Blocker, Renaldo C.

Abstract Background Provider burnout due to workload is a significant concern in primary care settings. Workload for primary care providers encompasses both scheduled visit care and non–visit care interactions. These interactions are highly influenced by patients' health conditions or acuity, which can be measured by the Adjusted Clinical Group (ACG) score. However, new patients typically have minimal health information beyond social determinants of health (SDOH) to determine ACG score. Objectives This study aims to assess new patient workload by first predicting the ACG score using SDOH, age, and gender and then using this information to estimate the number of appointments (scheduled visit care) and non–visit care interactions. Methods Two years of appointment data were collected for patients who had initial appointment requests in the first year and had the ACG score, appointment, and non–visit care counts in the subsequent year. State-of-art machine learning algorithms were employed to predict ACG scores and compared with current baseline estimation. Linear regression models were then used to predict appointments and non–visit care interactions, integrating demographic data, SDOH, and predicted ACG scores. Results The machine learning methods showed promising results in predicting ACG scores. Besides the decision tree, all other methods performed at least 9% better in accuracy than the baseline approach which had an accuracy of 78%. Incorporating SDOH and predicted ACG scores also significantly improved the prediction for both appointments and non–visit care interactions. The R 2 values increased by 95.2 and 93.8%, respectively. Furthermore, age, smoking tobacco, family history, gender, usage of injection birth control, and ACG were significant factors for determining appointments. SDOH factors such as tobacco usage, physical exercise, education level, and group activities were strongly correlated with non–visit care interactions. Conclusion The study highlights the importance of SDOH and predicted ACG scores in predicting provider workload in primary care settings.

Objective: In this study, we aim to develop and propose an evaluation method for analyzing the design of operating rooms (ORs) from the perspective of surgical teams’ reported experiences and stress levels. Background: Stress and burnout of surgical team members can lead to diminished performance and medical errors, which endangers the safety of both the patients and team members. The design and layout of the OR play a critical role in managing such stress. Methods: To understand surgical teams’ spatial needs related to their experiences and stress, we administered a survey and in-depth focus group discussions to three surgical teams from the same organization. The identified spatial needs were translated into functional scenarios and spatial metrics, essentially viewing the OR through the perspective of users. Results: Our analysis revealed four integral sections—patient flow, room organization, access to facilities/medical equipment/support staff/team members, and staff well-being—identified as critical design factors associated with the experiences and stress levels of the surgical teams in the ORs. Conclusions: We expect this method to serve as a tool for evaluating the effect of the design of OR layouts on stress, thereby supporting the well-being and resiliency of surgical teams.

A workplace that is a conduit for positive emotions can be important to employees retention and can contribute optimal levels of productivity. Validated tools for examining emotions are primarily subjective and retrospective in nature. Recent advances in technology have led to more novel and passive ways of measuring emotions. Wearable sensors, such as electroencephalogram (EEG), are being explored to assess cognitive and physical burdens objectively and in real-time. Therefore, there exists a need to investigate and validate the use of EEG to examine emotions objectively and in real-time. In this paper, we conducted a scoping review of EEG to measure positive emotions and/or indicators of joy in the workplace. Our review results in 22 articles that employ EEG to study joy in occupational settings. Three major themes identified in the analysis include (1) EEG for symptoms detection and outcomes, (2) Populations studied using EEG, and (3) EEG electrode systems.

Abstract A working environment which elicits positive emotions in employees is vital for employee retention, engagement and productivity. Wearable sensors provide the means to objectively measure the emotional responses of employees in the workplace in real-time. The study aim was to perform a preliminary investigation into the validity of two multimodal systems to classify employee’s emotional responses to positive, neutral or negative video stimuli: (1) using wearable electroencephalography (EEG) in combination with video-based facial expression analysis (FEA), and (2) using a wearable galvanic skin response (GSR) device in combination with video-based FEA. Five office employees each watched three short video clips at three time points during their regular work shifts while wearing EEG sensors on the forehead and GSR sensors on the middle and index fingers of their non-dominant hand with their face in view of a webcam. Russel’s circumplex model of affect was used to determine participant’s emotional responses to the video clips. The GSR device showed greater accuracy than the EEG device at detecting arousal responses to the video stimuli, with agreement, precision, and recall values of 87%, 100% and 80%, respectively, compared to 53%, 62%, and 80% for the EEG device. The FEA/EEG and FEA/GSR circumplex models were both able to accurately detect positive emotions elicited from video stimuli with levels of agreement and recall greater than 73%. Precision for the FEA/EEG model to detect positive stimuli was lower due to misclassification of 40% of both negative and neutral stimuli as positive. Precision values for both circumplex models were very low for detecting negative emotions. The results suggest that the EEG and GSR devices may be capable of detecting arousal when used alone, and detecting positive emotions when used in combination with video-based FEA in real-time in the workplace.

Studies utilizing a systems perspective show that individual work system elements impact surgeon workload. However, limited work has shown how multiple elements together can affect perceived workload in the healthcare domain. Using NASA-Task Load Index (NASA-TLX), this study aimed to compare operating room workload across two work system factors (surgical specialty and case number of the day) using a large set of self-reported surgeon workload data. Thirty-two surgeons completed 545 workload surveys across a three month period. Surgeons reported significant differences in composite workload scores across the surgical specialties (F(7,544)=3.622, p=0.001). Significant interactions were identified between surgical specialty and case number for composite workload, F(20,534)=1.72, p=0.027. While such findings are promising, future work is needed across multiple institutions to establish baseline workload values across specialties with different patient characteristics and work systems.

Abstract Objective The American College of Surgeons (ACS) encourages clinicians to provide training to laypeople on tourniquet application. It is unclear whether clinicians are confident in their abilities and equipped with adequate knowledge, skills, and resources. This study aimed to determine surgical trainee knowledge and attitudes regarding tourniquet application and compare the effectiveness of instructions. Methods Thirty surgical trainees performed a tourniquet application simulation using a Combat Application Tourniquet and one of the three instructions sets developed by ACS, Department of Homeland Security, and the tourniquet manufacturer. Participants reported tourniquet knowledge, attitudes, and confidence and discussed the instructions. One instruction set was updated and compared to the original set with 20 new trainees. Results Participants with ACS instructions passed the greatest number of steps (p < 0.01) and completed the task significantly faster compared to those with manufacturer instructions (p < 0.01). Participants (80%) reported favorable views toward tourniquets but 30–60% did not align with to ACS tourniquet guidelines. Focus group participants suggested revisions to the ACS instructions. Comparing the original and revised version of these instructions resulted in no significant improvements. Conclusions ACS instructions provide guidance; however, improvements to tourniquet instruction are needed for success in controlling exsanguinating hemorrhage.

Objective: Surgeon workload, or human “cost” of performing a procedure, is not well understood in light of emerging surgical technologies. This pilot study quantified surgeon workload for colorectal procedures and identified patient, surgeon, and procedural factors impacting workload. Summary Background Data: Innovative technologies and procedures in surgery have generally been promoted for the advancement of patient care. The resulting surgeon workload is poorly studied with little knowledge of the contributing factors impacting workload. Methods: Surgeons completed NASA-Task Load Index (NASA-TLX) questionnaires to self-assess workload following abdominopelvic colon and rectal procedures. Corresponding patient data were retrieved from the medical record. Descriptive statistics, correlations, and ANOVA were performed to compare surgeon and patient factors, procedure type, and surgical approach on workload overall and by subscales. Results: Seven attending surgeons rated 238 surgeries, of which 218 (92%) had corresponding patient data. Surgeon experience and patient demographics had inconsistent effects on workload. A statistically significant 3-way interaction was identified among disease process, procedure type, and surgical approach on workload (F(9, 146) = 2.17, P = 0.027), but was limited to open procedures for neoplasia and inflammatory bowel disease patients. Proctectomy and colectomy procedures compared across open, laparoscopic, and robotic approaches showed significant differences in overall workload and subscales, where the robotic procedures required significantly less mental demand, physical demand, and effort, than open or laparoscopic ( P < 0.05). Conclusions: Patient characteristics, disease process, and surgical experience had inconsistent effects on surgeon workload. Major differences in workload were identified for procedure type and surgical approach, where robotic procedures required less mental demand, physical demand, and effort.

The aim of this study was twofold—(1) to compare the current ED staffing workload alert system to clinicians’ perceptions of workload in the ED, and (2) to examine the potential impact of a multi-faceted, systems-level intervention on clinicians’ perceptions of workload. Constant flow of patients into the Emergency Departments (ED) regularly increases the workload of clinicians and can compromise the quality of care delivery and patient safety. An automatic staffing workload alert system was created and implemented in response to an observed shift in patient volume to the overnight hours at one academic quaternary care center. Surveys addressing workload and interruptions were administered to ED clinicians, pre-and post-intervention implementation. Output from the staffing workload alert system was recorded for each clinician shift. Clinicians’ perceptions of workload were able to predict swing shift activations, χ 2 (6) = 14.14, p = 0.028. Only the performance subscale significantly correlated with swing shift activations, p=0.006. A Kruskal-Wallis H test found perceived interruptions changed following systems-level changes, χ 2 (1) = 7.195, p = 0.007. Utilizing subjective measure of clinicians’ workload validated an objective, automated staffing workload alert system that determined if swing shift activations are necessary.

Objective: With advancements in surgical equipment and procedures, human–system interactions in operating rooms affect surgeon workload and performance. Workload was measured across surgical specialties using surveys to identify potential predictors of high workload for future performance improvement. Summary Background Data: Surgical instrumentation and technique advancements have implications for surgeon workload and human–systems interactions. To understand and improve the interaction of components in the work system, NASA-Task Load Index can measure workload across various fields. Baseline workload measurements provide a broad overview of the field and identify areas most in need of improvement. Methods: Surgeons were administered a modified NASA-Task Load Index survey (0 = low, 20 = high) following each procedure. Patient and procedural factors were retrieved retrospectively. Results: Thirty-four surgeons (41% female) completed 662 surgery surveys (M = 14.85, SD = 7.94), of which 506 (76%) have associated patient and procedural data. Mental demand (M = 7.7, SD = 5.56), physical demand (M = 7.0, SD = 5.66), and effort (M = 7.8, SD = 5.77) were the highest rated workload subscales. Surgeons reported difficulty levels higher than expected for 22% of procedures, during which workload was significantly higher ( P < 0.05) and procedural durations were significantly longer ( P > 0.001). Surgeons reported poorer perceived performance during cases with unexpectedly high difficulty ( P < 0.001). Conclusions: When procedural difficulty is greater than expected, there are negative implications for mental and physical demand that result in poorer perceived performance. Investigations are underway to identify patient and surgical variables associated with unexpected difficulty and high workload. Future efforts will focus on re-engineering the surgical planning process and procedural environment to optimize workload and performance for improved surgical care.

Interruptions in the emergency department (ED) have been studied across multiple clinical roles, with little investigation into how residents experience interruptions. Therefore this pilot study aimed to characterize interruptions experienced by emergency medicine (EM) residents at various post-graduate year (PGY) levels. Observers shadowed ED residents across entire shifts and logged interruptions that affected clinicians into the Workflow Interruption Tool (WIT). Interruption characteristics captured included duration, nature, location, and task priority. Chi-square analysis identified a significant association between interruption type and the interruption priority, p < 0.001. Residents at varying PGY-levels experienced significantly different amounts of interruptions, p=0.013. Observing resident interruptions across the entirety of their shifts identified that as EM residents gain more experience, they are interrupted more often while working in the ED.