Multitasking behaviors and provider outcomes in emergency department physicians: two consecutive, observational and multi-source studies

Surgical counting interruptions in operating rooms

BACKGROUND

Operating rooms are complex working environments with high workloads and high levels of cognitive demand. The first surgical count which occurs during the chaotic preoperative stage and is considered a critical phase, is a routine task in ORs. Interruptions often occur during the first surgical count; however, little is known about the first surgical counting interruptions. This study aimed to observe and analyse the sources, outcomes, frequency of the first surgical counting interruptions and responses to interruptions.

METHODS

A retrospective observational study was carried out to examine the occurrence of the first surgical counting interruptions between 1st August 2023 and 30th September 2023. The data were collected using the "Surgical Counting Interruption Event Form", which was developed by the researchers specifically for this study.

RESULTS

A total of 66 circulating nurses (CNs) and scrub nurses (SNs) were observed across 1015 surgeries, with 4927.8 min of surgical count. The mean duration of the first surgical count was 4.85 min, with a range of 1.03 min to 9.51 min. In addition, 697 interruptions were identified, with full-term interruptions occurring an average of 8.7 times per hour. The most frequent source of interruption during the first surgical counts was instruments (N = 144, 20.7%). The first surgical counting interruptions mostly affected the CN (336 times; 48.2%), followed by the ORNs (including CNs and SNs) (243 times; 34.9%) and the SN (118 times; 16.9%). Most of the outcomes of interruptions were negative, and the majority of the nurses responded immediately to interruptions.

CONCLUSIONS

The frequency of the first surgical counting interruption is high. Managers should develop interventions for interruptions based on different surgical specialties and different nursing roles.

Stroke Screening Process for Spanish-Speaking Patients

INTRODUCTION

The Balance Eyes Face Arms Speech Time stroke screening tool may have limitations for Spanish-speaking individuals. The purpose of this study is to identify potential screen failure events during evaluation for intervenable acute ischemic stroke events among Spanish-speaking patients.

METHODS

This is a retrospective, observational, single-center study at an urban academic center during 2020. Patients with a positive stroke screen were stratified by Spanish or non-Spanish. We measured last known well, sensitivity, specificity, negative predictive value, and positive predictive value of the emergency department provider's decision to escalate to complete stroke evaluation with acute ischemic stroke as the outcome of interest.

RESULTS

Among 796 patients (mean age of 52 years, 56% female, 37% Spanish speaking), 30% of patients with positive stroke screen were converted to complete stroke evaluation. For provider escalation to complete stroke evaluation for the outcome of acute ischemic stroke events, prevalence was 13%, sensitivity 81%, positive predictive value 22%, and negative predictive value 97% for the overall sample. Spanish-speaking patients were less likely to progress from screening to complete stroke evaluation (25.8% vs 32.8%; 95% for difference CI, 0.57-13.5). Importantly, there was no difference in rate of acute ischemic stroke between Spanish- and non-Spanish-speaking patients.

DISCUSSION

Over 1 year, with 796 patients triggered at triage by Balance Eyes Face Arms Speech Time for positive stroke screens, only 13% resulted in an acute ischemic stroke. Spanish-speaking patients were less likely to progress from screening to complete stroke evaluation, but the rate of acute ischemic stroke was not different by language.

Measuring Emergency Department Workload Perception Using Electronic Medical Record Measures of Patient Volume and Acuity

BACKGROUND

Workload in the emergency department (ED) fluctuates and there is no established model for measurement of clinician-level ED workload.

OBJECTIVE

The aim of this study was to measure perceived ED workload and assess the relationship between perceived workload and objective measures of workload from the electronic medical record (EMR).

METHODS

This study was conducted at a tertiary care, academic ED from July 1, 2020 through April 13, 2021. Attending workload perceptions were collected using a 5-point scale in three care areas with variable acuity. We collected eight EMR measures thought to correlate with perceived workload. EMR values were compared across areas of the department using ANOVA and correlated with attending workload ratings using linear regression.

RESULTS

We collected 315 unique workload ratings, which were normally distributed. For the entire department, there was a weak positive correlation between reported workload perception and mean percentage of inpatient admissions (r = 0.23; p < 0.001), intensive care unit admissions (r = 0.2; p < 0.001), patient arrivals per shift (r = 0.14; p = 0.017), critical care billed visits (r = 0.22; p < 0.001), cardiopulmonary resuscitation code activations (r = 0.2; p < 0.001), and level 5 visits (r = 0.13; p = 0.02). There was weak negative correlation for ED discharges (r = -0.23; p < 0.001). Several correlations were stronger in individual care areas, including percent admissions in the lowest-acuity area (r = 0.43; p = 0.033) and patient arrivals in the highest-acuity area (r = 0.44; p < .01). No significant correlation was found in any area for observation admissions or trauma activations.

CONCLUSIONS

In this study, EMR measures of workload were not closely correlated with ED attending physician workload perception. Future study should examine additional factors contributing to physician workload outside of the EMR.

Prospective effects of an artificial intelligence-based computer-aided detection system for prostate imaging on routine workflow and radiologists' outcomes

OBJECTIVES

Artificial intelligence (AI) is expected to alleviate the negative consequences of rising case numbers for radiologists. Currently, systematic evaluations of the impact of AI solutions in real-world radiological practice are missing. Our study addresses this gap by investigating the impact of the clinical implementation of an AI-based computer-aided detection system (CAD) for prostate MRI reading on clinicians' workflow, workflow throughput times, workload, and stress.

MATERIALS AND METHODS

CAD was newly implemented into radiology workflow and accompanied by a prospective pre-post study design. We assessed prostate MRI case readings using standardized work observations and questionnaires. The observation period was three months each in a single department. Workflow throughput times, PI-RADS score, CAD usage and radiologists' self-reported workload and stress were recorded. Linear mixed models were employed for effect identification.

RESULTS

In data analyses, 91 observed case readings (pre: 50, post: 41) were included. Variation of routine workflow was observed following CAD implementation. A non-significant increase in overall workflow throughput time was associated with CAD implementation (mean 16.99 ± 6.21 vs 18.77 ± 9.69 min, p = .51), along with an increase in diagnostic reading time for high suspicion cases (mean 15.73 ± 4.99 vs 23.07 ± 8.75 min, p = .02). Changes in radiologists' self-reported workload or stress were not found.

CONCLUSION

Implementation of an AI-based detection aid was associated with lower standardization and no effects over time on radiologists' workload or stress. Expectations of AI decreasing the workload of radiologists were not confirmed by our real-world study.

PRE-REGISTRATION

German register for clinical trials https://drks.de/; DRKS00027391.

Decision Fatigue among Emergency Physicians: Reality or Myth

How to cite this article: Nasa P, Majeed NA. Decision Fatigue among Emergency Physicians: Reality or Myth. Indian J Crit Care Med 2023;27(9):609-610.

Patient safety in emergency departments: a problem for health care systems? An international survey

BACKGROUND AND IMPORTANCE

Patient safety in healthcare is one of the cornerstones of quality of care. The emergency department (ED) is by its very nature a place where errors and safety issues are liable to occur.

OBJECTIVE

The aim of the study was to assess health professionals' perception of the level of safety in EDs and to identify in which work domains safety appears most at risk.

DESIGN AND PARTICIPANTS

Between 30 January and 27 February 2023, a survey addressing the main domains of safety was distributed to ED health care professionals through the European Society of Emergency Medicine contact network. It addressed five main domains: teamwork, safety leadership, physical environment and equipment, staff/external teams, and organisational factors and informatics, with a number of items for each domain. Further questions about infection control and team morale were added. The Cronbach's alpha measure was calculated to assure internal consistency.

MEASURES AND ANALYSIS

A score was developed for each domain by adding the question's value using the following ranking: never (1), rarely (2), sometimes (3), usually (4), and always (5) and was aggregated in three categories. The calculated sample size needed was 1000 respondents. The Wald method was used for analysis of the questions' consistency and X2 for the inferential analysis.

MAIN RESULTS

The survey included 1256 responses from 101 different countries; 70% of respondents were from Europe. The survey was completed by 1045 (84%) doctors and 199 (16%) nurses. It was noted that 568 professionals (45.2%) had less than 10 years' experience. Among respondents, 80.61% [95% confidence interval (CI) 78.42-82.8] reported that monitoring devices were available, and 74.7% (95% CI 72.28-77.11) reported that protocols for high-risk medication and for triage (66.19%) were available in their ED. The area of greatest concern was the disproportionate imbalance between needs and the availability of staff at times of greatest flow, considered sufficient by only 22.4% (95% CI 20.07-24.69) of doctors and 20.7% (95% CI 18.41-22.9) of nurses. Other critical issues were overcrowding due to boarding and a perceived lack of support from hospital management. Despite these difficult working conditions, 83% of the professionals said they were proud to work in the ED (95% CI 81.81-85.89).

CONCLUSION

This survey highlighted that most health professionals identify the ED as an environment with specific safety issues. The main factors appeared to be a shortage of personnel during busy periods, overcrowding due to boarding, and a perceived lack of support from hospital management.

Early prediction of hospital admission of emergency department patients

OBJECTIVE

The early prediction of hospital admission is important to ED patient management. Using available electronic data, we aimed to develop a predictive model for hospital admission.

METHODS

We analysed all presentations to the ED of a tertiary referral centre over 7 years. To our knowledge, our data set of nearly 600 000 presentations is the largest reported. Using demographic, clinical, socioeconomic, triage, vital signs, pathology data and keywords in electronic notes, we trained a machine learning (ML) model with presentations from 2015 to 2020 and evaluated it on a held-out data set from 2021 to mid-2022. We assessed electronic medical records (EMRs) data at patient arrival (baseline), 30, 60, 120 and 240 min after ED presentation.

RESULTS

The training data set included 424 354 data points and the validation data set 53 403. We developed and trained a binary classifier to predict inpatient admission. On a held-out test data set of 121 258 data points, we predicted admission with 86% accuracy within 30 min of ED presentation with 94% discrimination. All models for different time points from ED presentation produced an area under the receiver operating characteristic curve (AUC) ≥0.93 for admission overall, with sensitivity/specificity/F1-scores of 0.83/0.90/0.84 for any inpatient admission at 30 min after presentation and 0.81/0.92/0.84 at baseline. The models retained lower but still high AUC levels when separated for short stay units or inpatient admissions.

CONCLUSION

We combined available electronic data and ML technology to achieve excellent predictive performance for subsequent hospital admission. Such prediction may assist with patient flow.

An Adlerian-Based Narrative Inquiry of Temporal Awareness, Resilience, and Patient-Centeredness Among Emergency Physicians-The Gyroscope Model

INTRODUCTION

Although extensive research examined time perceptions among patients in the emergency department (ED), studies on temporal awareness among emergency physicians is scant. Salutogenics is the theoretical anchor.

METHODS

The sample comprised ten emergency resident physicians from an Israeli public tertiary hospital. Narrative interviews were conducted. To determine the theme of the study, Adlerian narrative analysis was performed. To identify categories, semantic and content analyses were performed.

RESULTS

Adlerian narrative analysis highlighted temporal awareness as a strong theme across interviews. Semantic and content analyses identified categories within temporal awareness. Analyses revealed a movement among three subcategories: A clinical task in which physicians rapidly shift along seven distinct times, temporal awareness shaping their work experience, and temporal awareness as inhibiting or enabling relationships with patients. Data-analyses identified two groups of physicians, one group driven by the need to control the time to avoid errors, experiencing anxiety and poor wellbeing, and the other, shifting from clinical tasks to patient-centeredness while removing the time factor from their considerations and experiencing resilience through manageability and meaningfulness. We introduce the "gyroscope model" for physicians to illustrate these findings and propose recommendations for practice.

DISCUSSION

Understanding the complexity of the temporal continuum and the influence of shifting from the clinical task to relationships with patients may contribute to resilience of resident physician in the ED and to their self-efficacy, enriching their professional skills and capacity to cope and grow while facing the complexity of the ED.

A Simulated Scenario to Improve Resident Efficiency in an Emergency Department

Introduction

Multitasking is a core competency in emergency medicine. Simulation has been shown to be an effective method of education, which allows learners to prepare for real-world challenges in a controlled environment.

Methods

In this study, trainees were given a scenario that simulated the experience of managing two patient encounters within a time metric while addressing interruptions that take place in a typical ED. Residents were evaluated using an internally developed scoresheet, which assessed task-switching abilities, documentation skills, and adherence to door to disposition time metric. Residents were asked to evaluate their experience with a survey.

Results

All the participants reported that they would translate some of the skills learned to their daily clinical practice. Five out of six residents reported improvements in their skills as a result of the task-switching training. The following three common themes were pervasive in the debrief discussion: (1) the residents felt the added pressure of the door-to-disposition metric, (2) the objectives of the simulation did not fit within their pre-constructed concept of a successful simulation equating to establishing the correct diagnosis, and (3) the interruptions were very realistic.

Discussion

Emergency physicians are interrupted approximately every 9-14 minutes, and this number increases with the number of patients being managed simultaneously. By developing a safe, simulated training environment, we sought to transfer key strategies for improving focus and learning to prioritize while also helping them to identify how certain pressures and interruptions affected their stress levels and concentration.