Association between Elder Mistreatment and Suicidal Ideation among Community-Dwelling Chinese Older Adults in the USA.

BACKGROUND: Elder mistreatment and suicidal ideation are important public health concerns among aging populations. However, very few studies have been conducted to explore the association between elder mistreatment and suicidal ideation. OBJECTIVES: To examine the association between elder mistreatment and suicidal ideation among Chinese older adults in the USA. METHODS: Guided by a community-based participatory research approach, in this study we conducted in-person interviews with Chinese older adults aged 60 years and older in the Greater Chicago area from 2011 to 2013. Elder mistreatment was assessed by a 10-item instrument derived from the Hwalek-Sengstock Elder Abuse Screening Test (H-S/EAST) and the Vulnerability to Abuse Screening Scale (VASS). Suicidal ideation was assessed by the ninth item of the Patient Health Questionnaire-9 (PHQ-9) and the Geriatric Mental State Examination-Version A (GMS-A). RESULTS: Overall, 3,159 Chinese older adults participated in this study, and their mean age was 72.8 years. After controlling for age, gender, education, income, medical comorbidities, depressive symptoms, and social support, elder mistreatment was significantly associated with 2-week suicidal ideation (OR 2.46, 95% CI 1.52-4.01) and 12-month suicidal ideation (OR 2.46, 95% CI 1.62-3.73). With respect to gender differences, the study found that the association remained significant for older women but not for older men after adjusting for all confounding factors. CONCLUSION: As the largest epidemiological study conducted among Chinese older adults in the USA, this study suggests that elder mistreatment is significantly associated with 2-week and 12-month suicidal ideation in older women but not in older men. Longitudinal studies should be conducted to explore the mechanisms through which elder mistreatment links with suicidal ideation.

The impact of demographic and perceptual variables on a young adult's decision to be covered by private health insurance.

BACKGROUND: The large number of uninsured individuals in the United States creates negative consequences for those who are uninsured and for those who are covered by health insurance plans. Young adults between the ages of 18 and 24 are the largest uninsured population subgroup. This subgroup warrants analysis. The major aim of this study is to determine why young adults between the ages of 18 and 24 are the largest uninsured population subgroup. METHODS: The present study seeks to determine why young adults between the ages of 18 and 24 are the largest population subgroup that is not covered by private health insurance. Data on perceived health status, perceived need, perceived value, socioeconomic status, gender, and race was obtained from a national sample of 1,340 young adults from the 2005 Medical Expenditure Panel Survey and examined for possible explanatory variables, as well as data on the same variables from a national sample of 1,463 from the 2008 Medical Expenditure Panel Survey. RESULTS: Results of the structural equation model analysis indicate that insurance coverage in the 2005 sample was largely a function of higher socioeconomic status and being a non-minority. Perceived health status, perceived need, perceived value, and gender were not significant predictors of private health insurance coverage in the 2005 sample. However, in the 2008 sample, these indicators changed. Socioeconomic status, minority status, perceived health, perceived need, and perceived value were significant predictors of private health insurance coverage. CONCLUSIONS: The results of this study show that coverage by a private health insurance plan in the 2005 sample was largely a matter of having a higher socioeconomic status and having a non-minority status. In 2008 each of the attitudinal variables (perceived health, perceived value, and perceived need) predicted whether subjects carried private insurance. Our findings suggest that among those sampled, the young adult subgroup between the ages of 18 and 24 does not necessarily represent a unique segment of the population, with behaviors differing from the rest of the sample.

Impact of health literacy on medication adherence: a systematic review and meta-analysis.

OBJECTIVE: To systematically review the literature and estimate the effect size of the relationship between health literacy and medication adherence through meta-analysis. DATA SOURCES: Databases searched included Cumulative Index to Nursing and Allied Health Literature (CINAHL; 1982-2013), International Pharmaceutical Abstracts (IPA; 1970-2013), MEDLINE OVID (1966-2013), PubMed (1966-2013), PsycInfo (1966-2013), and Web of Science (1966-2013). STUDY SELECTION AND DATA EXTRACTION: Inclusion criteria were as follows: English language; published through May 1, 2013; medication adherence as the outcome variable; use of validated measures of health literacy and medication adherence; availability of a direct (not mediating) relationship between health literacy and medication adherence; and identifiable effect size and statistical significance of the relationship. Exclusion criteria were as follows: duplicated results, irrelevant results, conference abstracts, proceeding papers, books, dissertations, reviews, editorial letters, continuing education units, or book reviews. Data included author, publication year, disease area, sample size, sampling method, location, study design, effect size of the relationship between health literacy and medication adherence, and measures of health literacy and medication adherence. DATA SYNTHESIS: There is a small statistically significant and positive association between health literacy and medication adherence. In the conservative results, the unweighted and weighted correlation coefficients were 0.081 and 0.056 with P values <0.001. In the less conservative results, the unweighted and weighted correlation coefficients were 0.088 and 0.072. CONCLUSIONS: The relationship between health literacy and medication adherence is statistically significant but weak. It is plausible that health literacy has a mediator relationship with other adherence determinants. Future research should explore such relationships.

The Hospital Work Environment And Job Satisfaction of Newly Licensed Registered Nurses.

In prior studies, newly licensed registered nurses (NLRNs) described their job as being stressful. Little is known about how the hospital work environment affects their job satisfaction. A random sample of NLRNs were surveyed to assess the influence of hospital work environment on job satisfaction. Perceptions of greater job difficulty, job demands, and patient load were significantly related to lower job satisfaction. In contrast, being White, working 12-hour shifts, working more hours, and having more job control, greater professional tenure, and a perception of a better initial orientation were significantly related to higher job satisfaction.

Factors associated with the use of annual health checkups in Thailand: evidence from a national cross-sectional health and welfare survey.

Introduction: Thailand has provided free annual health checkups (AHC) since universal health coverage began in 2002. However, evidence regarding the equitable use of AHC is scarce. Thus, this study explored factors associated with the use of AHC in Thailand. Methods: A cross-sectional study was conducted using data from the national 2015 Health and Welfare Survey. Respondents aged 15 years or above (n = 57,343) were selected as the study sample. Descriptive statistical analysis and multivariable binary logistic regression were conducted to examine the association between the use of AHC and factors selected on the basis on Andersen's Behavioral Model of Access to Medical Care. Results: Among the study sample, approximately 4.9% (n = 2,815) had used AHC during the past year. Regarding predisposing factors, the use of AHC was positively related to age (e.g., over 61 vs. 15-30: AOR = 2.90 [95% CI = 2.40-3.52], p < 0.001) and female sex (AOR = 1.23 [95% CI = 1.12-1.35] p < 0.001). For enabling factors, the AHC use was positively associated with income (e.g., Q4 vs. Q1: AOR = 1.98 [95% CI = 1.75-2.25], p < 0.001), education (e.g., high vs. low: AOR = 3.11 [95% CI = 2.75-3.51], p < 0.001), being married (e.g., vs. single: AOR = 1.27 [95% CI = 1.11-1.46], p < 0.001), and urban residency (AOR = 1.12 [95% CI = 1.04-1.22], p = 0.006). For need-for-care factors, the AHC use was positively related to chronic disease (AOR = 1.26 [95% CI = 1.15-1.38], p < 0.001), non-smoking (e.g., vs. daily: AOR = 1.18 [95% CI = 1.03-1.36], p = 0.015), non-drinking (e.g., vs. 3-4 times per week: AOR = 1.26 [95% CI = 1.04-1.53], p = 0.016), and vegetable consumption (e.g., over 5 ladles vs. below 1 ladle: AOR = 1.86 [95% CI = 1.50-2.31], p < 0.001). Conclusion: The results indicate that health awareness could play a significant role in the use of AHC. Individuals with high socioeconomic status (e.g., high-income people) and those with low-risk health behaviors (e.g., non-smokers) generally have a high interest in health and well-being. This may have been the primary reason for the high use of AHC among these groups. Thus, the government should continue to promote the public's health awareness through various public campaigns and education programs to increase the use of AHC.

Health information technology adoption in U.S. acute care hospitals.

Previous studies show that the healthcare industry lags behind many other economic sectors in the adoption of information technology. The purpose of this study is to understand differences in structural characteristics between providers that do and that do not adopt Health Information Technology (HIT) applications. Publicly available secondary data were used from three sources: American Hospital Association (AHA) annual survey, Healthcare Information and Management Systems Society (HIMSS) analytics annual survey, and Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) databases. Fifty-two information technologies were grouped into three clusters: clinical, administrative, and strategic decision making ITs. Negative binomial regression was applied with adoption of technology as the dependent variables and eight organizational and contextual factors as the independent variables. Hospitals adopt a relatively larger proportion of administrative information technology as compared to clinical and strategic IT. Large size, urban location and HMO penetration were found to be the most influential hospital characteristics that positively affect information technology adoption. There are still considerable variations in the adoption of information technology across hospitals and in the type of technology adopted. Organizational factors appear to be more influential than market factors when it comes to information technology adoption. The future research may examine whether the Electronic Health Record (EHR) Incentive Program in 2011 would increase the information technology uses in hospitals as it provides financial incentives for HER adoptions and uses among providers.

Gaps in nurse staffng and nursing home resident needs.

Trends in nurse staffing levels in nursing homes from 1997 to 2011 varied across the category of nurse and the type of nursing home. The gaps found in this study are important to consider because nurses may become overworked and this may negatively affect the quality of services and jeopardize resident safety. Nursing home administrators should consider improving staffing strategically. Staffing should be based not only on the number of resident days, but also allocated according to particular resident needs. As the demand for nursing home care grows, bridging the gap between nurse staffing and resident nursing care needs will be especially important in light of the evidence linking nurse staffing to the quality of nursing home care. Until more efficient nursing care delivery exits, there may be no other way to safeguard quality except to increase nurse staffing in nursing homes.

Nurse staffing and patient safety in hospitals: new variable and longitudinal approaches.

BACKGROUND: Most studies of the relationship between nurse staffing and patient outcomes in hospitals have shown that worse patient outcomes are associated with lower registered nurse (RN) staffing. However, inconsistent results exist, possibly because of the use of a variety of nurse staffing and patient outcomes measures and because of statistical methods that employ static, instead of change, relationships. OBJECTIVES: The aim of the study was to examine the relationship between changes in RN staffing and patient safety events in Florida hospitals from 1996 through 2004. METHODS: Using 9 years of data from 124 Florida hospitals, latent growth curve models were used to assess the impact on patient safety of RN staffing changes in hospitals. Patient safety measures were 4 of the 20 provider-level patient safety indicators (PSIs) developed by the Agency for Healthcare Research and Quality. Two measures of RN staffing-RN full-time equivalents and RN per adjusted patient day-were analyzed. RESULTS: Changes in RN full-time equivalents were positively related to changes in RN per adjusted patient day. All PSIs were negatively and significantly related to one or both RN staffing measures. Failure to rescue had the strongest relationship to RN staffing. Models of change relationships between staffing and PSIs were more likely to show significant relationships than models using initial levels. Initial levels of RN staffing tended to be unrelated to initial levels of PSIs. DISCUSSION: A negative relationship between RN staffing and PSIs was strongly supported with failure to rescue and was weakly supported with decubitus ulcers, selected infections, and postoperative sepsis. The PSIs should be retested in an expanded change model study using multistate or national sample Healthcare Cost and Utilization Project data.

Reliability estimates of clinical measures between Minimum Data Set and Online Survey Certification and Reporting data of US nursing homes.

BACKGROUND: Evidence-based quality improvement in nursing homes relies heavily on administrative data. Minimum Data Set (MDS) and Online Survey Certification and Reporting (OSCAR) are the 2 largest sources of national nursing home administrative data. Although clinical measures in each of the data systems have frequently and independently been used to measure nursing home performance, no study has systematically examined their relative reliability. OBJECTIVES: This study estimates the reliability of clinical measures between MDS and OSCAR data and discusses the utility of these databases in research. RESEARCH DESIGN: We analyzed 4 waves of national MDS and OSCAR data (1999-2002). A comparable group of 24 clinical indicators from both datasets was selected for the reliability test. Spearman rank-order correlation analyses were used to measure the test-retest reliability relationships. RESULTS: Across the 4 years, the majority of coefficients of clinical measures exhibit good reliability. There are 17 clinical measures (71% of the total measures) with correlation coefficients greater than 0.4, the minimally acceptable reliability threshold according to Morris. The highest correlation coefficients were associated with tube feeding at 0.883. CONCLUSIONS: Our findings indicate that the target clinical measures in OSCAR and MDS are generally consistent and reliable. However, researchers should use OSCAR self-reported clinical measures to measure nursing home outcomes in place of corresponding MDS clinical measures with caution because some indicators in the administrative data are more reliable than others.

Has the Medicare prospective payment system led to increased nursing home efficiency?

RESEARCH OBJECTIVE: To assess the impact of recent Medicare prospective payment system (PPS) changes on efficiency in skilled nursing homes. DATA SOURCE/STUDY SETTING: Medicare Cost Reports (MCR), On-line Survey Certification and Reporting System (OSCAR), Area Resource Files (ARF), a Centers for Medicare and Medicaid Services (CMS) hospital wage index website, a Consumer Price Index (CPI) database, and a survey of state Medicaid reimbursement rates. The sample was 8,361 nursing homes in the Medicare Cost Report databases from the years 1997 to 2003. STUDY DESIGN: Data-envelopment analyses (DEA) calculated efficiency scores for three separate DEA models: unadjusted, acuity-adjusted, and acuity-and-quality-adjusted efficiency. The efficiency scores from these models were regressed on the Medicare PPS changes (the Balanced Budget Act [BBA], the Balanced Budget Refinement Act [BBRA] and the Benefits Improvement and Protection Act) and other organizational and market explanatory variables using a panel-data truncated regression. PRINCIPAL FINDINGS: Mean values for all efficiency measures decreased over time, the acuity-quality-adjusted efficiency measures decreasing the most. All policy variables were significantly negatively related to all efficiency measures. Higher nurse staffing was negatively related to efficiency in all but the acuity-quality-adjusted model. Other explanatory variables varied in their relationships to the efficiency variables. CONCLUSIONS: The results suggest that the reimbursement policy changes had a significantly negative impact on efficiency. Higher nurse staffing contributed to lower efficiency only when efficiency was not adjusted for quality. Various organizational and market factors also played significant roles in all efficiency models.

Facility service environments, staffing, and psychosocial care in nursing homes.

Using 2003 Online Survey Certification and Reporting (OSCAR) data for Medicare and Medicaid certified facilities (N = 14, 184) and multinomial logistic regression this study investigated if (1) psychosocial care quality was better in facilities where State requirements for qualified social services staffing exceeded Federal minimum regulations and (2) facility service environments are associated with psychosocial care quality. For-profit status and higher percentage of Medicaid residents are associated with lower quality. Staffing, market demand, and market competition are associated with better quality. Psychosocial care quality is more associated with payer status and market forces and less with regulatory requirements.

Evaluation of chronic disease management on outcomes and cost of care for Medicaid beneficiaries.

OBJECTIVES: To evaluate the impacts of the chronic disease management program on the outcomes and cost of care for Virginia Medicaid beneficiaries. METHODS: A total of 35,628 patients and their physicians and pharmacists received interventions for five chronic diseases and comorbidities from 1999 to 2001. Comparisons of medical utilization and clinical outcomes between experimental groups and control group were conducted using ANOVA and ANCOVA analyses. RESULTS: Findings indicate that the disease state management (DSM) program statistically significantly improved patient's drug compliance and quality of life while reducing (ER), hospital, and physician office visits and adverse events. The average cost per hospitalization would have been $42 higher without the interventions. CONCLUSIONS: A coordinated disease management program designed for Medicaid patients experiencing significant chronic diseases can substantially improve clinical outcomes and reduce unnecessary medical utilization, while lowering costs, although these results were not observed across all disease groups. The DSM model may be potentially useful for Medicaid programs in states or other countries. If the adoption of the DSM model is to be promoted, evidence of its effectiveness should be tested in broader settings and best practice standards are expected.

Association Between Perceived Social Support and Depressive Symptoms Among Community-Dwelling Older Chinese Americans.

Purpose: This study examined the association between social support and depressive symptoms among U.S. Chinese older adults. Methods: Data were from the Population Study of Chinese Elderly in Chicago (PINE) study. Independent variables were positive and negative perceived social support (PSS). Dependent variable was depressive symptoms. Multinomial logistic regression analyses were performed. Results: A total of participants were 3,157 Chinese older adults with the mean age of 72.8 years (range 60-105 years). After controlling for confounding factors, Chinese older adults with higher positive PSS were 12% (odds ratio [OR] = 0.88, 95% confidence interval [CI] = [0.85, 0.92]) and 18% (OR = 0.82, 95% CI = [0.79, 0.86]) less likely to report mild and moderate-severe depressive symptoms, respectively, compared to reporting minimal depressive symptoms; On the contrary, Chinese older adults with higher negative PSS were 34% (OR = 1.34, 95% CI = [1.24, 1.46]) and 38% (OR = 1.38, 95% CI = [1.26, 1.52]) more likely to report mild and moderate-severe depressive symptoms, respectively. Discussion: The study findings corroborate previous research that social support is significantly associated with depressive symptoms. Our findings reinforce the importance of developing strategies to utilize positive social support and limit negative support in practice for the depressed older adults. Further studies should be conducted to better understand the associations between different dimensions of social support and depression among U.S. Chinese older adults.

Effects of institutional mechanisms on nursing home quality.

This study explores institutional mechanisms explaining the variation in nursing home quality. A two-level panel design with the national data is conducted. Structural equation modeling is employed to examine the main and interaction effects of institutional factors on nursing home quality at both facility and state levels. The findings indicate that the quality of nursing homes is more responsive to regulatory and payment constraints than to normative and mimetic mechanisms. The potential demand for care, Medicaid reimbursement rate, and occupancy rate are positively associated with nursing home quality. An interaction effect between the regulatory mechanism and nurse staffing is statistically significant. The findings lend support to the importance of multi-level analysis of nursing home quality.

An Early Look at the Association Between State Medicaid Expansion and Disparities in Cardiovascular Diseases: A Comprehensive Population Health Management Approach.

Cardiovascular disease (CVD) is one of the most prevalent chronic diseases nationally and disproportionately affects low-income individuals. There are substantial disparities on CVD outcomes that stem from the lack of health insurance among low-income populations. The Affordable Care Act expands Medicaid health insurance to low-income populations, and aims to increase the utilization of health, social, and economic preventive services to reduce health disparities and prevent chronic diseases. The authors analyzed data from the 2014 Behavioral Risk Factor Surveillance System to understand the potential impact of Medicaid expansion on disparities in CVD among low-income populations. Logistic regression models examined the association between CVD self-reported outcomes among low-income adults with incomes at or below 138% of the federal poverty level in states that have chosen to expand Medicaid and those states choosing not to expand, controlling for socioeconomic, demographic, behavioral, social, and health variables that affect CVD. Overall, the results show that adults in Medicaid expansion states have significantly lower odds of experiencing poor heart health compared to those in non-Medicaid expansion states (odds ratio = 0.767, 95% confidence interval 0.667-0.882). Additionally, significant findings were found between the association of CVD and demographic, socioeconomic, health, and health behavioral covariates. Policy makers should consider policies, systems, and interventions that increase access to a comprehensive set of preventive, population health, and socioeconomic services targeting the key determinants of CVD and other outcomes when expanding Medicaid and designing state plans and waivers.

Predictors of resident outcome improvement in nursing homes.

The effects of contextual characteristics and nursing-related factors on the overall quality improvement of resident outcomes, measured by a weighted index in incidents of pressure ulcers, physical restraints, and catheter use in nursing homes, were investigated by autoregressive latent trajectory modeling of panel data (1997-2003). Findings show that in the initial study period, nursing homes with a smaller bed size, being for-profit, caring for more Medicare residents, having residents with lower acuity levels, being located elsewhere than the South, having a high level of nurse staffing, and certified with lower frequencies of nursing care deficiencies had better quality. The intercept factor, representing the baseline of quality, was well predicted by six of the eight contextual and facility characteristics variables, and the slope trajectory of quality was only weakly predicted by them. The improved quality in resident outcomes was associated with facilities having fewer nursing care deficiency citations than their counterparts.

Minimum nurse staffing ratios for nursing homes.

The authors explored minimum nurse staffing ratios for nursing homes using production function simulations. Minimum levels of registered nurse hours per resident day were 0.31, 1.83, and 3.3 at 50%, 75%, and 90% levels of quality respectively. These results suggest that efficiency-oriented minimum nurse staffing points exist, and could be used to inform policymakers and nursing home administrators on better resource allocation and health care delivery.

The Impact of Tobacco-Free School Policies on Youth Smoking Rates in Florida Public School Districts.

BACKGROUND: Developing and implementing policies to curb and prevent youth tobacco use is of the utmost importance. In Florida, public school districts were authorized to develop tobacco-free school policies through an amendment to the Florida Clean Indoor Air Act in 2011. The purpose of this study is to determine the impact of tobacco-free school policies on smoking rates among youth in Florida. METHODS: Analysis of covariance (ANCOVA) and a multiple regression analysis were used to determine whether the comprehensiveness and enforcement of tobacco-free school policies affect the youth smoking rates within Florida public school districts. The 2010 and 2014 youth smoking rates were calculated based on the Florida Youth Tobacco Survey results. RESULTS: The 2010 youth smoking rate and the inclusion of the enforcement component with provision of cessation resources were statistically significant predictors of the 2014 youth smoking rate. However, the comprehensiveness level of a policy and the inclusion of an enforcement component were not statistically significant predictors. CONCLUSIONS: The inclusion of an enforcement component with provision of cessation resources is important in efforts to reduce youth smoking rates. The content of the tobacco-free school policies seems to be less relevant to their effectiveness than the enforcement of the policies.

Job and Professional Leaving Among Newly Licensed RNs: A Structural Equation Model.

With more than 50% of the nursing workforce close to retirement, it is especially important to keep younger nurses in nursing jobs and careers. This study empirically tests a structural equation model of registered nurse (RN) intent to leave the job and profession using data from a survey of newly licensed RNs (NLRNs). Job demands, difficulties and control, intent to leave the job, and intent to leave the profession were latent variables. A number of direct, indirect, and mediating relationships were modeled. Measurement models for all latent variables and the structural model had good fit. The final model showed a path from job demands, difficulties, and control to job satisfaction to intent to leave the job to intent to leave the profession. The results suggest that the process of an NLRN intending to leave the job and profession involves a number of mediators between the work environment and this intent.

Newly licensed registered nurse job turnover and turnover intent.

Through survey data, this study examines job leaving behaviors of newly licensed registered nurses and identifies educational and managerial issues that need to be addressed to retain them. Within 1.5-2.5 years of graduating, one third of all respondents had left their first job, most for work-related reasons. Predictors of job leaving or intentions to leave included not having had a good orientation, information issues, having difficulties doing a good job, not being rewarded fairly, and low job satisfaction.