The objective analysis of state of medical personnel, along with assessment of real need for specialists, is the basis of improving activities of any health care service. In relation to pathologists, there is unique opportunity to perform similar analysis, based on application of current corresponding staff standards that consider volume of workload of physicians in order to determine required number of positions. The implementation of corresponding original methodology permitted to establish that the actual number of staff positions of pathologists in 2022 amounted up to average 40.6% of the number required according to staffing standards in the Irkutsk Oblast. The physician staffing ratio, calculated on the basis of required number of positions found according to proposed methodology, decreases to 29.1% and staffing with physicians excluding combined jobs to 17.1%. At that, implemented workload per one pathologist reaches 5.9 of standard positions. The deficiency of representatives of this specialty in the region, even if current combined jobs ratio is maintained, is 154 specialists.

OBJECTIVE: To quantify the association between primary care team workload satisfaction and primary care physician (PCP) turnover and examine potential mediation of workplace climate factors using survey and administrative data.
METHODS: Longitudinal observational study using data from 2008 to 2016.
METHODS: The outcome variable was PCP turnover. The main explanatory variable was satisfaction with amount of workload. We included 7 additional workplace climate measures (eg, satisfaction with direct supervision) as mediators. We included characteristics of PCPs (eg, PCP years of experience, gender), salary, and clinic factors (eg, urban vs rural geography, community vs hospital based) as covariates.
RESULTS: US Department of Veterans Affairs (VA) PCPs working at 787 VA primary care clinics nationally were recruited for this study. Over the 9-year study period, 8362 unique PCPs were employed in the VA. The unadjusted mean quarterly turnover rate was 1.83%, and the mean (SD) workload satisfaction score was 3.58 ( 0.24) on a 5-point Likert scale over the study period. In adjusted analysis, a 1-point increase in workload satisfaction was associated with a decrease of 0.73 (95% CI, 0.36-1.10) percentage points in the probability of turnover in a calendar quarter. In the mediation analysis, we found that workload satisfaction impacted turnover through only 1 of the 7 workplace climate measures: satisfaction with direction by senior managers.
CONCLUSIONS: Our study findings highlight the key role that achieving primary care workload satisfaction can play in reducing PCP turnover. Identification of direction by senior managers as an underlying mechanism is an important finding for strategic planning to mitigate PCP turnover.

OBJECTIVE: To identify and present the available evidence regarding workforce well-being in the emergency department.
METHODS: Scoping review.
METHODS: The emergency department (ED).
METHODS: CINAHL, MEDLINE, APA PsycINFO and Web of Science were searched with no publication time parameters. The reference lists of articles selected for full-text review were also screened for additional papers.
METHODS: All peer-reviewed, empirical papers were included if: (1) participants included staff-based full-time in the ED, (2) ED workforce well-being was a key component of the research, (3) English language was available and (4) the main focus was not burnout or other mental illness-related variables.
RESULTS: The search identified 6109 papers and 34 papers were included in the review. Most papers used a quantitative or mixed methods survey design, with very limited evidence using in-depth qualitative methods to explore ED workforce well-being. Interventions accounted for 41% of reviewed studies. Findings highlighted pressing issues with ED workforce well-being, contributed to by a range of interpersonal, organisational and individual challenges (eg, high workloads, lack of support). However, the limited evidence base, tenuous conceptualisations and links to well-being in existing literature mean that the findings were neither consistent nor conclusive.
CONCLUSIONS: This scoping review highlights the need for more high-quality research to be conducted, particularly using qualitative methods and the development of a working definition of ED workforce well-being.

OBJECTIVE: to describe the development of a predictive nursing workload classifier model, using artificial intelligence.
METHODS: retrospective observational study, using secondary sources of electronic patient records, using machine learning. The convenience sample consisted of 43,871 assessments carried out by clinical nurses using the Perroca Patient Classification System, which served as the gold standard, and clinical data from the electronic medical records of 11,774 patients, which constituted the variables. In order to organize the data and carry out the analysis, the Dataiku® data science platform was used. Data analysis occurred in an exploratory, descriptive and predictive manner. The study was approved by the Ethics and Research Committee of the institution where the study was carried out.
RESULTS: the use of artificial intelligence enabled the development of the nursing workload assessment classifier model, identifying the variables that most contributed to its prediction. The algorithm correctly classified 72% of the variables and the area under the Receiver Operating Characteristic curve was 82%.
CONCLUSIONS: a predictive model was developed, demonstrating that it is possible to train algorithms with data from the patient\'s electronic medical record to predict the nursing workload and that artificial intelligence tools can be effective in automating this activity.

BACKGROUND: Nurses\' satisfaction has an impact on organizational and patient outcomes. Integrated care system in South Korea was established in 2015 to improve care quality and decrease caregiving burden. Since then, nurses\' satisfaction has increased due to an increase in nursing staffing. However, besides nurse staffing, various work environments still affect nurse satisfaction.
METHODS: Individual online surveys were conducted with participants to determine their personal characteristics, work environments, and hospital characteristics. We used mixed-effects linear regression equation contained both fixed and random effects.
RESULTS: This study included 2,913 nurses from 119 hospitals. Their average job satisfaction was less than 6 points out of 10 points. Age, shift type, perceived workload, and delegation criteria were significant factors influencing nurses\' satisfaction. There was no significant factor among hospital characteristics. The satisfaction level of nurses was high for no-night rotating shift, low perceived workload, and clear delegation criteria.
CONCLUSIONS: Nurses\' satisfaction is affected by several work environmental factors. Low nurse satisfaction has a substantial impact on both patients and nurses. Therefore, nurse managers and hospitals should determine factors influencing their satisfaction and develop strategies to improve their satisfaction.

Acute care surgery (ACS) encompasses five major pillars - trauma, surgical critical care, emergency general surgery, elective general surgery and surgical rescue. The specialty continues to evolve and due to high-acuity, high-volume and around-the-clock care, the workload can be significant leading to workforce challenges such as rightsizing of staff, work-life imbalance, surgeon burnout and more. To address these challenges and ensure a stable workforce, ACS as a specialty must be deliberate and thoughtful about how it manages workload and workforce going forward. In this article, we address the importance, benefits and challenges of defining full-time equivalence for ACS as a method to establish a stable ACS workforce for the future.

BACKGROUND: Triage is a dynamic process prioritising the patient coming to the emergency department. Caring behaviour and patient safety during the triage process are essential for ensuring a good care experience and treatment outcome.
OBJECTIVE: To describe triage nurses\' perceptions on caring behaviors and patient safety in the triage area.
METHODS: Strauss and Corbin\'s Grounded theory method was used to develop the model.
METHODS: The study was conducted in the emergency department in northeastern Slovenia. Semi-structured interviews were used for data collection, and 19 triage nurses were selected by theoretical sampling, guided by emerging categories between November 2021 and July 2022. The data analysis was conducted according to Strauss and Corbin\'s coding framework.
RESULTS: The analysis of the interviews generated one category: The process of creating a caring and safe triage encounter for the patient, together with two categories that explain the key phenomenon: (1) Triage caring and (2) Safety in the triage process. Within the category \"Triage caring\", four subcategories were developed: (1) Assurance of triage nurses\' presence, (2) Connectedness, (3) Respectful attitude, and (4) Knowledge and skills. The category Safety in the triage process consists of three identified subcategories: (1) Conception and perception of safety, (2) Factors influencing patient safety, and (3) Improving the triage safety.
CONCLUSIONS: The triage nurses\' perceptions about caring for the patient and his safety in the triage area show that caring and safety are inseparably linked and coincide when triaging a patient. Namely, caring for the patient means ensuring the patient\'s safety at the same time.
UNASSIGNED: A better understanding of the importance of triage nurses\' caring behavior and patient safety emerges from the findings, highlighting the challenges faced in a busy emergency department where nurses must balance providing care and responding to patients\' needs while ensuring safety. Findings in the study show that patient care and safety are inseparably linked and coincide when triaging a patient. Moreover, applying caring behaviour during triage encounter results in greater patient safety.
UNASSIGNED: The study\'s design, evaluation of the findings, and execution did not need the involvement of patients or the general public. Participants were triage nurses working in the emergency department. Triage nurses were interviewed about their perceptions of triage nurses on caring behaviors and patient safety during triage encounter.

OBJECTIVE: To examine differences in psychological detachment from work during nonwork time by nurses\' personal and work-related characteristics, and to examine the moderating and mediating effects of psychological detachment on the relationships between nursing workload and fatigue and sleep.
METHODS: This study employed a cross-sectional design with a self-administered online survey. Survey data from 827 hospital nurses providing direct patient care in the United States were used. Moderating and mediating effects of psychological detachment between workload and fatigue/sleep relationships were assessed using Hayes\' PROCESS macro in SPSS.
RESULTS: There were significant differences in psychological detachment from work based on age, highest nursing degree, work experience, shift length, weekly work hours, and frequency of providing care to patients with COVID-19. The associations of workload with physical fatigue, mental fatigue, and sleep quality were weakened when psychological detachment was high. Psychological detachment statistically mediated the associations between workload and fatigue and sleep problems.
CONCLUSIONS: Healthcare organizations are encouraged to facilitate nurses\' psychological detachment during time-off to protect them from fatigue and sleep problems.

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.
OBJECTIVE:  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.
CONCLUSIONS:  The study highlights the importance of SDOH and predicted ACG scores in predicting provider workload in primary care settings.

BACKGROUND: Public health emergencies of international concern (PHEICs) as the COVID-19 pandemic and others that have occurred since the early 2000s put enormous pressure on health and care systems. This is being a context for protests by health and care workers (HCWs) because of additional workload, working conditions and effects on mental and physical health. In this paper, we intended to analyze the demands of HCWs associated with industrial actions, protests, strikes and lockouts (IAPSLs) which occurred during COVID-19 pandemic and other PHEICs; to identify the impact of these grievances; and describe the relevant interventions to address these IAPSLs.
METHODS: We included studies published between January 2000 and March 2022 in PubMed, Embase, Scopus, BVS/LILACS, WHO\'s COVID-19 Research Database, ILO, OECD, HSRM, and Google Scholar for grey literature. Eligibility criteria were HCWs as participants, IAPSLs as phenomenon of interest occurring in the context of COVID-19 and other PHEICs. GRADE CERQual was used to assess risk of bias and confidence of evidence.
RESULTS: 1656 records were retrieved, and 91 were selected for full-text screening. We included 18 publications. A system-wide approach, rather than a limited approach to institutions on strike, makes it possible to understand the full impact of the strike on health and care services. PHEICs tend to aggravate already adverse working conditions of HCWs, acting as drivers for HCWs strikes, leading to staff shortages, and financial issues, both in the North and in the Global South, particularly evident in Asia and Africa. In addition, issues related to deficiencies in leadership and governance in heath sector and lack of medical products and technologies (e.g., lack of personal protective equipment) were the main drivers of strikes, each contributing 25% of the total drivers identified.
CONCLUSIONS: It is necessary to focus on the preparedness of health and care systems to respond adequately to PHEICs, and this includes being prepared for HCWs\' IAPSLs, talked much in the context of COVID-19 pandemic. Evidence to assist policymakers in defining strategies to respond adequately to the health and care needs of the population during IAPSLs is crucial. The main impact of strikes is on the disruption of health care services\' provision. Gender inequality being a major issue among HCWs, a proper understanding of the full impact of the strike on health and care services will only be possible if gender lens is combined with a systemic approach, rather than gender-undifferentiated approaches limited to the institutions on strike.