Conservation of resources perspective on authentic leadership and employee well-being: The influence of job stress and emotional intelligence.

BACKGROUND: Health care industries must consider their sustainable development, and employee well-being is a crucial environmental, social, and governance indicator that should be prioritized. During events such as the COVID-19 pandemic, information transparency is a concern for health care workers. Authentic leaders can build trust by openly sharing their thoughts and feelings. Understanding how authentic leadership affects employee well-being through job stress and how emotional intelligence reduces job stress is essential for health care workers. PURPOSES: This study investigated the effect of authentic leadership on employee well-being and considered the mediating role of job stress and moderating role of emotional intelligence in this effect. METHODOLOGY/APPROACH: A time-lagged survey of 452 full-time health care workers (comprising nurses, allied health professionals, and administrative workers) from a general hospital in Taiwan was conducted. FINDINGS: Authentic leadership was positively associated with employee well-being, and job stress mediated the effects of authentic leadership on employee well-being. Among the employees who perceived leadership to be authentic, those with higher emotional intelligence felt less job stress. CONCLUSION: From the perspective of conservation of resources theory, authentic leadership was identified as a crucial factor influencing how health care workers reduce job stress and improve their well-being. Emotional intelligence was identified as essential in enhancing the effects of authentic leadership on reducing the job stress of health care workers. PRACTICE IMPLICATIONS: Organizations should promote authentic interactions between leaders and followers and provide training for developing authentic leadership. They should also provide training to improve their employees' emotional intelligence.

Do hospitals attaining a public recognition for treating nurses fairly deliver better-quality health care? Evidence from cross-sectional analysis of California hospitals.

AIM: This study explored whether hospitals that allocate greater resources to their nursing staff provide better healthcare services than those that invest less in their nursing personnel. DESIGN: Cross-sectional logistic and tobit analyses. METHODS: We examined a sample of 314 California hospitals in 2017. We obtained a hospital's public recognition for treating nurses fairly between 2015 and 2017 from Nurse.org, the largest online community of nurses. We derived a hospital's healthcare quality in 2018 from the 2019-2020 Best Hospitals rankings released by U.S. News, a well-known media company publishing independent healthcare assessments periodically. RESULTS: Our results showed that a nurse-friendly workplace was a crucial determinant of its overall healthcare quality. CONCLUSION AND IMPLICATIONS: Healthcare administrators keen to enhance the quality of healthcare services should consider creating nurse-friendly workplaces. Furthermore, their evaluation of nurses' contributions to overall healthcare quality should not solely depend on the nurse-assessed quality of care, but rather comprise not only broad aspects of patient outcomes in primary care but also patient experiences, care-related factors and expert opinions. PATIENT OR PUBLIC CONTRIBUTION: Our study helped address the overwhelmed healthcare system, whose long-running shortage of nurses has been exacerbated by the COVID-19 pandemic. Our work suggested that a hospital's investment in a nurse-friendly workplace can enhance its acquisition, retention and devotion of the nursing staff. This, in turn, can have profound impacts on its overall healthcare quality. WHAT ALREADY IS KNOWN: Existing empirical evidence on the relation between nurse-friendly workplace and healthcare quality is limited and inconclusive. WHAT THIS PAPER ADDS: We documented evidence that the quality of healthcare services provided by hospitals varies with their treatment of nursing staff. IMPLICATIONS FOR PRACTICE/POLICY: Our results provided insights into key policies that have the potential to improve healthcare quality.

Effectiveness of a multicomponent activity and horticultural intervention for the hospitalized older adults: A randomized controlled trial: Effectiveness of Intervention for the Hospitalized Older Adults.

This study evaluated the effectiveness of different intervention programs in improving function among hospitalized older individuals using the Comprehensive Geriatric Assessment (CGA). A randomized controlled trial consisted of three groups: routine care, horticulture, and multicomponent activities (n = 32 each). Horticultural and multicomponent activity interventions showed beneficial effects on the CGA in hospitalized older individuals, particularly regarding cognitive function and quality-of-life. Additionally, horticultural activities significantly contributed to the perception of older adults' health status. We recommend to select older patients in geriatric wards with long-term hospitalization and adjust the frequency of activities or choose a single intervention program to provide long-term and effective intervention effects.

Relationship between using cancer resource center services and patient outcomes.

PURPOSE: Psychological and social support are crucial in treating cancer. Cancer resource centers provide patients with cancer and their families with services that can help them through cancer treatment, ensure that patients receive adequate treatment, and reduce cancer-related stress. These centers offer various services, including medical guidance, health education, emotional assistance (e.g., consultations for cancer care), and access to resources such as financial aid and post recovery programs. In this study, we comprehensively analyzed how cancer resource centers assist patients with cancer and improve their clinical outcomes. METHODS: The study participants comprised patients initially diagnosed with head and neck cancer or esophageal cancer. A total of 2442 patients from a medical center in Taiwan were included in the study. Data were analyzed through logistic regression and Cox proportional hazards regression. RESULTS: The results indicate that unemployment, blue-collar work, and a lower education level were associated with higher utilization of cancer resource center services. The patients who were unemployed or engaged in blue-collar work had higher risks of mortality than did their white-collar counterparts. Patient education programs can significantly improve the survival probability of patients with cancer. On the basis of our evaluation of the utilization and benefits of services provided by cancer resource centers, we offer recommendations for improving the functioning of support systems for patients with cancer and provide suggestions for relevant future research. CONCLUSIONS: We conclude that cancer resource centers provide substantial support for patients of low socioeconomic status and improve patients' survival.

Long-term care insurance purchase decisions of registered nurses: Deep learning versus logistic regression models.

OBJECTIVE: The purpose of this study was to use a deep learning model and a traditional statistical regression model to predict the long-term care insurance decisions of registered nurses. METHODS: We Prospectively surveyed 1,373 registered nurses with a minimum of 2 years of full-time working experience at a large medical center in Taiwan: 615 who already owned long-term care insurance (LTCI), 332 who had no intention to purchase LTCI (group 1), and 426 who intended to purchase LTCI (group 2). RESULTS: After inverse probability of treatment weighting (IPTW), no statistically significant differences were identified in the study characteristics of the two groups. All the performance indices for the deep neural network (DNN) model were significantly higher than those of the multiple logistic regression (MLR) model (P<0.001). The strongest predictor of an individual's long-term care insurance decision was their risk propensity score, followed by their caregiving responsibilities, whether they live with older adult relatives, their experiences of catastrophic illness, and their openness to experience. CONCLUSIONS: The DNN model is useful for predicting long-term care insurance decisions. Its prediction accuracy can be increased through training with temporal data collected from registered nurses. Future research can explore designs for two-level or multilevel models that explain the contextual effects of the risk factors on long-term care insurance decisions.

Abusive supervision and employee well-being of nursing staff: Mediating role of occupational stress.

AIM: The study examined whether occupational stress mediated the relationship between abusive supervision and well-being of nursing staff. DESIGN: A cross-sectional questionnaire survey was administered. METHODS: Data were collected at three-time points between July 2020 and January 2021. A total of 313 valid responses were obtained from nurses working in a general hospital in Taiwan. The data were analysed using descriptive statistics, Pearson's correlation analysis and the bootstrap method. RESULTS: Abusive supervision was positively associated with occupational stress (ß = 0.288, SE = 0.069, 95% CI [0.152, 0.423]) and negatively associated with employee well-being, including psychological (ß = -0.350, SE = 0.084, 95% CI [-0.515, -0.186]), physical (ß = -0.301, SE = 0.080, 95% CI [-0.459, -0.143]) and social well-being (ß = -0.422, SE = 0.121, 95% CI [-0.661, -0.183]). Occupational stress was negatively related to employee well-being. A mediation analysis with bootstrapping revealed that occupational stress mediated the relationship between abusive supervision and employee well-being, which included psychological (95% bootstrap CI [-0.183, -0.046]), physical (95% bootstrap CI [-0.212, -0.062]) and social well-being (95% bootstrap CI [-0.178, -0.040]). CONCLUSION: Abusive supervision influences employee well-being. Occupational stress mediates the relationship between abusive supervision and employee well-being. To improve employee well-being, hospital administrators should develop policies for effectively managing nursing supervisors' abusive behaviour and subordinates' stress management. IMPACT: Abusive supervision increased the occupational stress of employees and influenced their well-being. Thus, educational courses should be implemented to train supervisors to practice positive leadership and treat employees fairly. Promoting stress management among nursing staff may lead to the prompt reporting of abusive events and improved employee well-being. NO PATIENT OR PUBLIC CONTRIBUTION: This study investigated the relationship between the abusive supervision and employee well-being of nursing employees. No patient or public contribution is involved in this study.

Predicting 30-Day Readmission for Stroke Using Machine Learning Algorithms: A Prospective Cohort Study.

Background: Machine learning algorithms for predicting 30-day stroke readmission are rarely discussed. The aims of this study were to identify significant predictors of 30-day readmission after stroke and to compare prediction accuracy and area under the receiver operating characteristic (AUROC) curve in five models: artificial neural network (ANN), K nearest neighbor (KNN), random forest (RF), support vector machine (SVM), naive Bayes classifier (NBC), and Cox regression (COX) models. Methods: The subjects of this prospective cohort study were 1,476 patients with a history of admission for stroke to one of six hospitals between March, 2014, and September, 2019. A training dataset (n = 1,033) was used for model development, and a testing dataset (n = 443) was used for internal validation. Another 167 patients with stroke recruited from October, to December, 2019, were enrolled in the dataset for external validation. A feature importance analysis was also performed to identify the significance of the selected input variables. Results: For predicting 30-day readmission after stroke, the ANN model had significantly (P < 0.001) higher performance indices compared to the other models. According to the ANN model results, the best predictor of 30-day readmission was PAC followed by nasogastric tube insertion and stroke type (P < 0.05). Using a machine learning ANN model to obtain an accurate estimate of 30-day readmission for stroke and to identify risk factors may improve the precision and efficacy of management for these patients. Conclusion: Using a machine-learning ANN model to obtain an accurate estimate of 30-day readmission for stroke and to identify risk factors may improve the precision and efficacy of management for these patients. For stroke patients who are candidates for PAC rehabilitation, these predictors have practical applications in educating patients in the expected course of recovery and health outcomes.

Protective Behaviors for COVID-19 Were Associated With Fewer Psychological Impacts on Nurses: A Cross-Sectional Study in Taiwan.

OBJECTIVE: The COVID-19 pandemic has increased psychological distress among common people and has caused health care providers, such as nurses, to experience tremendous stress. METHODS: This prospective cross-sectional study assessed the psychological impacts on nurses in a community hospital in Taiwan, including major depressive disorder (MDD), posttraumatic stress (PTS), and pessimism. According to transactional theory, coping strategies and personal factors have psychological impacts. We hypothesized that behavioral responses to COVID-19 (problem-focused coping) are more effective in reducing psychological impacts than emotional responses to COVID-19 (emotion-focused coping). Independent variables were the use of behavioral and emotional coping strategies for COVID-19 and 3 personal factors, namely sleep disturbance, physical component summary (PCS-12), and mental component summary (MCS-12) of the 12-Item Short Form Health Survey (SF-12) obtained from the Medical Outcomes Study. Dependent variables comprised 3 psychological impacts, namely MDD, PTS, and pessimism. RESULTS: We determined that behavioral coping strategies had significant negative effects on PTS and pessimism; however, emotional coping strategies had significantly positive effects on PTS and pessimism. Sleep disturbance was significantly associated with increased MDD and pessimism. PCS-12 had a significant negative effect on PTS, whereas MCS-12 was not significantly associated with any of the 3 psychological impacts. CONCLUSIONS: Nurses who adopted protective behavior against COVID-19, such as washing hands, wearing masks, avoiding touching eyes, and mouth, and avoiding personal contact, were associated with less posttraumatic stress and pessimism. Healthcare providers should consider strategies for improving preventive behaviors to help ease their worries and fears concerning COVID-19.

Moderation effect of mammography screening among women with multiple chronic conditions.

Comorbidity substantially affects breast cancer risk and prognosis. However, women with chronic conditions are less likely to participate in mammography screening. Few studies have examined potential benefits of mammography in women with chronic conditions. This study investigated the moderation effects of mammography screening on early stage breast cancer and all-cause mortality among women aged 50-69 years with chronic conditions in Taiwan. We used a matched cohort design with four nationwide population databases, and an exact matching approach to match groups with different chronic conditions. Women population aged 50-69 years in 2010 in Taiwan were studied. A generic Charlson comorbidity index (CCI) measure was used to identify chronic illness burden. The sample sizes of each paired matched group with CCI scores of 0, 1, 2, or 3+ were 170,979 using a 1-to-1 exact matching. Conditional logistic regressions with interaction terms were used to test moderation effect, and adjusted predicted probabilities and marginal effects to quantify average and incremental chronic conditions associated with outcome measures. Statistical analyses were conducted in 2020-2021. Women with more chronic conditions were less likely to participate in mammography screening or to receive early breast cancer diagnoses, but were at greater risk of mortality. However, mammography participation increased the likelihood of early breast cancer diagnosis (OR 1.48, 95% CI 1.36-1.60) and decreased risk of all-cause mortality (HR 0.53, 95% CI 0.51-0.55). The interaction terms of CCI and mammography participation indicated significantly increased benefits of early breast cancer diagnosis and decreased risk of all-cause mortality as chronic illness increased. Mammography participation significantly moderated the link between comorbidity and outcome measures among women with chronic conditions. Hence, it is important for public health policy to promote mammography participation for women with multiple chronic conditions.

Determinants of Successful Nursing Home Accreditation.

OBJECTIVES: This study examined the factors associated with better accreditation outcomes among nursing homes. METHOD: A total of 538 nursing homes in Taiwan were included in this study. Measures included accreditation scores, external factors (household income, Herfindahl-Hirschman Index, old-age dependency ratio, population density, and number of older adult households), organizational factors (hospital-based status, chain-affiliated status, occupancy rate, the number of registered nurses or nurse aides per bed, and bed size), and internal factors (accountability, deficiencies, person-centered care, nursing skills, quality control, and integrated care). RESULTS: Bed size, hospital-based status, accountability, deficiencies, person-centered care, nursing skills, quality control, and integrated care were found to predict accreditation. CONCLUSION: Among all variables in this study, the quality indicators contributed to the most variation, followed by organizational factors. External environmental factors played a minor role in predicting accreditation. A focus on quality of care would benefit not only the residents of a nursing home but also facilitate its accreditation.

Cost and Effectiveness of Long-Term Care Following Integrated Discharge Planning: A Prospective Cohort Study.

Little is known about the effects of seamless hospital discharge planning on long-term care (LTC) costs and effectiveness. This study evaluates the cost and effectiveness of the recently implemented policy from hospital to LTC between patients discharged under seamless transition and standard transition. A total of 49 elderly patients in the standard transition cohort and 119 in the seamless transition cohort were recruited from November 2016 to February 2018. Data collected from medical records included the Multimorbidity Frailty Index, Activities of Daily Living Scale, and Malnutrition Universal Screening Tool during hospitalization. Multiple linear regression and Cox regression models were used to explore risk factors for medical resource utilization and medical outcomes. After adjustment for effective predictors, the seamless cohort had lower direct medical costs, a shorter length of stay, a higher survival rate, and a lower unplanned readmission rate compared to the standard cohort. However, only mean total direct medical costs during hospitalization and 6 months after discharge were significantly (p < 0.001) lower in the seamless cohort (USD 6192) compared to the standard cohort (USD 8361). Additionally, the annual per-patient economic burden in the seamless cohort approximated USD 2.9-3.3 billion. Analysis of the economic burden of disability in the elderly population in Taiwan indicates that seamless transition planning can save approximately USD 3 billion in annual healthcare costs. Implementing this policy would achieve continuous improvement in LTC quality and reduce the financial burden of healthcare on the Taiwanese government.

Long-Term Trends and Predictors of Medical Resource Utilization and Medical Outcomes in Inguinal Hernia Repair: A Nationwide Cohort Study.

BACKGROUND: Few studies have comprehensively and systematically analyzed nationwide samples. This study purposed to explore temporal trends and predictors of medical resource utilization and medical outcomes in these patients to obtain data that can be used to improve healthcare policies and to support clinical and administrative decision-making. METHODS: This study used nationwide population data contained in the Longitudinal Health Insurance Database of Taiwan. The 14,970 inguinal hernia repair patients were enrolled in this study (age range, 18-100 years) from 1997 to 2013 in Taiwan. After temporal trends analysis of demographic characteristics, clinical characteristics, and institutional characteristics, predictors of postoperative medical resource utilization and medical outcomes were evaluated through multiple linear regression analysis and Cox regression analysis. RESULTS: The prevalence of inguinal hernia repair per 100,000 population significantly decreased from 195.38 in 1997 to 39.66 in 2013 (p < 0.05). Demographic characteristics, clinical characteristics, and institutional characteristics were significantly associated with postoperative medical resource utilization and medical outcomes (p < 0.05). Of these characteristics, both surgeon volume and hospital volume had the strongest association. CONCLUSIONS: The inguinal hernia repair prevalence rate gradually decreased during the study period. Demographic characteristics, clinical characteristics, and institutional characteristics had strong associations with postoperative medical resource utilization and medical outcomes. Furthermore, hospital volume and surgeon volume had the strongest associations with postoperative medical resource utilization and medical outcomes. Additionally, providing the education needed to make the most advantageous medical decisions would be a great service not only to patients and their families, but also to the general population.

Impact of Multidisciplinary Stroke Post-Acute Care on Cost and Functional Status: A Prospective Study Based on Propensity Score Matching.

Few papers discuss how the economic burden of patients with stroke receiving rehabilitation courses is related to post-acute care (PAC) programs. This is the first study to explore the economic burden of stroke patients receiving PAC rehabilitation and to evaluate the impact of multidisciplinary PAC programs on cost and functional status simultaneously. A total of 910 patients with stroke between March 2014 and October 2018 were separated into a PAC group (at two medical centers) and a non-PAC group (at three regional hospitals and one district hospital) by using propensity score matching (1:1). A cost-illness approach was employed to identify the cost categories for analysis in this study according to various perspectives. Total direct medical cost in the per-diem-based PAC cohort was statistically lower than that in the fee-for-service-based non-PAC cohort (p < 0.001) and annual per-patient economic burden of stroke patients receiving PAC rehabilitation is approximately US $354.3 million (in 2019, NT $30.5 = US $1). Additionally, the PAC cohort had statistical improvement in functional status vis-à-vis the non-PAC cohort and total score of each functional status before rehabilitation and was also statistically significant with its total score after one-year rehabilitation training (p < 0.001). Early stroke rehabilitation is important for restoring health, confidence, and safe-care abilities in these patients. Compared to the current stroke rehabilitation system, PAC rehabilitation shortened the waiting time for transfer to the rehabilitation ward and it was indicated as an efficient policy for treatment of stroke in saving medical cost and improving functional status.

Private Long-Term Care Insurance Decision: The Role of Income, Risk Propensity, Personality, and Life Experience.

The rising aging population contributes to increased caregiver burden and a greater need for long-term care services, thereby posing stronger financial burden. The current study aimed to examine the effect of income, risk-taking propensity, personality traits, and life experience on the ownership of and intention to own private long-term care insurance (LTCI). Primary data were collected from 1373 registered nurses with a minimum of two years of full-time working experience. Multinomial logistic regression was used to examine the relationships between ownership of LTCI and personal discretionary income, risk propensity, openness to experience, and life experience. Personal discretionary income was a crucial positive indicator in predicting ownership of LTCI. Higher risk-taking propensity was found to be negatively related to both currently own and future intention to own private LTCI. Participants who currently live with elders and who agree to caregiving responsibilities with government-provided cash allowance showed future intention to purchase LTCI. Little evidence was found for an association between life experience and future intention to own LTCI. Income, risk-taking propensity, and personality traits differ in their impact on ownership of and future intention to own LTCI. Our results provide policy makers with a better understanding of the forces driving demand in the private LTCI market, as well as the accompanying implications for public LTCI.

Breast Cancer Surgery 10-Year Survival Prediction by Machine Learning: A Large Prospective Cohort Study.

Machine learning algorithms have proven to be effective for predicting survival after surgery, but their use for predicting 10-year survival after breast cancer surgery has not yet been discussed. This study compares the accuracy of predicting 10-year survival after breast cancer surgery in the following five models: a deep neural network (DNN), K nearest neighbor (KNN), support vector machine (SVM), naive Bayes classifier (NBC) and Cox regression (COX), and to optimize the weighting of significant predictors. The subjects recruited for this study were breast cancer patients who had received breast cancer surgery (ICD-9 cm 174-174.9) at one of three southern Taiwan medical centers during the 3-year period from June 2007, to June 2010. The registry data for the patients were randomly allocated to three datasets, one for training (n = 824), one for testing (n = 177), and one for validation (n = 177). Prediction performance comparisons revealed that all performance indices for the DNN model were significantly (p < 0.001) higher than in the other forecasting models. Notably, the best predictor of 10-year survival after breast cancer surgery was the preoperative Physical Component Summary score on the SF-36. The next best predictors were the preoperative Mental Component Summary score on the SF-36, postoperative recurrence, and tumor stage. The deep-learning DNN model is the most clinically useful method to predict and to identify risk factors for 10-year survival after breast cancer surgery. Future research should explore designs for two-level or multi-level models that provide information on the contextual effects of the risk factors on breast cancer survival.

Machine Learning Algorithms to Predict Recurrence within 10 Years after Breast Cancer Surgery: A Prospective Cohort Study.

No studies have discussed machine learning algorithms to predict recurrence within 10 years after breast cancer surgery. This study purposed to compare the accuracy of forecasting models to predict recurrence within 10 years after breast cancer surgery and to identify significant predictors of recurrence. Registry data for breast cancer surgery patients were allocated to a training dataset (n = 798) for model development, a testing dataset (n = 171) for internal validation, and a validating dataset (n = 171) for external validation. Global sensitivity analysis was then performed to evaluate the significance of the selected predictors. Demographic characteristics, clinical characteristics, quality of care, and preoperative quality of life were significantly associated with recurrence within 10 years after breast cancer surgery (p < 0.05). Artificial neural networks had the highest prediction performance indices. Additionally, the surgeon volume was the best predictor of recurrence within 10 years after breast cancer surgery, followed by hospital volume and tumor stage. Accurate recurrence within 10 years prediction by machine learning algorithms may improve precision in managing patients after breast cancer surgery and improve understanding of risk factors for recurrence within 10 years after breast cancer surgery.

Effect of referral systems on costs and outcomes after hip fracture surgery in Taiwan.

OBJECTIVE: To explore the economic burdens of hip fracture surgery in patients referred to lower-level medical institutions and to evaluate how referral systems affect costs and outcomes of hip fracture surgery. DESIGN: A nationwide population-based retrospective cohort study. SETTING: All hospitals in Taiwan. PARTICIPANTS: A total of 7500 patients who had received hip fracture surgery (International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) diagnostic codes 820.0 ∼ 820.9 and procedure codes 79.15, 79.35, 81.52, 81.53) performed in 1997 to 2013. MAIN OUTCOME MEASURES: Total costs including outpatient costs, inpatient costs and total medical costs and medical outcomes including 30-day readmission, 90-day readmission, infection, dislocation, revision and mortality. RESULTS: The patients were referred to a lower medical institution after hip fracture surgery (downward referral group) and 3034 patients continued treatment at the same medical institution (non-referral group). Demographic characteristics, clinical characteristics and institutional characteristics were significantly associated with postoperative costs and outcomes (P < 0.05). On average, the annual healthcare cost was New Taiwan Dollars (NT$)2262 per patient lower in the downward referral group compared with the non-referral group. The annual economic burdens of the downward referral group approximated NT$241 million (2019 exchange rate, NT$30.5 = US$1). CONCLUSIONS: Postoperative costs and outcomes of hip fracture surgery are related not only to demographic and clinical characteristics, but also to institutional characteristics. The advantages of downward referral after hip fracture surgery can save huge medical costs and provide a useful reference for healthcare authorities when drafting policies for the referral system.

Emotional Labor in Health Care: The Moderating Roles of Personality and the Mediating Role of Sleep on Job Performance and Satisfaction.

The objective of this study is to investigate the effects of emotional labor on job performance and satisfaction, as well as to examine the mediating effect of sleep problems and the moderating effects of personality traits. A time-lagged study was conducted on 864 health professionals. Scales for emotional labor, sleep, personality traits, and job satisfaction were used and job performance data was obtained from records maintained by human resources. Structural equation modeling was performed to investigate the relations. Sleep problems only partially mediated the relationship between surface acting and job satisfaction but completely mediated the relationship between surface acting and job performance. Several personality traits were shown to moderate the relationship between surface acting and sleep problems. The effects were stronger for people with low agreeableness and high neuroticism. The relationship between high levels of deep acting and low levels of sleep problems was more pronounced in individuals with low extraversion. Supervisors should be conscious of emotional labor in the work context and provide necessary deep acting training to facilitate emotional regulation.

Prescribing patterns of coronary artery aneurysm in Taiwan.

BACKGROUND: Coronary artery aneurysm (CAA) is a rare disease, and there are limited data on prescribing patterns for CAA. The aim of our study was to investigate prescribing patterns for CAA in Taiwan via the National Health Insurance Research Database (NHIRD). METHODS: We included all CAA patients in Taiwan from 2005 to 2011. Data from 1 year before and after the CAA diagnosis were used to analyze examinations, comorbidities and prescribing patterns. RESULTS: A total of 1397 patients diagnosed with CAA were enrolled in our study. Most pediatric patients with CAA were diagnosed with Kawasaki disease (95.7%). In pediatric CAA patients, the utilization rates of aspirin and gamma globulins were 82.9 and 53.6%, respectively, after CAA diagnosis. Among the antithrombotic agents, aspirin was used most commonly, followed by dipyridamole (16.9%), heparin (5.8%) and warfarin (4.6%). In adult CAA patients, common comorbidities included hypertension (63.4%), hyperlipidemia (39.6%), and diabetes mellitus (26.1%). Coronary atherosclerosis was identified in 72.5% of adult patients after CAA diagnosis. Antithrombotic agents, particularly aspirin, clopidogrel and heparin, were prescribed more frequently after CAA diagnosis. Among the prescribed medications, aspirin (75.8%), ß-blockers (48.3%), statins (47.6%), metformin (14.4%), sulfonylureas (14.4%) and isosorbide mononitrate (32.9%) were frequently observed in each category. CONCLUSIONS: Kawasaki disease was the main cause of CAA in pediatric patients, and coronary artery disease was the most common comorbidity in adult CAA patients. The most commonly used antithrombic agent after CAA diagnosis was aspirin in both adult and pediatric patients.

Multidiscipline Stroke Post-Acute Care Transfer System: Propensity-Score-Based Comparison of Functional Status.

Few studies have investigated the characteristics of stroke inpatients after post-acute care (PAC) rehabilitation, and few studies have applied propensity score matching (PSM) in a natural experimental design to examine the longitudinal impacts of a medical referral system on functional status. This study coupled a natural experimental design with PSM to assess the impact of a medical referral system in stroke patients and to examine the longitudinal effects of the system on functional status. The intervention was a hospital-based, function oriented, 12-week to 1-year rehabilitative PAC intervention for patients with cerebrovascular diseases. The average duration of PAC in the intra-hospital transfer group (31.52 days) was significantly shorter than that in the inter-hospital transfer group (37.1 days) (p < 0.001). The intra-hospital transfer group also had better functional outcomes. The training effect was larger in patients with moderate disability (Modified Rankin Scale, MRS = 3) and moderately severe disability (MRS = 4) compared to patients with slight disability (MRS = 2). Intensive post-stroke rehabilitative care delivered by per-diem payment is effective in terms of improving functional status. To construct a vertically integrated medical system, strengthening the qualified local hospitals with PAC wards, accelerating the inter-hospital transfer, and offering sufficient intensive rehabilitative PAC days are the most essential requirements.