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.

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.

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.

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.

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.

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.

Breast Cancer Incidence and Predictors of Surgical Outcome: a Nationwide Longitudinal Study in Taiwan.

AIMS: Despite the huge and growing global burden of patients who require breast cancer surgery, high-quality population-based studies of breast cancer trends and outcomes are scarce. The purpose of this study was to explore the incidence of breast cancer and predictors of hospital resource utilisation, mortality and recurrence in a nationwide population of patients who have received surgery. MATERIALS AND METHODS: This retrospective study analysed trends and outcomes in a Taiwan population of 77 971 patients after breast cancer surgery during 1996-2010. The Cox proportional hazards model was used for multivariate assessment of both mortality and recurrence predictors. RESULTS: The data analysis indicated that, during this period, the estimated mean hospital treatment cost and mean length of stay increased by 16.3% and 53.4%, respectively. The estimated mean overall survival time was 138.9 months (standard deviation 0.3 months) and the overall 1, 3, 5 and 10 year survival rates were 97.3, 89.2, 82.2 and 70.1%, respectively. The estimated mean overall recurrence time was 10.8 months (standard deviation 0.2 months) and the overall 1, 3, 5 and 10 year recurrence rates were 0.1, 18.8, 26.6 and 36.0%, respectively. Outcomes were significantly associated with age, Deyo-Charlson comorbidity index score, surgeon seniority, hospital volume, surgeon volume, surgery type, hospital level and baseline comorbidities (P<0.001). CONCLUSIONS: Analyses of these population-based data revealed simultaneous increases in the standard incidence of breast cancer surgery and its associated medical resource utilisation. Notably, healthcare providers and patients should recognise that both patient attributes and hospital attributes may affect breast cancer surgery outcomes.

The moderating effect of leadership on the relationship between personality and performance.

AIM: To examine how personality and leadership influence efficiency in the nursing service environment. BACKGROUND: Leadership and personality contribute to the success and failure of a unit. However, how they interact to influence performance is still understudied. METHODS: We used matched pairs sample design to survey 135 head nurses and 1353 registered nurses on validated instruments of demographic characteristics, leadership styles and personality during June and July of 2014. Efficiency was calculated using Data Envelopment Analysis. Tobit regression was used for analysis. RESULTS: High conscientiousness and low neuroticism were significantly associated with higher efficiency. Particularly, under the initiating structure leadership style, high conscientiousness, high extraversion, high agreeableness, high openness and low neuroticism were related to higher efficiency. Openness would improve efficiency under a low consideration leadership style. CONCLUSIONS: Most personality traits were related to higher efficiency under the initiating leadership style. Only openness would improve leaders' efficiency under a high initiating structure and a low consideration leadership style. IMPLICATIONS FOR NURSING MANAGEMENT: Considering personality as one factor of selecting head nurses, selecting the right person can improve the fit between individuals and organisations, which in turn, improves job performance. Training head nurses to develop better leadership styles in nurses is another way to enhance efficiency.

Patient assessment of diabetes care in a pay-for-performance program.

OBJECTIVE: Few studies address quality of care in pay-for-performance (P4P) programs from the perspective of patients' perceptions. This study aimed to examine and compare the patient assessment of diabetes chronic care as perceived by diabetic patients enrolled and not enrolled in a P4P program from the patients' self-reported perspectives. DESIGN: A cross-sectional study with case and comparison group design. SETTING: A large-scale survey was conducted from February to November 2013 in 18 healthcare institutions in Taiwan. PARTICIPANTS: A total of 1458 P4P (n = 1037) and non-P4P (n = 421) diabetic patients participated in this large survey. The Chinese version of the Patient Assessment of Chronic Illness Care (PACIC) instrument was used and patients' clinical outcome data (e.g. HbA1c, LDL) were collected. INTERVENTION: None. MAIN OUTCOME MEASURES: Five subscales from the PACIC were measured, including patient activation, delivery system design/system support, goal setting/tailoring, problem solving/contextual and follow-up/coordination. Patient clinical outcomes were also measured. Multiple linear regression and logistic regression models were used and controlled for patient demographic and health institution characteristics statistically. RESULTS: After adjusting for covariates, P4P patients had higher overall scores on the PACIC and five subscales than non-P4P patients. P4P patients also had better clinical processes of care (e.g. HbA1c test) and intermediate outcomes. CONCLUSIONS: Patients who participated in the program likely received better patient-centered care given the original Chronic Care Model. Better perceptions of diabetic care assessment also better clinical outcomes. The PACIC instrument can be used for the patient assessment of chronic care in a P4P program.

Associations between Tai Chi Chung program, anxiety, and cardiovascular risk factors.

PURPOSE: To examine the effects of a Tai Chi Chung (TCC) program, an efficiency approach, on anxiety and cardiovascular risk factors. DESIGN: A quasi-experimental study. SETTING: A community in Taipei City, Taiwan. Subjects. One hundred thirty-three adults aged 55 years and older. Intervention. Sixty-four participants (experimental group) attended a 60-minute Tai Chi exercise three times per week for 12 weeks, whereas 69 participants (control group) maintained their usual daily activities. MEASURES: Anxiety states, systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), and waist circumference (WC) were assessed at baseline, 6 weeks into the experiment, and 12 weeks into the experiment. ANALYSIS: Generalized estimating equations were used to evaluate the changes. RESULTS: Participants showed a greater drop in anxiety levels (ß = -2.57, p = .001) and DBP (ß = -7.02, p < .001) at the 12-week follow-up than did the controls. SBP significantly decreased in the 6-week follow-up and 12-week follow-up tests. The participants in the intervention achieved a greater drop in BMI at the 6-week and 12-week follow-up visits than the controls. The interventions demonstrated decreased average WC at the 6-week and 12-week follow-up visits as compared to the controls. CONCLUSION: The results highlight the long-term benefits of a TCC program in facilitating health promotion by reducing anxiety and risk factors for cardiovascular diseases.

The effect of Qigong on menopausal symptoms and quality of sleep for perimenopausal women: a preliminary observational study.

OBJECTIVES: The study objectives were to examine the effect of a 12-week 30-minute-a-day Ping Shuai Qigong exercise program on climacteric symptoms and sleep quality in perimenopausal women. DESIGN: This was a prospective observational study. SETTINGS/LOCATION: The subjects (N=70) from two communities were women aged 45 years and above who were experiencing menopausal symptoms. SUBJECTS: Thirty-five (35) women from one community were assigned to a Ping Shuai Qigong intervention group, while 35 women from the other community were assigned to the control group. INTERVENTIONS: This was a 12-week, 30-minute-a-day Ping Shuai Qigong program. OUTCOME MEASURES: The Greene Climacteric Symptom scale and the Pittsburgh Sleep Quality Index were the outcome measures. METHODS: Descriptive analysis and repeated-measures analysis of variance were used. RESULTS: Pretest scores at baseline found no significant group differences in climacteric symptoms or sleep quality. Significant improvements in climacteric symptoms were found at 6 weeks and 12 weeks (t=4.07, p<0.001 and t=11.83, p<0.001) in the intervention group. They were also found to have significant improvements in sleep quality in those times (t=5.93, p<0.001 and t=10.58, p<0.001, respectively). CONCLUSIONS: Ping Shuai Qigong improved climacteric symptoms and sleep quality in perimenopausal women at 6 weeks and 12 weeks. The longer a person practiced this form of meditative exercise, the greater the improvement in sleeping quality and climacteric symptoms.