential to guide how to tailor interventions to roles, levels of experience, settings, and types of patients. We conducted ethnographic observations of sign-outs by attending and resident physicians in 2 medical intensive care units at one institution. Digitally audiotaped data were manually analyzed for content using codes and time spent using box plots for emergent categories. A total of 34 attending and 58 resident physician handovers were observed. Resident physicians spent more time for "soon to be discharged" and "higher concern" patients than attending physicians. Resident physicians spent less time discussing patients which they had provided care for within the last 3 days ("handbacks"). The study suggested differences for how handovers were conducted for attending and resident physicians for 3 categories of patients; handovers differ on the basis of role or level of expertise, patient type, and amount of prior knowledge of the patient. The findings have implications for new directions for subsequent research and for how to tailor quality improvement interventions based upon the role, level of experience, level of prior knowledge, and patient categories.

Objective Although there is a growing recognition of the importance of active communication behaviours from the incoming clinician receiving a patient handover, there are currently no agreed-upon measures to objectively describe those behaviours. This study sought to identify differences in incoming clinician communication behaviours across levels of clinical training for physicians and nurses. Methods Handover observations were conducted during shift changes for attending physicians, resident physicians, registered nurses and nurse practitioners in three medical intensive care units from July 2011 to August 2012. Measures were the number of interjections from the incoming clinician and the communication mode of those interjections. Each collaborative cross-check, a specific type of interactive question, was subsequently classified by level of assertiveness. Results 133 patient handovers were analysed. Statistical differences were found in both measures. Higher levels of training were associated with fewer interjections, and a higher proportion of interactive questioning to detect erroneous assessments and actions by the incoming provider. All groups were observed to use the least assertive level of a collaborative cross-check, which contributed to misunderstandings. Nurses used less assertive collaborative cross-checks than physicians. Conclusions Differences across clinician type and levels of clinical training were found in both measures during patient handovers. The findings suggest that training could enable physicians and nurses to learn communication competencies during patient handovers which were used more frequently by more experienced practitioners, including interjecting less frequently and using interactive questioning strategies to clarify understanding, and assertively question the appropriateness of diagnoses, treatment plans and prognoses. Accompanying cultural change initiatives might be required to routinely employ these strategies in the clinical setting, particularly for nursing personnel.