Development and validation of an assessment tool for nursing workload in emergency departments

Quantifying emergency department nursing workload at the task level using NASA-TLX: An exploratory descriptive study

BACKGROUND

Emergency departments (ED) nurses experience high mental workloads because of unpredictable work environments; however, research evaluating ED nursing workload using a tool incorporating nurses' perception is lacking. Quantify ED nursing subjective workload and explore the impact of work experience on perceived workload.

METHODS

Thirty-two ED nurses at a tertiary academic hospital in the Republic of Korea were surveyed to assess their subjective workload for ED procedures using the National Aeronautics and Space Administration Task Load Index (NASA-TLX). Nonparametric statistical analysis was performed to describe the data, and linear regression analysis was conducted to estimate the impact of work experience on perceived workload.

RESULTS

Cardiopulmonary resuscitation (CPR) had the highest median workload, followed by interruption from a patient and their family members. Although inexperienced nurses perceived the 'special care' procedures (CPR and defibrillation) as more challenging compared with other categories, analysis revealed that nurses with more than 107 months of experience reported a significantly higher workload than those with less than 36 months of experience.

CONCLUSION

Addressing interruptions and customizing training can alleviate ED nursing workload. Quantified perceived workload is useful for identifying acceptable thresholds to maintain optimal workload, which ultimately contributes to predicting nursing staffing needs and ED crowding.

The effect of the intensive care unit nurse manpower on care behaviours and stress level on the nurses

BACKGROUND

Nurses working in the intensive care units (ICU) regarding the work-index-nursing work environment, the effect level ICU environment has on the nurses' care behaviors and stress levels of the nurses should be determined.

OBJECTIVE

The study aimed to investigate the effect of the nurse manpower on care behaviours and stress level of the nurses working in the ICU.

METHODS

This was a cross-sectional and correlational study. The sample of the study consisted of 123 nurses working in the ICUs. The data were collected using the survey form, Distress Thermometer (DT), The Practice Work Environment Scale of the Nursing Work Index (PES-NWI), and Caring Behaviors Scale-24 (CBS-24).

RESULTS

The mean age of nurses in the ICU was 30.2±5.6 and the mean of working time in the intensive care unit of nurses in the ICU was 3.7±3.1 years. The mean of the DT was 4.8±3.4, and the mean score of PES-NWI was 2.6±1.0 and the mean score of CBS-24 was 4.7±1.1 in nurses in the ICU. The regression model which was studied to investigate the relationship between caring behaviors and stress and nurse manpower of nurses working in intensive care unit was significant.

CONCLUSION

Care behaviors and stress levels of nurses working in intensive care units are negatively affected by insufficient nurse manpower.

Subjective mental workload in Spanish emergency nurses. A study on predictive factors

INTRODUCTION

Mental workload refers to the cognitive or intellectual requirements that a worker is subjected to in a workday. The objective of the present work was to discover the subjective mental workload of nursing staff at Hospital Emergency Units, and its relationship with sociodemographic, work, environmental factors at the workplace, and personality variables.

METHOD

A quantitative, descriptive, observational, and crosssectional study was conducted with 201 emergency nurses from 13 different provinces in Spain. Each participant completed 5 questionnaires (sociodemographic, work conditions, environmental conditions, personality, and subjective mental workload). Descriptive statistics were obtained, and Pearson's correlations and multivariate models (multiple linear regression) were performed.

RESULTS

The nurses had medium to high levels of mental workload. The environmental conditions had a direct relationship with the mental workload, especially with respect to noise and lighting. The participants obtained high scores in kindness, responsibility, openness/intellect, and extraversion. Positive and statistically significant relations were found between neuroticism and mental workload. Being female, older, and having stable employment or a permanent contract were associated with a greater mental workload of emergency nurses.

CONCLUSION

The domain of neuroticism personality, and the hygienic conditions in the workplace were the predictors with the most weight in the model. This study could be useful for defining aspects that need to be considered for the well-being of emergency nurses, such as lighting conditions or environmental noise in the workplace. It also invites reflection on the influence of personal factors (age, gender, personality) and work factors (type of contract, professional experience) on the mental workload of emergency nurses.

Evaluating workload and manpower planning among pediatric emergency department nurses in Turkey during COVID-19: A cross-sectional, multicenter study

PURPOSE

Quality nursing care in pediatric emergency departments (PEDs) can be achieved only through sustained workload-based manpower planning. The purpose of this paper to evaluate perceptions of workload and manpower planning in the PED setting in Turkey from the nurses' point of view.

DESIGN AND METHODS

This cross-sectional, multicenter study that was conducted among 187 nurses working in a PED setting in Turkey between June and September 2021. Data were collected using a questionnaire that measured nurses' perceptions of workload and manpower planning. The reporting of this study adhered to STROBE guidelines.

RESULTS

The majority of the respondents perceived the number of patients-per-nurse during a shift to be too high, the number of nurses to be insufficient in proportion to the workload, and the nursing manpower-planning to be insufficient and biased. Those with ≤1 year of nursing experience in the PED perceived an increased workload and more burnout during the COVID-19 pandemic period.

CONCLUSIONS

Nurses working in PED setting perceived the workload and manpower planning to be inadequate. In addition, nurses who were less experienced or felt burnout perceived their workload to be increased during the COVID-19 pandemic.

PRACTICE IMPLICATIONS

Further exploration of workload and manpower planning in PEDs is required. Quantifying nurses' perspectives of workload and manpower when managing emergency pediatric patients is essential for designing appropriate interventions to improve the working environment. Future studies should focus on comparing nurses' perceptions with actual workloads and manpower planning in PEDs using appropriate measurement tools.

The effect of medical material management system app on nursing workload and stress

Aims

To develop a clinical medical material management App for nurses, in order to reduce their workload and improve the efficacy of medical material management.

Design

The single-group pre- and post-test experimental design was adopted.

Methods

The subjects were nurses in the intensive care units of a regional hospital in Hsinchu City enrolled by purposive sampling. Single-group pre-tests and post-tests were conducted. The research period was from November 2019 to March 2020. The workload, stress, and information acceptance of 57 nurses before and after the intervention of the Medical Equipment App were collected. The research tools included a structured questionnaire, which includes open questions that cover the aspects of workload, stress, and information acceptance intention of nurses, as well as a demographic questionnaire, which collects the basic personal data, including gender, age, years of service, educational level, nursing ability level, use ability of IT products, and unit type. The results were analyzed and compared using SPSS, APP Inventor, and data mining modeling to determine the effects of the App.

Results

After employing the Shift Check App, the average workload of nurses was effectively reduced, in particular, the workload reduction of the N1 level nursing ability was greater than that of N2. In addition to satisfaction, the scores of information acceptance intention in all aspects, including behavioral intention, technology use intention, and contributing factors, all increased.

Conclusion

The use of information technology products to assist medical material management in clinical practice has a significant effect on the load reduction of nurses and improvement of satisfaction.

Clinical relevance

The App developed in this study can improve nurses’ work satisfaction, quality of care and workload reduction.

Monitoring Diagnostic Safety Risks in Emergency Departments: Protocol for a Machine Learning Study

BACKGROUND

Diagnostic decision making, especially in emergency departments, is a highly complex cognitive process that involves uncertainty and susceptibility to errors. A combination of factors, including patient factors (eg, history, behaviors, complexity, and comorbidity), provider-care team factors (eg, cognitive load and information gathering and synthesis), and system factors (eg, health information technology, crowding, shift-based work, and interruptions) may contribute to diagnostic errors. Using electronic triggers to identify records of patients with certain patterns of care, such as escalation of care, has been useful to screen for diagnostic errors. Once errors are identified, sophisticated data analytics and machine learning techniques can be applied to existing electronic health record (EHR) data sets to shed light on potential risk factors influencing diagnostic decision making.

OBJECTIVE

This study aims to identify variables associated with diagnostic errors in emergency departments using large-scale EHR data and machine learning techniques.

METHODS

This study plans to use trigger algorithms within EHR data repositories to generate a large data set of records that are labeled trigger-positive or trigger-negative, depending on whether they meet certain criteria. Samples from both data sets will be validated using medical record reviews, upon which we expect to find a higher number of diagnostic safety events in the trigger-positive subset. Machine learning will be used to evaluate relationships between certain patient factors, provider-care team factors, and system-level risk factors and diagnostic safety signals in the statistically matched groups of trigger-positive and trigger-negative charts.

RESULTS

This federally funded study was approved by the institutional review board of 2 academic medical centers with affiliated community hospitals. Trigger queries are being developed at both organizations, and sample cohorts will be labeled using the triggers. Machine learning techniques such as association rule mining, chi-square automated interaction detection, and classification and regression trees will be used to discover important variables that could be incorporated within future clinical decision support systems to help identify and reduce risks that contribute to diagnostic errors.

CONCLUSIONS

The use of large EHR data sets and machine learning to investigate risk factors (related to the patient, provider-care team, and system-level) in the diagnostic process may help create future mechanisms for monitoring diagnostic safety.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/24642.

A person-centered perspective on the factors associated with the work recovery process

BACKGROUND AND OBJECTIVES

This research identified profiles characterized by distinct levels of overcommitment, rumination, psychological detachment (Studies 1 and 2), and need for recovery (Study 2). This research also considers the role of hindrance demands and resources in the prediction of profile membership, and the outcomes of these profiles.

METHODS

These objectives were addressed in two empirical cross-sectional studies relying on self-reported questionnaires. Study 1 relies on a convenience sample of French workers from a variety of occupations. Study 2 relies on a convenience sample of French nurses and nursing assistants.

RESULTS

Latent profile analyses revealed four identical profiles in both studies (High Ability to Achieve Recovery, Moderately High Ability to Achieve Recovery, Moderately Low Ability to Achieve Recovery, and Low Ability to Achieve Recovery), accompanied by an additional (Normative) profile in Study 2. The results from both studies revealed well-differentiated outcome associations, which generally matched the theoretical desirability of the identified profiles. Likewise, hindrance demands were associated with a decreased likelihood of membership into the High Ability to Achieve Recovery profile, as well as an increased likelihood of membership into the Low Ability to Achieve Recovery profile across studies.

CONCLUSIONS

Theoretical contributions and implications for practice are discussed.