Hospital Doctors Research Articles

CEU 2023 Florence: an appointment with the future of the emergency system

The Academy of Emergency Medicine and Care is one of the more than 20 scientific societies promoting the 3rd National Congress of Emergency/Urgency (CEU2023), planned in Florence from March 30th to April 1st.1
 This will be a fundamental appointment for update on all clinical and organizing aspects of the Italian emergency system. More that 2500 people will participated to the CEU2023 meeting and courses with the possibility to attend more than 50 sessions with approximately 500 national and international speakers. This organization will ensure elevate quality of updating for specific themes by covering the point of view of hospital and pre-hospital medical doctors and nurses, emergency medicine trainees, but other professionals (drivers, rescuers, technicians, and volunteers). [...]

Hospital-wide survey of clinical experience with artificial intelligence applied to daily chest radiographs.

To assess experience with and perceptions of clinical application of artificial intelligence (AI) to chest radiographs among doctors in a single hospital. A hospital-wide online survey of the use of commercially available AI-based lesion detection software for chest radiographs was conducted with all clinicians and radiologists at our hospital in this prospective study. In our hospital, version 2 of the abovementioned software was utilized from March 2020 to February 2021 and could detect three types of lesions. Version 3 was utilized for chest radiographs by detecting nine types of lesions from March 2021. The participants of this survey answered questions on their own experience using AI-based software in daily practice. The questionnaires were composed of single choice, multiple choices, and scale bar questions. Answers were analyzed according to the clinicians and radiologists using paired t-test and the Wilcoxon rank-sum test. One hundred twenty-three doctors answered the survey, and 74% completed all questions. The proportion of individuals who utilized AI was higher among radiologists than clinicians (82.5% vs. 45.9%, p = 0.008). AI was perceived as being the most useful in the emergency room, and pneumothorax was considered the most valuable finding. Approximately 21% of clinicians and 16% of radiologists changed their own reading results after referring to AI, and trust levels for AI were 64.9% and 66.5%, respectively. Participants thought AI helped reduce reading times and reading requests. They answered that AI helped increase diagnostic accuracy and were more positive about AI after actual usage. Actual adaptation of AI for daily chest radiographs received overall positive feedback from clinicians and radiologists in this hospital-wide survey. Participating doctors preferred to use AI and regarded it more favorably after actual working with the AI-based software in daily clinical practice.

Digital Virtual Consultations and Improved Stakeholders’ Health and Wellbeing amongst Hospital Doctors

The past several decades have seen a shift in patient care towards digitalisation, which has ushered in a new era of health care delivery and improved sustainability and resilience of health systems, with positive impacts on both internal and external stakeholders. This study’s aim was to understand the role of digital virtual consultations in improving internal and external stakeholders’ health, as well as wellbeing among hospital doctors. A qualitative research approach was used with semi-structured online interviews administered to hospital doctors. The interviews showed that the doctors viewed digital virtual consultations as supplementary to in-person consultations, and as tools to reduce obstacles related to distance and time. If the necessary infrastructure and technology were in place, doctors would be willing to use these options. Implementing these technologies would improve the medical profession’s flexibility on the one hand; but it might affect doctors’ work–life balance if consultations extended beyond standard working hours.

A Survey Study on the Perception for Development of Integrated Medical Service Model and Its Application in Clinical Field - A Survey study with Doctors and Korean Medicine Doctors -

Objectives: Objectives: In this study, we define a medical service type that combines Western medicine, Korean medicine, and complementary and alternative medicine (CAM) as an integrated medical service. This study, as part of tertiary hospital-based integrated medical service model and clinical field application, aims to collect status and opinions on integrated medical service for medical staff in the field.Methods: This is a survey study, and was conducted on doctors from Kyung Hee University Hospital and Korean medicine doctors from Kyung Hee University Korean Medicine Hospital. Respondents were recruited on a first-come, first-served basis until the number of respondents reached 120. The investigation was conducted for a total of 16 days from October 4, 2021 to October 19, 2021 by e-mail.Results: Recognition of integrated medical services was confirmed to be 45.8%, and 49.2% responded positively to the necessity of it. As a group of diseases that require the establishment of integrated medical services in the future, 'disorders of musculoskeletal systems and connective tissues' was the highest. The most expected advantages of providing integrated medical services were 'increased satisfaction of patients and guardians' and 'increased treatment effects.’Conclusions: In this study, we investigated the perception of doctors and Korean medicine doctors on integrated medical services that combine Western medicine, Korean medicine, and CAM. It has been confirmed that medical staff generally have a positive perception of integrated medical services, and if the scientific basis for the effect of integrated medical services is supported, the rate of positive perception is expected to increase.

Prevalence and psychosocial profile of instagram addiction among Tunisian doctors

IntroductionInstagram is the most popular social media platform which is frequently used by population today. Besides, this subject has not been well discussed among doctors.ObjectivesTo study the prevalence of addiction to instagram among tunisian doctors and to identify its associated factors.MethodsThis was a cross-sectional descriptive study carried out among doctors (interns, residents and university hospital doctor) during the months of septembre and octobre 2022.A socio-demographic and clinical characteristics were collected using an online anonymous questionnaire from Google form that we distributed via facebook.Instagram Addiction Scale (IAS) was used to assess Instagram addiction levels. A score above 37 indicates addiction to instagram.ResultsOur sample included 106 patients. The mean age was 32.32 years (SD=5.66 years) and the sex ratio (M/F) was 0.60. More than half (56.6%) were married and lived with their husband. They were residents in 37% and they were using psychoactive substances in 42.5%.All of participants used other socialnetwork, the most used was facebook (63.2%).IAS : The mean score was 31.18 (SD=11.64). The prevalence of addiction to instagram was 42.5%.The instagram addiction was significantly correlated with : age (p=0,0001), the female gender (p=0.043), the celibacy (p=0.0001), the number of children (p=0.0001) and the number of siblings (p=0.049). Residents were more likely to develop an addiction to instagram (p=0.0001).ConclusionsThe study highlighted the high level of instagram addiction among tunisian doctors and identified individuals who were at higher risk. Specific interventions were necessary to deal with the problem of addiction.Disclosure of InterestNone Declared

Cognitive impairment and behavioural emergencies within the acute hospital setting

BackgroundPatients with cognitive impairment exhibiting agitation and aggression are challenging to manage in the acute hospital setting. When a patient’s behaviours place themselves or others at risk of harm, a...

Stroke intervention and pharmacotherapy guidelines: Knowledge-to-practice translation gaps among the emergency resident physicians in Riyadh, Saudi Arabia

Translating the updated medical guidelines into routine clinical practice is an important initiative to improve the population's health and decrease disease outcomes. A cross-sectional survey-based study was conducted in Riyadh City, Saudi Arabia, to evaluate the knowledge and degree of application (practice) of the stroke management guidelines among emergency resident physicians. An interview-based self-administered questionnaire was used to survey the emergency resident doctors in Riyadh hospitals from May 2019 to January 2020. Of 129 participants, 78 valid, complete responses were obtained (60.5% response rate). Descriptive statistics, principle component, and correlation analyses were used. Most resident doctors were men(69.4%) with a mean age of 28.4±3.37 years. More than 60% of the residents were satisfied with their knowledge of the stroke guidelines; meanwhile, 46.2% were satisfied with their application of the guidelines. Both Knowledge and practice compliance components were significantly and positively correlated. Also, both components were significantly correlated with being updated, aware of, and strictly following these guidelines. The mini-test challenge showed a negative result with a mean knowledge score of 1.03±0.88. Even though the majority of participants utilized different tools of education and were aware of the American Stroke Association Guidelines. It was concluded that a considerable gap in the residents’ knowledge regarding the current stroke management guidelines was present in Saudi hospitals. Also, it was reflected on their actual implementation and application into clinical practice. Continuous medical education, training, and follow-up of the emergency resident doctors, administered as a part of the government health programs, are crucial to improve the health care delivery for acute stroke patients.

Working Motivation of Doctors: The Case of Public Hospitals in Hanoi

This study was conducted to identify, evaluate and measure the attributes of working motivation of doctors in public hospitals in Hanoi. Based on literature review and the results of some interviews, 225 questionnaires were sent to doctors in public hospitals in Hanoi and were collected in 2 months. However, only 212 questionnaires were satisfactory and included in the analysis. The results of descriptive statistics, Cronbach’s Alpha analysis, Independent T-test and ANOVA have identified and measured 3 attributes of working motivation which effect on doctors in public hospitals in Hanoi. Based on the findings, some recommendations are given for doctors and public hospitals in Hanoi to improve the working motivation of doctocrs. The research has brought practical significance to hospital administrators in public hospitals, who need solutions and policies for improving doctors’ performance.

Ten simple rules for providing bioinformatics support within a hospital

Bioinformatics has become a key aspect of the biomedical research programmes of many hospitals’ scientific centres, and the establishment of bioinformatics facilities within hospitals has become a common practice worldwide. Bioinformaticians working in these facilities provide computational biology support to medical doctors and principal investigators who are daily dealing with data of patients to analyze. These bioinformatics analysts, although pivotal, usually do not receive formal training for this job. We therefore propose these ten simple rules to guide these bioinformaticians in their work: ten pieces of advice on how to provide bioinformatics support to medical doctors in hospitals. We believe these simple rules can help bioinformatics facility analysts in producing better scientific results and work in a serene and fruitful environment.

Optimal Hospital Care Scheduling During the SARS-CoV-2 Pandemic

The COVID-19 pandemic has seen dramatic demand surges for hospital care that have placed a severe strain on health systems worldwide. As a result, policy makers are faced with the challenge of managing scarce hospital capacity to reduce the backlog of non-COVID patients while maintaining the ability to respond to any potential future increases in demand for COVID care. In this paper, we propose a nationwide prioritization scheme that models each individual patient as a dynamic program whose states encode the patient’s health and treatment condition, whose actions describe the available treatment options, whose transition probabilities characterize the stochastic evolution of the patient’s health, and whose rewards encode the contribution to the overall objectives of the health system. The individual patients’ dynamic programs are coupled through constraints on the available resources, such as hospital beds, doctors, and nurses. We show that the overall problem can be modeled as a grouped weakly coupled dynamic program for which we determine near-optimal solutions through a fluid approximation. Our case study for the National Health Service in England shows how years of life can be gained by prioritizing specific disease types over COVID patients, such as injury and poisoning, diseases of the respiratory system, diseases of the circulatory system, diseases of the digestive system, and cancer. This paper was accepted by Chung-Piaw Teo, optimization. Funding: G. Forchini acknowledges funding from Jan Wallanders and Tom Hedelius Foundation and the Tore Browaldh Foundation, funding from MRC Centre for Global Infectious Disease Analysis [Reference MR/R015600/1], jointly funded by the UK Medical Research Council (MRC) and the UK Foreign, Commonwealth and Development Office (FCDO), under the MRC/FCDO Concordat agreement, part of the EDCTP2 program supported by the European Union; and acknowledges funding by Community Jameel. D. Rizmie acknowledges partial funding from the MRC Centre for Global Infectious Disease Analysis [Reference MR/R015600/1]. J. C. D’Aeth acknowledges funding from the Wellcome Trust [Reference 102169/Z/13/Z]. S. Moret acknowledges partial support from the Swiss National Science Foundation (SNSF) under [Grant P2ELP2_188028]. S. Ghosal was funded by the Imperial College President’s PhD Scholarship. F. Grimm was funded by the Health Foundation as part of core staff member activity. This research was funded in whole, or in part, by the Wellcome Trust [Grant 102169/Z/13/Z]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4679 .

Evaluation of rural general practice experiences for pre-vocational medical graduates.

Despite substantial investment in rural workforce support, sustaining the necessary recruitment and retention of general practitioners (GPs) in rural areas remains a challenge. Insufficient medical graduates are choosing a general/rural practice career. Medical training at postgraduate level, particularly for those 'between' undergraduate medical education and specialty training, remains strongly reliant on hospital experience in larger hospitals, potentially diverting interest away from general/rural practice. The Rural Junior Doctor Training Innovation Fund (RJDTIF) program offered junior hospital doctors (interns) an experience of 10 weeks in a rural general practice, aiming to increase their consideration of general/rural practice careers This study aimed to evaluate the educational and potential workforce impact of the RJDTIF program. Up to 110 places were established during 2019-2020 for Queensland's interns to undertake an 8-12-week rotation (depending on individual hospital rosters) out of regional hospitals to work in a rural general practice. Participants were surveyed before and after the placement, although only 86 were invited due to the disruption caused by the COVID-19 pandemic. Descriptive quantitative statistics were applied to the survey data. Four semi-structured interviews were conducted to further explore the experiences post-placement, with audio-recordings transcribed verbatim. Semi-structured interview data were analysed using inductive, reflexive thematic analysis. In total, 60 interns completed either survey, although only 25 were matched as completing both surveys. About half (48%) indicated they had preferenced the rural GP term and 48% indicated strong enthusiasm for the experience. General practice was indicated as the most likely career option for 50%, other general specialty 28% and subspecialty 22%. Likelihood to be working in a regional/rural location in 10 years was indicated as 'likely' or 'very likely' for 40%, 'unlikely' for 24% and 'unsure' for 36%. The two most common reasons for preferencing a rural GP term were experiencing training in a primary care setting (50%) and gaining more clinical skills through increased patient exposure (22%). The overall impact on pursuing a primary care career was self-assessed as much more likely by 41%, but much less by 15%. Interest in a rural location was less influenced. Those rating the term poor or average had low pre-placement enthusiasm for the term. The qualitative analysis of interview data produced two themes: importance of the rural GP term for interns (hands-on learning, skills improvement, influence on future career choice and engagement with the local community), and potential improvements to rural intern GP rotations. Most participants reported a positive experience from their rural GP rotation, which was recognised as a sound learning experience at an important time with respect to choosing a specialty. Despite the challenges posed by the pandemic, this evidence supports the investment in programs that provide opportunities for junior doctors to experience rural general practice in these formative postgraduate years to stimulate interest in this much-needed career pathway. Focusing resources on those who have at least some interest and enthusiasm may improve its workforce impact.

Intersectoral management of patients with abnormal liver enzymes and non-alcoholic fatty liver disease (NAFLD)

The prevalence of fatty liver disease has increased significantly in Germany in recent years. With an estimated 18 million German citizens being affected, it is now among the most prevalent diseases. Furthermore, it is also considered a relevant and independent risk factor for other common cardiovascular diseases such as heart attack or stroke. Finally, diabetes mellitus promotes the development of and an unfavorable course of fatty liver disease. Given the high prevalence and complications, the German healthcare system is reaching its limits.Therefore, close coordination of all healthcare providers and specialists involved in the treatment of these patients is essential. In an expert consensus involving private practice and hospital doctors from the fields of gastroenterology, endocrinology, cardiology, general practitioners and laboratory physicians, as well as in close coordination with patient representatives, we have designed a concept for the care of these patients in the German healthcare system. Necessary developments are also addressed. In addition to being useful as a practical guideline, this should also support health policy work, especially in the development of practical care solutions at the medical level.

AIMDP: An Artificial Intelligence Modern Data Platform. Use case for Spanish national health service data silo

The huge amount of data being handled today in any environment, such as energy, economics or healthcare, makes data management systems key to extracting information, analysing and creating more efficient daily processes in these environments. However, the inability of current systems to take advantage of the data generated can waste good opportunities for analysing and extracting information from the data. Modern data platforms (MDP) appear suitable for supporting management systems and are able to perform future prospective analyses. This paper presents a data platform called Artificial Intelligence Modern Data Platform (AIMDP), based on Big Data, artificial intelligence for management, and efficient data handling. The different components of AIMDP intervene in the data acquisition phase and implement algorithms capable of analysing massive data collected from heterogeneous sources. In addition, the entire platform is geared towards data management and exploitation with a layer of security and data governance that allows the integrity and privacy of the databases to be maintained. The proposed platform is designed to be used by users who are not experts in data science. To this end, it implements a user-oriented workflow that has effectively been introduced in a use case of two Spanish hospitals to extract knowledge from their historical data, which had been siloed and had never been explored by any hospital researchers or doctors.

The Effect of Supportive Care Environment on the Treatment Process in Hospitals: A Qualitative Study

Objectives: According to the available evidence, changes in the design of medical centers, which can create a more comfortable, pleasant, and natural environment, have reduced the patient tensions and increased their satisfaction with the quality of treatment in the given centers. The present study aimed to investigate the effect of the architecture and design of a supportive care environment on the treatment process in hospitals adopting a qualitative study design. Materials and Methods: This qualitative study with a phenomenological approach was conducted to investigate the effect of an optimal supportive care environment in hospitals based on the experiences and opinions of experts, university professors of architecture, and doctors in hospitals. To this end, experts were interviewed qualitatively and, then, eight main themes as well as 22 sub-themes were classified by performing content analysis. Furthermore, the effect of the environment on the patients, treatment control length, blood pressure control, and subjective nature of the disease’s impact, as well as the effect of social relations on the vital signs, comprehensiveness and acceptability, place of using the supportive care model and a completely mechanical attitude towards humans in the modern period were all evaluated. Results: The effect of the optimal supportive care environment on the patients’ treatment processes was confirmed by qualitatively reviewing the experts’ viewpoints and collecting comprehensive information from other sources. Conclusions: In sum, it was recommended that that the heads of the hospitals should consider the concepts of optimal supportive care environment when designing and/or reconstructing hospitals.

Interpretable Differential Diagnosis of Non-COVID Viral Pneumonia, Lung Opacity and COVID-19 Using Tuned Transfer Learning and Explainable AI.

The coronavirus epidemic has spread to virtually every country on the globe, inflicting enormous health, financial, and emotional devastation, as well as the collapse of healthcare systems in some countries. Any automated COVID detection system that allows for fast detection of the COVID-19 infection might be highly beneficial to the healthcare service and people around the world. Molecular or antigen testing along with radiology X-ray imaging is now utilized in clinics to diagnose COVID-19. Nonetheless, due to a spike in coronavirus and hospital doctors' overwhelming workload, developing an AI-based auto-COVID detection system with high accuracy has become imperative. On X-ray images, the diagnosis of COVID-19, non-COVID-19 non-COVID viral pneumonia, and other lung opacity can be challenging. This research utilized artificial intelligence (AI) to deliver high-accuracy automated COVID-19 detection from normal chest X-ray images. Further, this study extended to differentiate COVID-19 from normal, lung opacity and non-COVID viral pneumonia images. We have employed three distinct pre-trained models that are Xception, VGG19, and ResNet50 on a benchmark dataset of 21,165 X-ray images. Initially, we formulated the COVID-19 detection problem as a binary classification problem to classify COVID-19 from normal X-ray images and gained 97.5%, 97.5%, and 93.3% accuracy for Xception, VGG19, and ResNet50 respectively. Later we focused on developing an efficient model for multi-class classification and gained an accuracy of 75% for ResNet50, 92% for VGG19, and finally 93% for Xception. Although Xception and VGG19's performances were identical, Xception proved to be more efficient with its higher precision, recall, and f-1 scores. Finally, we have employed Explainable AI on each of our utilized model which adds interpretability to our study. Furthermore, we have conducted a comprehensive comparison of the model's explanations and the study revealed that Xception is more precise in indicating the actual features that are responsible for a model's predictions.This addition of explainable AI will benefit the medical professionals greatly as they will get to visualize how a model makes its prediction and won't have to trust our developed machine-learning models blindly.

1324 DEVELOPMENT OF A M&M MEETING INTEGRATING THE SITUATIONAL JUDGEMENT REVIEW (SJR) FRAMEWORK IN A GERIATRIC DEPARTMENT

Abstract Introduction The National Mortality Case Record Review Programme commissioned in 2016 aimed to improve the learning from deaths process. As part of this aim, several reports were published, which identified barriers in implementing the mortality review process. Mortality and Morbidity (M&M) meetings can be an important mechanism for removing these barriers, and while have been in place for a long time in surgical specialties, are only recently becoming more common in medical specialties. We have developed an innovative M&M meeting in our geriatric department to integrate Mortality case reviews with teaching and QI development. Methods We created a standardised mortality data collection proforma, using the (SJR) framework as a template. During the development, feedback was obtained from consultants and juniors. Data was then collected using the proforma by trainees, and all mortality cases were then reviewed with consultant supervision, and specific cases were chosen for their educational benefit or requiring areas of improvement. Cases were then presented at the meeting. At the end of the meetings, an action plan was then created in collaboration with the consultant and juniors in the meeting to create a teaching plan or develop a QI project to help improve service. Results From feedback gained, the M&M was well received, and has already helped improve training and delivery of end of life care and recognising the dying patient. There were several difficulties identified during the process such as incomplete medical records, time and lack of engagement from other team members due to work pressures. Conclusion Mortality meetings are an essential part of junior doctor training and hospital clinical governance, often times underutilised. They can support quality improvement and professional learning, especially when facilitated by a standardised mortality review process.

Investigation on the Needs of Obstetricians & Gynecologists in Different Types of Hospitals for the Content and Forms of Continuing Medical Education and Training

Background: Medicine is to some extent an empirical science that requires repeated clinical practice. To explore the needs of obstetricians & gynecologists (Ob & Gy) in different kinds of hospitals for continuing medical education (CME) training content and forms. Method: From April 2020 to May 2020, an online questionnaire was distributed on the largest academic training platform for Ob & Gy in China, which included doctors’ mastery of diseases, training content and forms of CME. Results: A total of 4458 questionnaires were returned, of which 3954 were included in the study. There is a significant statistical difference between doctors in general hospitals, maternity specialized hospitals, or maternity and child specialized hospitals in the mastery of most common gynecological and obstetric diseases, among which, doctors in general hospitals have a better mastery (p < 0.001). Generally, doctors in different types of hospitals have a lower mastery of gynecological endocrine-related diseases; doctors in general hospitals have a better mastery of abnormal uterine bleeding (Exp 1.25, 95% Confidence Interval (CI) 1.09~1.44, p = 0.00), and doctors in specialized hospitals are better at infertility and precocious puberty/delayed pubertal development (p = 0.00). The preferred professional direction and training for doctors in different types of hospitals were to strengthen the knowledge of gynecological endocrine diseases through online teaching. Conclusions: Doctors in different types of hospitals generally have lower mastery of gynecological endocrine-related diseases, and doctors in general hospitals have a better mastery of common gynecological and obstetric diseases than those in specialized hospitals. The training content with the greatest need focuses on common gynecological endocrine-related diseases. Online teaching is the most popular educational model.

Decision making capacity assessment in general practice in Ireland.

It has been reported internationally that doctors have a limited understanding of the legal standard that applies to decision making capacity (DMC). No research on this has been conducted in Ireland to date. We sought to assess the understanding of legal principles relating to capacity and consent among Irish general practitioners (GPs), alongside how DMC assessments are conducted. This study utilised a cross-sectional cohort model circulating online questionnaires to Irish GPs associated with a university research network. Data were analysed using SPSS to conduct a variety of statistical tests. There were 64 participants, with 50% aged 35-44 years and 60.9% being female. Of these, 62.5% found DMC assessments time-consuming. Only 10.9% of participants felt extremely confident in their abilities; most participants (59.4%) felt 'somewhat confident' in their ability to assess DMC. Also, 90.6% of GPs routinely engaged with families when assessing capacity. GPs felt their medical training did not prepare them for DMC assessment (undergraduate 90.6%, non-consultant hospital doctor 78.1%, GP training 65.6%). 70.3% felt guidelines relating to DMC would be helpful and 65.6% felt they needed additional training. Most GPs recognise the importance of DMC assessment, and it is not considered a complex or burdensome task. There was limited knowledge of the legal instruments relevant to DMC. GPs felt there should be extra support available to assist them with DMC assessment; specific guidelines for different categories of patients was found to be the most popular resource requested.

Patient Identification Errors in the Hospital Setting: A Prospective Observational Study

Background and aim: In every aspect of clinical care, including diagnostic testing and medication administration, patient identification (ID) errors can disrupt care and harm patients. The study assesses healthcare workers' frequency and accuracy in verifying patient identity before performing common tasks and develops a proposed patient verifying identity program clinical model to meet the training needs of healthcare workers. Methods: An observational cross-sectional study was conducted at Al-Najaf Teaching Hospital from March to May 2022. Data collection was done through a questionnaire and participatory observation. Hundred-forty healthcare workers participated in the study: 52 clinic doctors, 27 registered nurses, 34 information officers, 17 pharmacists, 4 radiologists, and 6 outpatient hospital doctors. Results: The majority of participants (62.1%) were female. The majority of the 40 participants (28.6%) worked in the operating room. Furthermore, the majority of the participants (82.1%) did not ask the patients for their names and dates of birth (DOB). Clinic doctors made up the majority of those who did not complete the identification process (37.1%). Conclusion: More than three-quarters of healthcare workers missed patient identification while performing a task. Although patient identification errors frequently result in serious adverse events that can be avoided with better training, better use of technology may improve the way healthcare workers verify patients' identities.

Key determinates of job satisfaction for acute care nurse practitioners in Taiwan

BackgroundTaiwan is a super-aged society, and the shortage of hospital doctors; nurse practitioners (NPs) became vital healthcare providers to fulfill the healthcare demands of the population. The purpose of this study was to explore the key determinates of job satisfaction for NPs in acute care practices using significant practice variables, such as empowerment and burnout.MethodsParticipants of this descriptive survey study were recruited from a national sample of NPs with membership in the Taiwan Association of Nurse Practitioners. The data were collected utilizing an online questionnaire based on demographic and practice variables, the Misener Nurse Practitioner Job Satisfaction Scale (MNPJSS), the Condition for Work Effectiveness Questionnaire II (CWEQ II), and the Copenhagen Burnout Inventory (CBI). A total of 1,211 NPs completed the online survey. A multiple regression model with the stepwise selection was used to explore job satisfaction.ResultsThe mean overall satisfaction score indicated that the level of satisfaction was between slightly dissatisfied and slightly satisfied. Regression results indicated that formal power, work-related burnout, access to information, and needed resources were critical components of job satisfaction, and accounted for 63% of the variance. Moreover, NPs who were married, had a higher annual salary, worked only during the day shift, and had lower patients-related burnout showed better job satisfaction.ConclusionsThis study provides evidence for healthcare organizations to formulate policies to strengthen NP job satisfaction. Empowerment and burnout are vital factors in NPs’ job satisfaction. Healthcare organizations have an obligation to implement policies to empower NPs in practice and provide interventions to mitigate burnout. Implementing these changes will improve job satisfaction and with it the quality of patient care.