Small Patients but a Heavy Lift: Workload and Burnout of Advanced Practice Providers and Physicians in a Level IV Neonatal Intensive Care Unit.

OBJECTIVE: This study explored the association between workload and the level of burnout reported by clinicians in our neonatal intensive care unit (NICU). A qualitative analysis was used to identify specific factors that contributed to workload and modulated clinician workload in the NICU. STUDY DESIGN: We conducted a study utilizing postshift surveys to explore workload of 42 NICU advanced practice providers and physicians over a 6-month period. We used multinomial logistic regression models to determine associations between workload and burnout. We used a descriptive qualitative design with an inductive thematic analysis to analyze qualitative data. RESULTS: Clinicians reported feelings of burnout on nearly half of their shifts (44%), and higher levels of workload during a shift were associated with report of a burnout symptom. Our study identified 7 themes related to workload in the NICU. Two themes focused on contributors to workload, 3 themes focused on modulators of workload, and the final 2 themes represented mixed experiences of clinicians' workload. CONCLUSION: We found an association between burnout and increased workload. Clinicians in our study described common contributors to workload and actions to reduce workload. Decreasing workload and burnout along with improving clinician well-being requires a multifaceted approach on unit and systems levels.

Assessing Neonatal Intensive Care Unit Structures and Outcomes Before and During the COVID-19 Pandemic: Network Analysis Study.

BACKGROUND: Health care organizations (HCOs) adopt strategies (eg. physical distancing) to protect clinicians and patients in intensive care units (ICUs) during the COVID-19 pandemic. Many care activities physically performed before the COVID-19 pandemic have transitioned to virtual systems during the pandemic. These transitions can interfere with collaboration structures in the ICU, which may impact clinical outcomes. Understanding the differences can help HCOs identify challenges when transitioning physical collaboration to the virtual setting in the post-COVID-19 era. OBJECTIVE: This study aims to leverage network analysis to determine the changes in neonatal ICU (NICU) collaboration structures from the pre- to the intra-COVID-19 era. METHODS: In this retrospective study, we applied network analysis to the utilization of electronic health records (EHRs) of 712 critically ill neonates (pre-COVID-19, n=386; intra-COVID-19, n=326, excluding those with COVID-19) admitted to the NICU of Vanderbilt University Medical Center between September 1, 2019, and June 30, 2020, to assess collaboration between clinicians. We characterized pre-COVID-19 as the period of September-December 2019 and intra-COVID-19 as the period of March-June 2020. These 2 groups were compared using patients' clinical characteristics, including age, sex, race, length of stay (LOS), and discharge dispositions. We leveraged the clinicians' actions committed to the patients' EHRs to measure clinician-clinician connections. We characterized a collaboration relationship (tie) between 2 clinicians as actioning EHRs of the same patient within the same day. On defining collaboration relationship, we built pre- and intra-COVID-19 networks. We used 3 sociometric measurements, including eigenvector centrality, eccentricity, and betweenness, to quantify a clinician's leadership, collaboration difficulty, and broad skill sets in a network, respectively. We assessed the extent to which the eigenvector centrality, eccentricity, and betweenness of clinicians in the 2 networks are statistically different, using Mann-Whitney U tests (95% CI). RESULTS: Collaboration difficulty increased from the pre- to intra-COVID-19 periods (median eccentricity: 3 vs 4; P<.001). Nurses had reduced leadership (median eigenvector centrality: 0.183 vs 0.087; P<.001), and neonatologists with broader skill sets cared for more patients in the NICU structure during the pandemic (median betweenness centrality: 0.0001 vs 0.005; P<.001). The pre- and intra-COVID-19 patient groups shared similar distributions in sex (~0 difference), race (4% difference in White, and 3% difference in African American), LOS (interquartile range difference in 1.5 days), and discharge dispositions (~0 difference in home, 2% difference in expired, and 2% difference in others). There were no significant differences in the patient demographics and outcomes between the 2 groups. CONCLUSIONS: Management of NICU-admitted patients typically requires multidisciplinary care teams. Understanding collaboration structures can provide fine-grained evidence to potentially refine or optimize existing teamwork in the NICU.

A Time and Motion Analysis of Nursing Workload and Electronic Health Record Use in the Emergency Department.

INTRODUCTION: The use of an electronic health record may create unanticipated consequences for emergency care delivery. We sought to describe emergency department nursing task distribution and the use of the electronic health record. METHODS: This was a prospective observational study of nurses in the emergency department using a time-and-motion methodology. Three trained research assistants conducted 1:1 observations between March and September 2019. Nurse tasks were classified into 6 established categories: electronic health record, direct/indirect patient care, communication, personal time, and other. Nurses' perceived workload was assessed using the National Aeronautics and Space Administration (NASA) Task Load Index. RESULTS: Twenty-three observations were conducted over 46 hours. Overall, nurses spent 27% of their time on electronic health record tasks, 25% on direct patient care, 17% on personal time, 15% on indirect patient care, and 6% on communication. During morning (7 am-12 pm) and afternoon shifts (12 pm-3 pm), the use of the health record was the most commonly performed task, whereas indirect patient care was the task most performed during evening shifts (3 pm-12 pm). Using the National Aeronautics and Space Administration (NASA) Task Load Index, nurses reported an increase in mental demand and effort during afternoon shifts compared with morning shifts. DISCUSSION: We observed that emergency nurses spent more time using the electronic health record as compared to other tasks. Increased usability of the electronic health record, particularly during high occupancy periods, may be a target for improvement.

A simulation-based curriculum to introduce key teamwork principles to entering medical students.

BACKGROUND: Failures of teamwork and interpersonal communication have been cited as a major patient safety issue. Although healthcare is increasingly being provided in interdisciplinary teams, medical school curricula have traditionally not explicitly included the specific knowledge, skills, attitudes, and behaviors required to function effectively as part of such teams. METHODS: As part of a new "Foundations" core course for beginning medical students that provided a two-week introduction to the most important themes in modern healthcare, a multidisciplinary team, in collaboration with the Center for Experiential Learning and Assessment, was asked to create an experiential introduction to teamwork and interpersonal communication. We designed and implemented a novel, all-day course to teach second-week medical students basic teamwork and interpersonal principles and skills using immersive simulation methods. Students' anonymous comprehensive course evaluations were collected at the end of the day. Through four years of iterative refinement based on students' course evaluations, faculty reflection, and debriefing, the course changed and matured. RESULTS: Four hundred twenty evaluations were collected. Course evaluations were positive with almost all questions having means and medians greater than 5 out of 7 across all 4 years. Sequential year comparisons were of greatest interest for examining the effects of year-to-year curricular improvements. Differences were not detected among any of the course evaluation questions between 2007 and 2008 except that more students in 2008 felt that the course further developed their "Decision Making Abilities" (OR 1.69, 95% CI 1.07-2.67). With extensive changes to the syllabus and debriefer selection/assignment, concomitant improvements were observed in these aspects between 2008 and 2009 (OR = 2.11, 95% CI: 1.28-3.50). Substantive improvements in specific exercises also yielded significant improvements in the evaluations of those exercises. CONCLUSIONS: This curriculum could be valuable to other medical schools seeking to inculcate teamwork foundations in their medical school's preclinical curricula. Moreover, this curriculum can be used to facilitate teamwork principles important to inter-disciplinary, as well as uni-disciplinary, collaboration.

An Electronic Emergency Triage System to Improve Patient Distribution by Critical Outcomes.

BACKGROUND: Patient triage is necessary to manage excessive patient volumes and identify those with critical conditions. The most common triage system used today, Emergency Severity Index (ESI), focuses on resources utilized and critical outcomes. OBJECTIVE: This study derives and validates a computer-based electronic triage system (ETS) to improve patient acuity distribution based on serious patient outcomes. METHODS: This cross-sectional study of 25,198 (97 million weighted) adult emergency department visits from the 2009 National Hospital Ambulatory Medical Care Survey. The ETS distributes patients by using a composite outcome based on the estimated probability of mortality, intensive care unit admission, or transfer to operating room or catheterization suite. We compared the ETS with the ESI based on the differentiation of patients, outcomes, inpatient hospitalization, and resource utilization. RESULTS: Of the patients included, 3.3% had the composite outcome and 14% were admitted, and 2.52 resources/patient were used. Of the 90% triaged to low-acuity levels, ETS distributed patients evenly (Level 3: 30%; Level 4: 30%, and Level 5: 29%) compared to ESI (46%, 34%, and 7%, respectively). The ETS better-identified patients with the composite outcome present in 40% of ETS Level 1 vs. 17% for ESI and the ETS area under the receiver operating characteristic curve (AUC) was 0.83 vs. ESI 0.73. Similar results were found for hospital admission (ETS AUC = 0.83 vs. ESI AUC = 0.72). The ETS demonstrated slight improvements in discriminating patient resource utilization. CONCLUSIONS: The ETS is a triage system based on the frequency of critical outcomes that demonstrate improved differentiation of patients compared to the current standard ESI.

Reducing intraoperative red blood cell unit wastage in a large academic medical center.

BACKGROUND: The wastage of red blood cell (RBC) units within the operative setting results in significant direct costs to health care organizations. Previous education-based efforts to reduce wastage were unsuccessful at our institution. We hypothesized that a quality and process improvement approach would result in sustained reductions in intraoperative RBC wastage in a large academic medical center. STUDY DESIGN AND METHODS: Utilizing a failure mode and effects analysis supplemented with time and temperature data, key drivers of perioperative RBC wastage were identified and targeted for process improvement. RESULTS: Multiple contributing factors, including improper storage and transport and lack of accurate, locally relevant RBC wastage event data were identified as significant contributors to ongoing intraoperative RBC unit wastage. Testing and implementation of improvements to the process of transport and storage of RBC units occurred in liver transplant and adult cardiac surgical areas due to their history of disproportionately high RBC wastage rates. Process interventions targeting local drivers of RBC wastage resulted in a significant reduction in RBC wastage (p < 0.0001; adjusted odds ratio, 0.24; 95% confidence interval, 0.15-0.39), despite an increase in operative case volume over the period of the study. Studied process interventions were then introduced incrementally in the remainder of the perioperative areas. CONCLUSIONS: These results show that a multidisciplinary team focused on the process of blood product ordering, transport, and storage was able to significantly reduce operative RBC wastage and its associated costs using quality and process improvement methods.

A Multimodal Intervention Improves Postanesthesia Care Unit Handovers.

BACKGROUND: Failures of communication are a major contributor to perioperative adverse events. Transitions of care may be particularly vulnerable. We sought to improve postoperative handovers. METHODS: We introduced a multimodal intervention in an adult and a pediatric postanesthesia care unit (PACU) to improve postoperative handovers between anesthesia providers (APs) and PACU registered nurses (RNs). The intervention included a standardized electronic handover report form, a didactic webinar, mandatory simulation training focused on improving interprofessional communication, and post-training performance feedback. Trained, blinded nurse observers scored PACU handovers during 17 months using a structured tool consisting of 8 subscales and a global score (1-5 scale). Multivariate logistic regression assessed the effect of the intervention on the proportion of observed handovers receiving a global effectiveness rating of ≥3. RESULTS: Four hundred fifty-two clinicians received the simulation-based training, and 981 handovers were observed and rated. In the adult PACU, the estimated percentages of acceptable handovers (global ratings ≥3) among AP-RN pairs, where neither received simulation-based training (untrained dyads), was 3% (95% confidence interval, 1%-11%) at day 0, 10% (5%-19%) at training initiation (day 40), and 57% (33%-78%) at 1-year post-training initiation (day 405). For AP-RN pairs where at least one received the simulation-based training (trained dyads), these percentages were estimated to be 18% (11%-28%) and 68% (57%-76%) on days 40 and 405, respectively. The percentage of acceptable handovers was significantly greater on day 405 than it was on day 40 for both untrained (P < 0.001) and trained dyads (P < 0.001). Similar patterns were observed in the pediatric PACU. Three years later, the unadjusted estimate of the probability of an acceptable handover was 87% (72%-95%) in the adult PACU and 56% (40%-72%) in the pediatric PACU. CONCLUSIONS: A multimodal intervention substantially improved interprofessional PACU handovers, including those by clinicians who had not undergone formal simulation training. An effect appeared to be present >3 years later.

Methodology and bias in assessing compliance with a surgical safety checklist.

BACKGROUND: Surgical safety checklists, such as the perioperative time-out, have been shown to improve performance on a variety of patient safety measures. A variety of methods have been used to assess compliance with the perioperative time-out, but no standardized methodology with a reliable observer group currently exists. An observation-based methodology was used to assess time-out compliance at an academic medical center. METHODS: A single observer group made up of medical students and nurses recorded compliance with each of the 11 standardized items of the time-out. A total of 193 time-out procedures were observed, 48 by medical students and 145 by nurses. RESULTS: One item (procedure to be performed) achieved > 95% compliance. Three items (surgical site; availability of necessary blood products, implants, devices; and start of antibiotics) achieved 80%-95% compliance. Seven items achieved < 80% compliance (presence of required members of procedure team, presence of person who marked patient, patient identity, side marking, relevant images, allergies, and discussion of relevant special considerations). Compliance with the four core time-out items was 78.2%. Of the 11 items on the time-out being evaluated, there was a statistically significant difference between medical student and nursing observations for 10 items (p < .05). CONCLUSIONS: In our cohort of observed time-outs, the compliance rate was low, calling into question time-out quality, and, more importantly, patient safety. Measures must be taken by large hospitals to regularly audit time-out compliance and create effective programming to improve performance. Although observational assessment is an effective method to assess compliance with surgical safety checklists, observer group bias has the potential to skew results.

Workload In Neonatology (WORKLINE): Validation and feasibility of a system for measuring clinician workload integrated into the electronic health record.

OBJECTIVE: The purpose of the study was to validate WORKLINE, a NICU specific clinician workload model and to evaluate the feasibility of integrating WORKLINE into our EHR. STUDY DESIGN: This was a prospective, observational study of the workload of 42 APPs and physicians in a large academic medical center NICU over a 6-month period. We used regression models with robust clustered standard errors to test associations of WORKLINE values with NASA Task Load Index (NASA-TLX) scores. RESULTS: We found significant correlations between WORKLINE and NASA-TLX scores. APP caseload was not significantly associated with WORKLINE scores. We successfully integrated the WORKLINE model into our EHR to automatically generate workload scores. CONCLUSION: WORKLINE provides an objective method to quantify the workload of clinicians in the NICU, and for APPs, performed better than caseload numbers to reflect workload. Integrating the WORKLINE model into the EHR was feasible and enabled automated workload scores.

Real-time forecasting of pediatric intensive care unit length of stay using computerized provider orders.

OBJECTIVE: To develop a model to produce real-time, updated forecasts of patients' intensive care unit length of stay using naturally generated provider orders. The model was designed to be integrated within a computerized decision support system to improve patient flow management. DESIGN: Retrospective cohort study. SETTING: Twenty-six bed pediatric intensive care unit within an urban, academic children's hospital using a computerized order entry system. PATIENTS: A total of 2,178 consecutive pediatric intensive care unit admissions during a 16-month time period. MEASUREMENTS AND MAIN RESULTS: We obtained unit length of stay measurements, time-stamped provider orders, age, admission source, and readmission status. A joint discrete-time logistic regression model was developed to produce probabilistic length of stay forecasts from continuously updated provider orders. Accuracy was assessed by comparing forecasted expected discharge time with observed discharge time, rank probability scoring, and calibration curves. Cross-validation procedures were conducted. The distribution of length of stay was heavily right-skewed with a mean of 3.5 days (95% confidence interval 0.3-19.1). Provider orders were predictive of length of stay in real-time accurately forecasting discharge within a 12-hr window: 46% for patients within 1 day of discharge, 34% for patients within 2 days of discharge, and 27% for patients within 3 days of discharge. The forecast model incorporating predictive orders demonstrated significant improvements in accuracy compared with forecasts based solely on empirical and temporal information. Seventeen predictive orders were found, grouped by medication, ventilation, laboratory, diet, activity, foreign body, and extracorporeal membrane oxygenation. CONCLUSIONS: Provider orders reflect dynamic changes in patients' conditions, making them useful for real-time length of stay prediction and patient flow management. Patients' length of stay represent a major source of variability in intensive care unit resource utilization and if accurately predicted and communicated, may lead to proactive bed management with more efficient patient flow.

Surgical debriefing: a reliable roadmap to completing the patient safety cycle.

Morbidity and mortality due to preventable medical errors are a disastrous reality in medicine. Debriefing, a process that allows individuals to discuss team performance in a constructive, supportive environment, has been linked to improved performance in various medical and surgical fields, including improvements in specific procedures, teamwork and communication, and error identification. However, the neurosurgical literature on this topic is limited. The authors review the debriefing literature in the field of medicine, with a specific emphasis on the operating room, and they report their own institutional experience with a debriefing module, from invention to pilot implementation, at Vanderbilt University Medical Center. The authors share the challenges and lessons learned from their quality improvement project. The field of neurosurgery would undoubtedly benefit from embracing debriefing, as its potential has been established in other medical specialties and can serve as a valuable role in immediately learning from mistakes. The authors hope that their colleagues can learn from this experience and improve their own.

Perioperative Care Structures and Non-Routine Events: Network Analysis.

Non-routine events (NREs) are any aspect of care perceived by clinicians as a deviation from optimal care. The reporting of NREs to peers (or care teams) may help healthcare organizations improve patient safety in high-risk work environments (e.g., surgery). While various factors, including care structure and organizational factors may influence a clinician's NRE reporting behavior, their role has not been systematically studied. We conducted a retrospective study relying on NREs and electronic health records to determine if perioperative interaction structures among clinicians are associated with the frequency of NRE reporting in a large academic medical center. The data covers November 1, 2016, to January 31, 2019 and includes 295 perioperative clinicians, 225 neonatal surgical cases, and 543 NREs. Using network analysis, we measured a clinician's status in interaction structures according to the sociometric factors of degree, betweenness, and eigenvector centrality. We applied a proportional odds model to measure the relationship between each sociometric factor and NRE reporting frequency. Our findings indicate that the centrality of clinicians is directly associated with the quantity of NREs per surgical case.

A pilot study to determine the incidence, type, and severity of non-routine events in neonates undergoing gastrostomy tube placement.

BACKGROUND: Non-routine events (NRE) are defined as any suboptimal occurrences in a process being measured in the opinion of the reporter and comes from the field of human factors engineering. These typically occur well up-stream of an adverse event and NRE measurement has not been applied to the complex context of neonatal surgery. We sought to apply this novel safety event measurement methodology to neonates in the NICU undergoing gastrostomy tube placement. METHODS: A prospective pilot study was conducted between November 2016 and August 2020 in the Level IV NICU and the pediatric operating rooms of an urban academic children's hospital to determine the incidence, severity, impact, and contributory factors of clinician-reported non-routine events (NREs, i.e., deviations from optimal care) and 30-day NSQIP occurrences in neonates receiving a G-tube. RESULTS: Clinicians reported at least one NRE in 32 of 36 (89%) G-tube cases, averaging 3.0 (Standard deviation: 2.5) NRE reports per case. NSQIP-P review identified 7 cases (19%) with NSQIP-P occurrences and each of these cases had multiple reported NREs. One case in which NREs were not reported was without NSQIP-P occurrences. The odds ratio of having a NSQIP-P occurrence with the presence of an NRE was 0.695 (95% CI 0.06-17.04). CONCLUSION: Despite being considered a "simple" operation, >80% of neonatal G-tube placement operations had at least one reported NRE by an operative team member. In this pilot study, NRE occurrence was not significantly associated with the subsequent reporting of an NSQIP-P occurrence. Understanding contributory factors of NREs that occur in neonatal surgery may promote surgical safety efforts and should be evaluated in larger and more diverse populations. LEVEL OF EVIDENCE: IV.

Blood product positive patient identification: comparative simulation-based usability test of two commercial products.

BACKGROUND: The blood product administration process has been subject to various quality improvement initiatives aimed at reducing errors, including blood product labels that are missing, inaccessible, unreadable, or mismatched to orders and/or patients. This article reports the results of a formal simulation-based usability test of two comparable technologies designed to reduce blood product administration errors. STUDY DESIGN AND METHODS: Nineteen nurses and three anesthesia providers evaluated one of the two products during simulated use in realistic scenarios during 90-minute test sessions. Both products required additional learning despite 15 minutes of dedicated vendor-provided pretest training. RESULTS: There were significant effectiveness differences between the two products, but use of both devices was less efficient than manual checking. Usability issues included poor access to subtasks, lack of process feedback, inadequate error messaging, and confusing device interactions. CONCLUSION: While clinicians' subjective ratings of both devices were similarly high, both products had significant usability issues likely to lead to clinician frustration and workarounds during actual use. This study suggests that usability testing is a valuable and more effective method than preference surveys of determining the ability of blood administration products to meet clinicians' needs in the complex world of patient care.

Measuring Collaboration Through Concurrent Electronic Health Record Usage: Network Analysis Study.

BACKGROUND: Collaboration is vital within health care institutions, and it allows for the effective use of collective health care worker (HCW) expertise. Human-computer interactions involving electronic health records (EHRs) have become pervasive and act as an avenue for quantifying these collaborations using statistical and network analysis methods. OBJECTIVE: We aimed to measure HCW collaboration and its characteristics by analyzing concurrent EHR usage. METHODS: By extracting concurrent EHR usage events from audit log data, we defined concurrent sessions. For each HCW, we established a metric called concurrent intensity, which was the proportion of EHR activities in concurrent sessions over all EHR activities. Statistical models were used to test the differences in the concurrent intensity between HCWs. For each patient visit, starting from admission to discharge, we measured concurrent EHR usage across all HCWs, which we called temporal patterns. Again, we applied statistical models to test the differences in temporal patterns of the admission, discharge, and intermediate days of hospital stay between weekdays and weekends. Network analysis was leveraged to measure collaborative relationships among HCWs. We surveyed experts to determine if they could distinguish collaborative relationships between high and low likelihood categories derived from concurrent EHR usage. Clustering was used to aggregate concurrent activities to describe concurrent sessions. We gathered 4 months of EHR audit log data from a large academic medical center's neonatal intensive care unit (NICU) to validate the effectiveness of our framework. RESULTS: There was a significant difference (P<.001) in the concurrent intensity (proportion of concurrent activities: ranging from mean 0.07, 95% CI 0.06-0.08, to mean 0.36, 95% CI 0.18-0.54; proportion of time spent on concurrent activities: ranging from mean 0.32, 95% CI 0.20-0.44, to mean 0.76, 95% CI 0.51-1.00) between the top 13 HCW specialties who had the largest amount of time spent in EHRs. Temporal patterns between weekday and weekend periods were significantly different on admission (number of concurrent intervals per hour: 11.60 vs 0.54; P<.001) and discharge days (4.72 vs 1.54; P<.001), but not during intermediate days of hospital stay. Neonatal nurses, fellows, frontline providers, neonatologists, consultants, respiratory therapists, and ancillary and support staff had collaborative relationships. NICU professionals could distinguish high likelihood collaborative relationships from low ones at significant rates (3.54, 95% CI 3.31-4.37 vs 2.64, 95% CI 2.46-3.29; P<.001). We identified 50 clusters of concurrent activities. Over 87% of concurrent sessions could be described by a single cluster, with the remaining 13% of sessions comprising multiple clusters. CONCLUSIONS: Leveraging concurrent EHR usage workflow through audit logs to analyze HCW collaboration may improve our understanding of collaborative patient care. HCW collaboration using EHRs could potentially influence the quality of patient care, discharge timeliness, and clinician workload, stress, or burnout.

Collaboration Structures in COVID-19 Critical Care: Retrospective Network Analysis Study.

BACKGROUND: Few intensive care unit (ICU) staffing studies have examined the collaboration structures of health care workers (HCWs). Knowledge about how HCWs are connected to the care of critically ill patients with COVID-19 is important for characterizing the relationships among team structures, care quality, and patient safety. OBJECTIVE: We aimed to discover differences in the teamwork structures of COVID-19 critical care by comparing HCW collaborations in the management of critically ill patients with and without COVID-19. METHODS: In this retrospective study, we used network analysis methods to analyze the electronic health records (EHRs) of 76 critically ill patients (with COVID-19: n=38; without COVID-19: n=38) who were admitted to a large academic medical center, and to learn about HCW collaboration. We used the EHRs of adult patients who were admitted to the COVID-19 ICU at the Vanderbilt University Medical Center (Nashville, Tennessee, United States) between March 17, 2020, and May 31, 2020. We matched each patient according to age, gender, and their length of stay. Patients without COVID-19 were admitted to the medical ICU between December 1, 2019, and February 29, 2020. We used two sociometrics-eigencentrality and betweenness-to quantify HCWs' statuses in networks. Eigencentrality characterizes the degree to which an HCW is a core person in collaboration structures. Betweenness centrality refers to whether an HCW lies on the path of other HCWs who are not directly connected. This sociometric was used to characterize HCWs' broad skill sets. We measured patient staffing intensity in terms of the number of HCWs who interacted with patients' EHRs. We assessed the statistical differences in the core and betweenness statuses of HCWs and the patient staffing intensities of COVID-19 and non-COVID-19 critical care, by using Mann-Whitney U tests and reporting 95% CIs. RESULTS: HCWs in COVID-19 critical care were more likely to frequently work with each other (eigencentrality: median 0.096) than those in non-COVID-19 critical care (eigencentrality: median 0.057; P<.001). Internal medicine physicians in COVID-19 critical care had higher core statuses than those in non-COVID-19 critical care (P=.001). Nurse practitioners in COVID-19 care had higher betweenness statuses than those in non-COVID-19 care (P<.001). Compared to HCWs in non-COVID-19 settings, the EHRs of critically ill patients with COVID-19 were used by a larger number of internal medicine nurse practitioners (P<.001), cardiovascular nurses (P<.001), and surgical ICU nurses (P=.002) and a smaller number of resident physicians (P<.001). CONCLUSIONS: Network analysis methodologies and data on EHR use provide a novel method for learning about differences in collaboration structures between COVID-19 and non-COVID-19 critical care. Health care organizations can use this information to learn about the novel changes that the COVID-19 pandemic has imposed on collaboration structures in urgent care.

Mining tasks and task characteristics from electronic health record audit logs with unsupervised machine learning.

OBJECTIVE: The characteristics of clinician activities while interacting with electronic health record (EHR) systems can influence the time spent in EHRs and workload. This study aims to characterize EHR activities as tasks and define novel, data-driven metrics. MATERIALS AND METHODS: We leveraged unsupervised learning approaches to learn tasks from sequences of events in EHR audit logs. We developed metrics characterizing the prevalence of unique events and event repetition and applied them to categorize tasks into 4 complexity profiles. Between these profiles, Mann-Whitney U tests were applied to measure the differences in performance time, event type, and clinician prevalence, or the number of unique clinicians who were observed performing these tasks. In addition, we apply process mining frameworks paired with clinical annotations to support the validity of a sample of our identified tasks. We apply our approaches to learn tasks performed by nurses in the Vanderbilt University Medical Center neonatal intensive care unit. RESULTS: We examined EHR audit logs generated by 33 neonatal intensive care unit nurses resulting in 57 234 sessions and 81 tasks. Our results indicated significant differences in performance time for each observed task complexity profile. There were no significant differences in clinician prevalence or in the frequency of viewing and modifying event types between tasks of different complexities. We presented a sample of expert-reviewed, annotated task workflows supporting the interpretation of their clinical meaningfulness. CONCLUSIONS: The use of the audit log provides an opportunity to assist hospitals in further investigating clinician activities to optimize EHR workflows.

Defining the Epidemiology of Safety Risks in Neonatal Intensive Care Unit Patients Requiring Surgery.

OBJECTIVE: The aim of the study was to determine the incidence, type, severity, preventability, and contributing factors of nonroutine events (NREs)-events perceived by care providers or skilled observers as a deviations from optimal care based on the clinical situation-in the perioperative (i.e., preoperative, operative, and postoperative) care of surgical neonates in the neonatal intensive care unit and operating room. METHODS: A prospective observational study of noncardiac surgical neonates, who received preoperative and postoperative neonatal intensive care unit care, was conducted at an urban academic children's hospital between November 1, 2016, and March 31, 2018. One hundred twenty-nine surgical cases in 109 neonates were observed. The incidence and description of NREs were collected via structured researcher-administered survey tool of involved clinicians. Primary measurements included clinicians' ratings of NRE severity and contributory factors and trained research assistants' ratings of preventability. RESULTS: One or more NREs were reported in 101 (78%) of 129 observed cases for 247 total NREs. Clinicians reported 2 (2) (median, interquartile range) NREs per NRE case with a maximum severity of 3 (1) (possible range = 1-5). Trained research assistants rated 47% of NREs as preventable and 11% as severe and preventable. The relative risks for National Surgical Quality Improvement Program - pediatric major morbidity and 30-day mortality were 1.17 (95% confidence interval = 0.92-1.48) and 1.04 (95% confidence interval = 1.00-1.08) in NRE cases versus non-NRE cases. CONCLUSIONS: The incidence of NREs in neonatal perioperative care at an academic children's hospital was high and of variable severity with a myriad of contributory factors.

Measuring and comparing safety climate in intensive care units.

BACKGROUND: Learning about the factors that influence safety climate and improving the methods for assessing relative performance among hospital or units would improve decision-making for clinical improvement. OBJECTIVES: To measure safety climate in intensive care units (ICU) owned by a large for-profit integrated health delivery systems; identify specific provider, ICU, and hospital factors that influence safety climate; and improve the reporting of safety climate data for comparison and benchmarking. RESEARCH DESIGN: We administered the Safety Attitudes Questionnaire (SAQ) to clinicians, staff, and administrators in 110 ICUs from 61 hospitals. SUBJECTS: A total of 1502 surveys (43% response) from physicians, nurses, respiratory therapists, pharmacists, mangers, and other ancillary providers. MEASURES: The survey measured safety climate across 6 domains: teamwork climate; safety climate; perceptions of management; job satisfaction; working conditions; and stress recognition. Percentage of positive scores, mean scores, unadjusted random effects, and covariate-adjusted random effect were used to rank ICU performance. RESULTS: The cohort was characterized by a positive safety climate. Respondents scored perceptions of management and working conditions significantly lower than the other domains of safety climate. Respondent job type was significantly associated with safety climate and domain scores. There was modest agreement between ranking methodologies using raw scores and random effects. CONCLUSIONS: The relative proportion of job type must be considered before comparing safety climate results across organizational units. Ranking methodologies based on raw scores and random effects are viable for feedback reports. The use of covariate-adjusted random effects is recommended for hospital decision-making.

The effect of physician triage on emergency department length of stay.

BACKGROUND: Emergency Department (ED) overcrowding is a serious public health issue, but few solutions exist. OBJECTIVES: We sought to determine the impact of physician triage on ED length of stay for discharged and admitted patients, left-without-being-seen (LWBS) rates, and ambulance diversion. METHODS: This was a pre-post study performed using retrospective data at an urban, academic tertiary care, Level I trauma center. On July 11, 2005, physician triage was initiated from 1:00 p.m. to 9:00 p.m., 7 days a week. An additional physician was placed in triage so that the ED diagnostic evaluation and treatment could be started in waiting room patients. Using the hospital information system, we obtained individual patient data, ED and waiting room statistics, and diversion status data from a 9-week pre-physician triage (May 11, 2005 to July 10, 2005) and a 9-week physician triage (July 11, 2005 to September 9, 2005) period. RESULTS: We observed that overall ED length of stay decreased by 11 min, but this decrease was entirely attributed to non-admitted patients. No difference in ED length of stay was observed in admitted patients. LWBS rates decreased from 4.5% to 2.5%. Total time spent on ambulance diversion decreased from 5.6 days per month to 3.2 days per month. CONCLUSION: Physician triage was associated with a decrease in LWBS rates, and time spent on ambulance diversion. However, its effect on ED LOS was modest in non-admitted ED patients and negligible in admitted patients.