Skills Of Medical Staff Research Articles

A Novel Computer-Aided Approach for Predicting COVID-19 Severity Using Hyperparameters in ResNet50v2 from X-ray Images

This research has been globally impacted by COVID-19 virus, which was a very uncommon, highly contagious & dangerous respiratory illness demanding early detection for effective containment and further spread. In this research, we proposed an innovative methodology that utilizes images of X-rays for COVID-19 detection at an early stage. By employing a convolution neural network, we enhance the accuracy performance via using ResNet50v2 using a hyperparameter. The methodology achieves a remarkable accuracy with an average accuracy of 99.12%. This accuracy surpasses other available models based on different deep learning models like VGG, Xception and DenseNet for COVID identification & detection with the help of X-ray images. X-ray scans are now preferably used modality for the identification & detection of COVID-19, given its widespread utilization and effectiveness. However, manual treatment & examination using X-ray images is very challenging, specifically in the field which is facing a limitation of skilled medical staff. Utilization of deep learning models has demonstrated significant potential and effective results in automating the diagnosis for timely identification of COVID with the help of X-ray films. The suggested architecture is specifically developed for timely prediction and analysis of COVID cases employing X-ray films. It firmly believes that this study holds significant potential in alleviating the workload of frontline radiologists, expediting patient diagnosis and treatment, and facilitating pandemic control efforts.

Prompt engineering for digital mental health: a short review.

Prompt engineering, the process of arranging input or prompts given to a large language model to guide it in producing desired outputs, is an emerging field of research that shapes how these models understand tasks, process information, and generate responses in a wide range of natural language processing (NLP) applications. Digital mental health, on the other hand, is becoming increasingly important for several reasons including early detection and intervention, and to mitigate limited availability of highly skilled medical staff for clinical diagnosis. This short review outlines the latest advances in prompt engineering in the field of NLP for digital mental health. To our knowledge, this review is the first attempt to discuss the latest prompt engineering types, methods, and tasks that are used in digital mental health applications. We discuss three types of digital mental health tasks: classification, generation, and question answering. To conclude, we discuss the challenges, limitations, ethical considerations, and future directions in prompt engineering for digital mental health. We believe that this short review contributes a useful point of departure for future research in prompt engineering for digital mental health.

Enhancing Efficiency, Improving Care: Exploring Patient Opinions on Hospital Social Work

Purpose: This study investigates patient perceptions of factors influencing the efficiency of hospital social work services. Specifically, it explores the perceived role of social workers in addressing patients' psychosocial needs and identifies potential strategies for enhancing service efficiency. By understanding the patient perspective, this research aims to illuminate the impact of various factors on social work effectiveness and ultimately contribute to improved patient care delivery. Methods: A convenience sampling technique was employed to recruit 130 patients from Trung Vuong Hospital who participated in a self-administered survey assessing their perspectives on hospital social work services. The survey comprised two scales: one evaluating factors affecting social work efficiency and another proposing measures for improvement. Descriptive statistics were utilized for data analysis. Results: Patient perceptions identified "patient needs" and "knowledge and skills of medical staff, doctors, and social workers" as the most critical factors impacting hospital social work efficiency. This underscores the importance of ongoing professional development for social workers and ensuring adequate staffing levels. Proposed strategies for improvement included: enhanced professional training for social workers, fostering effective communication regarding social work services available to patients, and the expansion of external resource networks to provide comprehensive support for patients facing complex challenges. Conclusion: This study sheds light on critical areas for optimizing hospital social work efficiency, highlighting the importance of strategic staffing decisions, fostering interdisciplinary collaboration, and prioritizing continuous professional development for social workers. By integrating patient feedback into service delivery models, social work departments can enhance patient support and contribute to improved healthcare outcomes. Future research efforts should strive for broader generalizability by incorporating diverse healthcare settings and soliciting the perspectives of a wider range of stakeholders. This will provide a more comprehensive understanding of social work effectiveness in the evolving landscape of healthcare delivery.

Global Workforce Solutions for Supporting the UK NHS

BTA programs have supported significant cost savings for organisations in reducing agency locum spending which then can be spent on patient care or further workforce development. Gains to the organisations include highly skilled medical staff who can meet the needs of various communities and current and future healthcare needs. These doctors with either postgraduate qualifications or through the in-house 2-year training program (2+2) enter relevant clinical specialities providing high-quality patient care.

Predictors of hospital length of stay and mortality among COVID-19 inpatients during 2020-2021 in Hormozgan Province of Iran: A retrospective cohort study.

About one-fifthof patients with COVID-19 need to be hospitalized. Predicting factors affecting the hospital length of stay (LOS) can be effective in prioritizing patients, planning for services, and preventing the increase in LOS and death of patients. The present study aimed to identify the factors that predict LOS and mortality in COVID-19 patients in a retrospective cohort study. A total of 27,859 patients were admitted to 22 hospitals from February 20, 2020to June 21, 2021. The data collected from 12,454 patients were screened according to the inclusion and exclusion criteria. The data were captured from the MCMC (Medical Care Monitoring Center) database. The study tracked patients until their hospital discharge or death. Hospital LOS and mortality were assessed as the study outcomes. As the results revealed, 50.8% of patients were male and 49.2% were female. The mean hospital LOS of the discharged patients was 4.94. Yet, 9.1% of the patients (n = 1133) died. Among the predictors of mortality and long hospital LOS were the age above 60, admission to the ICU, coughs, respiratory distress, intubation, oxygen level less than 93%, cigarette and drug abuse, and a history of chronic diseases. Masculinity, gastrointestinal symptoms, and cancer were the effective variables in mortality, and positive CT was a factor significantly affecting the hospital LOS. Paying special attention to high-risk patients and modifiable risk factors such as heart disease, liver disease, and other chronic diseases can diminish the complications and mortality rate of COVID-19. Providing training, especially for those who care for patients experiencing respiratory distress such as nurses and operating room personnel can improve the qualifications and skills of medical staff. Also, ensuring the availability of sufficient supply of medical equipment is strongly recommended.

Maternal mortality is preventable in Lebanon: A case series of maternal deaths to identify lessons learned using the "Three Delays" model.

To identify the lessons learned from women who died during pregnancy or childbirth in Lebanon between 2018 and 2020. This is a case series and synthesis of maternal deaths between 2018 and 2020 that were reported by healthcare facilities to the Ministry of Public Health in Lebanon. The notes recorded from the maternal mortality review reports were analyzed using the "Three Delays" model to identify preventable causes and lessons learned. A total of 49 women died before, during, or after childbirth, with hemorrhage being the most frequent cause (n = 16). The possible factors that would have prevented maternal deathsincluded a prompt recognition of clinical severity, availability of blood for transfusion and magnesium sulfate for eclampsia, adequate transfer to tertiary care hospitals comprising specialist care, and involvement of skilled medical staff in obstetric emergencies. Many maternal deaths in Lebanon are preventable. Better risk assessment, use of an obstetric warning system, access to adequately skilled human resources and medications, and improved communication and transfer mechanisms between private and tertiary care hospitals may avoid future maternal deaths.

A comparative study of positive and negative electronic word-of-mouth on the SERVQUAL scale during the COVID-19 epidemic - taking a regional teaching hospital in Taiwan as an example

BackgroundIn recent years, studies have shown that electronic WOM (eWOM) directly reflects consumers’ post-purchase psychological perception and directly affects repurchase behavior. This information is valued by institutions in various fields. Within the scope of the evaluation of service characteristics, medical service is the least visible and most difficult service attribute to evaluate. Service organizations must have high trust attributes. Therefore, an eWOM review significantly influences people’s decision-making process when choosing a healthcare provider. The purpose of this research is to combine eWOM reviews with the SERVQUAL scale in a comparative study of positive and negative eWOM reviews of a regional teaching hospital in Taiwan.MethodsThis research obtained data from publicly available eWOM reviews on Google Maps of a regional teaching hospital in Taiwan over the past 10 years (from June 24, 2011, to December 31, 2021) using website scraping technology. The semantic content analysis method was used in this study to classify eWOM reviews according to the revised PZB SERVQUAL scale.ResultsStatistical analysis was conducted. During the COVID-19 pandemic, positive reviews showed a downward trend. Among the five determinants of the SERVQUAL of PZB, positive eWOM reviews performed best in “assurance” with a positive review rate of 60.00%, followed by 42.11% for “reliability”. For negative eWOM reviews, “assurance” performed the worst with a positive rate of 72.34%, followed by “responsiveness” at 28.37% and “reliability” at 26.95%.ConclusionSince the onset of COVID-19 in 2020, negative eWOM has increased significantly and exceeded the amount of positive eWOM. Regardless of positive and negative reviews, what patients care most about is “assurance” of the professional attitude and skills of medical staff, which urgently needs to be strengthened. In addition, good “reliability” will help to develop positive eWOM. However, “responsiveness” as indicated by poor service waiting time can easily lead to the spread of negative eWOM. Hospital management should focus on these service-oriented qualities.

Psychological characteristics of Japanese patients and their family members receiving genetic counseling: A single-institute exploratory study.

In Japan, clinical genetic services became available in the 1970s, and genomic medicine, including genetic counseling (GC), developed rapidly. However, research on the outcomes of GC in Japan is limited. Japan has a unique cultural context, and appropriate GC methods have not yet been optimized for this population. The current study aimed to evaluate the psychological status of Japanese patients and their companions undergoing GC and the outcomes of GC. We used the Quality of Care Through the Patients' Eyes-gene cancer (QUOTE-geneCA ), the Genetic Counseling Outcome Scale-24 (GCOS-24), and the State-Trait Anxiety Inventory (STAI) to evaluate patients and their companions' needs and preferences regarding GC, empowerment, and anxiety, respectively. We evaluated stress status during GC by measuring saliva cortisol levels. QUOTE-geneCA results for patients (n= 69) and a group of patients and their companions (n= 96) revealed that participants felt that it was important that skilled medical staff explained medical information and provided advice in an easily understandable manner. Japanese patients and their companions regarded the procedural aspects of counseling as most important and their autonomy in decision-making as less important. GCOS-24 results revealed a significant increase in empowerment scores in 38 patients (by 9.63 points) from pre- to post-GC (p< 0.001; Cohen's d=0.79). STAI results revealed a significant decrease in state anxiety for patients (6.11 points; p< 0.001; Cohen's d=0.66). Cortisol levels in patients significantly decreased after GC (p= 0.001). The improvement of empowerment scores from pre- to post-GC among patients and their companions were significantly negatively correlated with pre-GC empowerment scores (p< 0.001), trait anxiety scores (p= 0.001), and the number of people living together (p= 0.011). The change of cortisol levels during GC in patients and their companions was significantly positively correlated with trait anxiety score (p= 0.027). This study suggested that these characteristics of Japanese patients and their companions may predict GC outcomes.

Challenges of paediatric palliative care in Romania: a focus groups study

BackgroundThe availability of palliative care facilities for children vary considerably among the European member states. In Romania, a country where health expenditure is among the lowest in Europe, palliative care has been mainly provided by charitable organizations. Despite the high number of children needing palliative care, there is scant literature and research available on paediatric palliative care in Romania. The study explores the viewpoints of various paediatric oncology providers with regard to paediatric palliative care provision in Romania.MethodsFour mixed focus groups were conducted at four university-affiliated paediatric oncology centres located in three distinct Romanian regions (Bucuresti-llfov, Nord-Est and Nord-Vest). The focus groups were analyzed using thematic coding.ResultsFor many healthcare professionals, emotional burden inherent to the profession; unhealthy work-life balance and understaffing were among the biggest barriers to the successful integration of pediatric palliative care. The lack of staff was attributed to a shortage of financial resources, and to the persisting cultural stigma surrounding palliative care and oncology. Also political turmoil was identified as an important obstacle to palliative care implementation.ConclusionSignificant barriers persist limiting the broader implementation of pediatric palliative care in Romania. In order to render palliative care in pediatric oncology more sustainable, more attention should be paid to the mental health care of healthcare professionals working in this field, to the development of mobile palliative care services and to the emigration of skilled medical staff.

Research of Ionic, Molecular and Cellular Mechanisms for Formation of Electric Impedance in Biological Fluids and Tissues

Contemporary medicine applies the analysis of molecular composition and physicochemical properties of biological fluids as one of the main tools for diagnostics and control over body state and behaviour of pathological processes. However, most laboratory diagnostics methods (such as biochemical, enzyme-linked immunosorbent assay, etc.) are too expensive and time-consuming. They demand the availability of well-equipped laboratories, complex equipment, scarce and expensive reactants and materials and the highly skilled medical staff. Compared to them, bioimpedansometry is an incomparably simpler and cheaper method of laboratory research, becoming increasingly popular for diagnosing internal diseases. In the current research the main physical factors responsible for bioelectrical impedance variations in some conductive intracellular and extracellular biological fluids with different protein molecules, cell components and microbes were studied experimentally. The original laboratory impedance meter was developed for investigation of blood or interstitial biological fluids as well as condensates composition in orderto determine the concentration of organic substances in them and the rate of biochemical and immune reactions.

COVID-CNNnet: Convolutional Neural Network for Coronavirus Detection

The coronavirus disease (COVID-19) is the most recent severe diseases that has spread globally at an exponential rate. During this crisis, any technological approach that allows highly precise early detection of COVID-19 infection will save many lives. The main clinical technique for COVID-19 recognition is the reverse transcription polymerase chain reaction (RT-PCR). However, the RT-PCR testing tool is time-consuming, inaccurate and requires skilled medical staff. Therefore, auxiliary diagnostic tools should be developed to stop the spread of COVID-19 amongst people. Chest X-ray imaging is a readily available method that able to serve as an extremely good alternative for RT-PCR in identifying patients with COVID-19 diseases because it provides salient COVID-19 virus information. In this study, the COVID-CNNnet model proposed based on a convolutional neural network (CNN) deep learning (DL) algorithm, to detect COVID-19 cases rapidly and accurately based on patient chest X-ray images. The proposed COVID-CNNnet model aims to provide an accurate binary diagnostic classification for COVID-19 cases versus normal cases. To validate the proposed model, 3540 chest X-ray images were obtained from multiple sources, including 1770 images for COVID-19 cases. Results show that the COVID-CNNnet model can identify all classes (COVID-19 cases versus normal cases) with an accuracy of 99.86%. The proposed method can assist doctors diagnose COVID-19 cases effectively using chest X-ray images.

Pregnant woman with circumvallate placenta and suspected fetal hypotrophy caused by placental insufficiency: a case report

Background: The circumvallate placenta is a rare pathology of the human placenta that occurs in 1–2% of pregnancies. It is characterized by extrachorial placental development, resulting in a ring formation along the edges of the placenta, which leads to efficiency impairment. As a consequence, it causes an intrauterine fetal hypotrophy. The fetal hypotrophic pregnancies are classified as high-risk pregnancies, requiring not only intensive monitoring of fetal development but also maternal and fetal care by the highest reference clinical center. Aim of the study: The aim of this study was to analyze the case of a patient with circumvallate placenta and fetal hypotrophy suspicion. Material and methods: The study was based on the case study method. The data was obtained by analyzing medical documentation collected during hospitalization. The patient was interviewed and observed. All of the selected parameters were measured and scaled. Case study: A 30-year-old primiparous woman at 38+1 weeks gestation, with diagnosed circumvallate placenta and suspected fetal hypotrophy. The pregnancy had several complications, including gestational hypothyroidism. There was spotting and imminent abortion in the first trimester and in the second and third trimester, the patient was treated for vaginal mycosis. There was a risk of preterm labor in the third trimester. The patient was admitted to the delivery room in the first stage of labor. The course of first stage of labor was normal however the second stage of labor was complicated. Obstructed labor with ace presentation, mentoposterior position. A lower uterine segment cesarean section (LUSCS) was performed and a live full-term female infant was delivered, which was found to be small for gestational age (SGA). The course of the early puerperium was uncomplicated with an expected duration of stay in the neonatology department. Both mother and baby were discharged from hospital on postpartum day 3. Conclusions: Circumvallate placenta is not a contraindication to natural delivery however is associated with an increased risk of many perinatal complications. Holistic care during delivery and the early puerperium requires specialized knowledge and skills of medical staff in taking care of both of the mother and the child.

ETHICAL LEVEL DIFFERENCES OF MEDICAL STAFF IN VARIOUS ORGANIZATIONS

The relevance of the research is associated with an increasing interest to the ethical role both in social life and in business management. Some experts and analysts suggest that if organizations have a high ethical level they can reach significant results and prosperity, whereas those with a low ethical level are prone to regression, stagnation or ultimate failure. In the medical staff survey questionnaire, we have used English scholar's profile following the principle of «right-wrong answers». It includes 15 typical business-like situations describing a problem of ethical norm choice in professional activities. The survey enrolled 121 people from three different medical organizations: PHC (Primary Health Centre), Military medics and Regional Laboratory Centre doctors. Each team included both male and female doctors, and also only female nurses. Data showed a high ethical level in Military medics' team who followed the rules and orders with the ethical deductions. Ethical analysis of medical staff based on the gender dimension revealed women to be more ethically oriented than men. Training and ethical behavior improving should be an inherent part of medical staff development both in medical organizations and during skill improvement courses and training. The issues of ethical conduct and developing ethical skills of medical staff should be introduced in academic curricula of post-graduate studies for both doctors and nurses.

The qualitative research and countermeasure analysis on the management problems of accidental falls in elderly patients

Objective To explore the main problems and difficulties encountered by nursing managers in the management of elderly patients with accidental falls. Methods A semi-structured in-depth interview was conducted with ten nursing managers in charge of adverse events, and data was analyzed by Colaizzi analysis. Results Seven themes were extracted from the data, including lack of active awareness of falls prevention, inadequate ability of safety support, lack of precise implementation of interventions, uncoordinated multi-sectoral control, inadequate concepts of ageing and accessibility, lack of related technology products and lack of policy and financial support. Conclusions Fall courses and training programs should be added to improve the level of knowledge and skills of medical staff, and increase the risk awareness and companionship for older and caregivers. And a multidisciplinary team should be formed to conduct a multi-factor intervention on falls. Meanwhile, the concept of barrier-free and ageing to improve the hospital environment will be advocated under the supports of the government to formulate medical policies and increase capital investment. Key words: Aged; Accidental falls; Inpatients; Qualitative research; Nursing management

A fully-automated deep learning pipeline for cervical cancer classification

Cervical cancer ranks the fourth most common cancer among females worldwide with roughly 528, 000 new cases yearly. Around 85% of the new cases occurred in less-developed countries. In these countries, the high fatality rate is mainly attributed to the lack of skilled medical staff and appropriate medical pre-screening procedures. Images capturing the cervical region, known as cervigrams, are the gold-standard for the basic evaluation of cervical cancer presence. Cervigrams have high inter-rater variability especially among less skilled medical specialists. In this paper, we develop a fully-automated pipeline for cervix detection and cervical cancer classification from cervigram images. The proposed pipeline consists of two pre-trained deep learning models for the automatic cervix detection and cervical tumor classification. The first model detects the cervix region 1000 times faster than state-of-the-art data-driven models while achieving a detection accuracy of 0.68 in terms of intersection of union (IoU) measure. Self-extracted features are used by the second model to classify the cervix tumors. These features are learned using two lightweight models based on convolutional neural networks (CNN). The proposed deep learning classifier outperforms existing models in terms of classification accuracy and speed. Our classifier is characterized by an area under the curve (AUC) score of 0.82 while classifying each cervix region 20 times faster. Finally, the pipeline accuracy, speed and lightweight architecture make it very appropriate for mobile phone deployment. Such deployment is expected to drastically enhance the early detection of cervical cancer in less-developed countries.

Active screening for diabetic foot — assessment of health care professionals’ compliance to it

Background. The strategy of care for chronic diabetic complications prevention includes appropriate organization and education of healthcare professionals. Despite the availability of skilled medical staff, there is insufficient information about the feet examination in standard practice. We evaluated the personnel’s compliance in the context of following the guidelines for foot examination. Materials and methods. We retrospectively analyzed 290 questionnaires from patients with diabetes mellitus (54.13% women) enclosed in the medical records from Diabetic Foot Center. Results. The mean patients’ age was 63.24; 7.6% participants suffered from type 1 and 92.4 % from type 2 diabetes; 17.6% patients declared previous foot examination: 31.8% with type 1, 16.4% with type 2 diabetes and it was irrespective from: age, diabetes duration (p = 0.6 and p = 0.37 respectively) and diabetes type (p = 0.068). Conclusion. The foot examination among patients with diabetes, by medical practitioners, is very poor. Neither patient age nor duration or type of diabetes had an influence on the decision for foot examination in our study. Our study has showed that not the guidelines but inadequate foot examination by medical staff could be the main problem of the prevention of diabetic foot. We should stress and re-educate patients but also medical staff about the foot examination.

"The Degree Of Satisfaction Perceived By Healthcareservices Consumers In State Hospitals - Case Studyemergency County Hospital From Alba Iulia "

The paper investigates the degree of satisfaction of the patients that accessed themedical services provided by the Emergency County Hospital from Alba Iulia. The hey factorsconsidered important in establishing the degree of satisfaction were the following: theendowment with new generation of portable medical equipment (ultrasound machine, portableoxygen, resuscitation equipment); the endowment with new generation of fixed medicalequipment (ray machine, CT); the hospital furniture; the endowment with non-medicalequipment for physical comfort of patients (climate equipment); skills of medical staff; thewaiting time until the takeover by a doctor/nurse; the effectiveness of doctors; nurses efficiency,cleaning efficiency of support staff perceived patient in the respective unit.

Recognition of medical staff in the oncology department about management of cancer related fatigue: a qualitative research

Objective To explore how medical staff in the oncology department understand management of cancer related fatigue (CRF), and explore what factors influencing the effective practice of CRF management. Methods Qualitative inquiry was adopted. Ten medical staffs in the oncology department were selected for in-depth interview. Generic analysis was applied to code, categorize and interpret the qualitative data. Results Participants believed that many factors influenced the CRF, which hadn't been assessed as an independent symptom and lacked the systematic, effective and specific interventions. The medical staff, patients and their families neglecting the CRF management was the main barrier. Strengthening system construction and staff training was mentioned as major area which needed to be improved. Conclusions CRF management guideline should be formulated according to our national situations based on the clinical practices, besides, the training of correlated clinical knowledge and skills of medical staff should be strengthened and eventually promote the cancer patients' quality of life. Key words: Medical staff; Cancer related fatigue; Symptom management; Qualitative inquiry

의료관광 동기에 있어 추진(Push)요인과 유인(Pull)요인의 관계

Using canonical correlation analysis, this study analyzed the relation of push-pull factors in motivations for medical tourism focusing on Chinese people in their 20s and 30s. In order to promote facilitation of medical tourism in Korea, it is necessary to investigate strategies interrelating push factors and pull factors effectively as an important area of research. The result of the analysis drew out 3 canonical functions. In Canonical Function 1, the push factors of ‘Exotic and unusual sentiments’(-.574), ‘Recharging and break from the busy daily life’(-.466) were highly correlated with pull factors of ‘Various opportunities for shopping’(-.513), ‘Various foods of the country’(-.462). In Canonical Function 2, the push factor of ‘Treatment of illness (disease) that is difficult to be treated in my country’(.433) was highly correlated with pull factors of ‘Highly skilled medical staff and professionals’(.425), ‘Availability of treatment in internationally accredited hospitals’(.422), ‘Advanced high-tech medical facilities’(.418). The findings could figure out the kinds of motivations for medical tourism that the Chinese medical tourists were attracted and implemented by.

Physicians’ brain drain in Greece: A perspective on the reasons why and how to address it

This review study explores the “brain drain” currently evident amongst physicians in Greece, which is closely linked to the country's severe financial woes. In particular, it shows that the Greek healthcare labour market offers few opportunities and thus physicians are forsaking their homeland to seek jobs abroad. The main causes generating or greatly inflating the brain drain of Greek physicians are unemployment, job insecurity, income reduction, over-taxation, together with limited budgets for research institutes. It is argued that, to stop the evolving mass exodus of skilled medical staff, policy-makers should implement fiscal and human-centred approaches, thoroughly safeguarding both the right of skilled Greek physicians to work in their homeland with motivation and dignity, but also of Greek citizens to continue receiving high-quality healthcare by skilled physicians at times when this is mostly needed.